[[File:CUNY-HPCC-HEADER-LOGO.jpg]]

__TOC__

[[Image:hpcc-panorama3.png]]

The City University of New York (CUNY) High Performance Computing Center (HPCC) is located on the
campus of the College of Staten Island, 2800 Victory Boulevard, Staten Island, New York 10314. HPCC
goals are to:

:*Support the scientific computing needs of CUNY faculty, their collaborators at other universities, and their public and private sector partners, and CUNY students and research staff.
:*Create opportunities for the CUNY research community to develop new partnerships with the government and private sectors; and
:*Leverage the HPC Center capabilities to acquire additional research resources for its faculty and graduate students in existing and major new programs.

==Organization of systems and data storage (architecture)==

All user data and project data are kept on Data Storage and Management System ('''DSMS''') which is mounted only on login node(s) of all servers. Consequently, no jobs can be started directly from '''DSMS''' storage. Instead, all jobs must be submitted from a separate (fast but small) '''/scratch''' file system mounted on all computational nodes and on all login nodes. As the name suggests, the '''/scratch''' file system is not home directory for accounts nor can be used for long term data preservation. Users must use "staging" procedure described below to ensure preservation of their data, codes and parameters files. The figure below is a schematic of the environment.

Upon registering with HPCC every user will get 2 directories:

:• '''<font face="courier">/scratch/<font color="red"><userid></font color></font>''' – this is temporary workspace on the HPC systems
:• '''<font face="courier">/global/u/<font color="red"><userid></font color></font>''' – space for “home directory”, i.e., storage space on the DSMS for program, scripts, and data

:• In some instances a user will also have use of disk space on the DSMS in '''<font face="courier">/cunyZone/home/<font color="red"><projectid></font color></font>''' (IRods).

The '''/global/u/<userid>''' directory has quota (see below for details) while the '''/scratch/<userid>''' do not have. However the '''/scratch''' space is cleaned up following the rules described below. There are no guarantees of any kind that files in '''/scratch''' will be preserved during the hardware crashes or cleaning up. Access to all HPCC resources is provided by bastion host called ''''''chizen'''''. The Data Transfer Node called '''Cea''' allows file transfer from/to remote sites directly to/from '''<font face="courier">/global/u/<font color="red"><userid></font color></font>''' or to/from '''<font face="courier">/scratch/<font color="red"><userid></font color></font>''' [[Image:HPCC_structure.png|frameless|900x900px]]

==HPC systems==

The HPC Center operates variety of architectures in order to support complex and demanding workflows. The deployed systems include: distributed memory (also referred to as “cluster”) computers, symmetric multiprocessor (also referred as SMP) and shared memory (also reffred as NUMA machines).

''Computational Systems'':

'''SMP''' servers have several processors (working under a single operating system) which "share everything". Thus all cpu-cores allocate a common memory block via shared bus or data path. SMP servers support all combinations of memory VS cpu (up to the limits of the particular computer). The SMP servers are commonly used to run sequential or thread parallel (e.g. OpenMP) jobs and they may have or may not have GPU. Currently, HPCC operates 3 SMP servers named '''Math, Cryo ''' and '''Karle'''. Karle is a server which does not have GPU and is used for visualizations, visual analytics and interactive MATLAB/Mathematica jobs. '''Math''' is a condominium server without GPU as well. Cryo (CPU+GPU server) is specialized server designed to support large scale multi-core multi-GPU jobs.

'''Cluster''' is defined as a single system comprizing a set of SMP servers interconnected with high performance network. Specific software coordinates programs on and/or across those in order to perform computationally intensive tasks. Each SMP member of the cluster is called a node. All nodes run independent copies of the same operating system (OS). Some or all of the nodes may incorporate GPU. The main cluster at HPCC is a hybrid (CPU+GPU) cluster called '''Penzias'''. Sixty six (66) of Penzias nodes have 2 x GPU K20m, and the 3 fat nodes (nodes with large number of CPU-cores and memory) of the cluster do not have GPU. In addition HPCC operates the cluster '''Herbert''' dedicated only to education.

'''Distributed shared memory''' computer is tightly coupled server in which the memory is physically distributed, but it is logically unified as a single block. The system resembles SMP, but the number of cpu cores and the amounts of memory possible is far beyond limitations of the SMP. Because the memory is distributed, the access times across address space are non-uniform. Thus, this architecture is called Non Uniform Memory Access (NUMA) architecture. Similarly to SMP, the '''NUMA''' systems are typically used for applications such as data mining and decision support system in which processing can be parceled out to a number of processors that collectively work on a common data. HPCC operates the '''NUMA''' server called '''Appel'''. This server does not have GPU.

'' Infrastructure systems'':

o Master Head Node ('''MHN''') is a redundant login node from which all jobs on all servers start. This server is not directly accessible from outside CSI campus.

o '''Chizen''' is a redundant gateway server which provides access to protected HPCC domain.

o '''Cea''' is a file transfer node allowing transfer of files between users’ computers to/from /scratch space or to/from /global/u/<usarid>. '''Cea''' is accessible directly (not only via '''Chizen'''), but allows only limited set of shell commands.

'''Table 1''' below provides a quick summary of the attributes of each of the systems available at the HPC Center.
{| class="wikitable"
|+
!System
!Type
!Type of Jobs
!Nodes
!Cores/node & GPU
!Mem/node
!Mem/core
!Multi-core Processor
|-
| rowspan="4" |Penzias
| rowspan="4" |Hybrid Cluster
|Sequential & Parallel jobs w/wo GPU
|66
|16
2xK20m GPU, PCIe
|64 GB
|4 GB
|Sand Bridge, EP 2.20 GHz
|-
| rowspan="3" |Sequential & Parallel jobs
| rowspan="3" |1
|24
|1500 GB
|62 GB
| rowspan="3" |Haswell, 2.30 GHz
|-
|36
|768 GB
|21 GB
|-
|24
|768 GB
|32 GB
|-
|Appel
|NUMA
|Massive Parallel, sequential
|1
|384
|11 TB
|28 GB
|Ivy Bridge, 3 GHz
|-
|Cryo
|SMP
|Sequential and Parallel jobs, with GPU
|1
|40 8xV100 (32GB) GPU, XSM
|1500 GB
|37 GB
|Skylake, 2.40 GHz
|-
| rowspan="2" |Blue Moon
| rowspan="2" |Hybrid Cluster
| rowspan="2" |Sequential and Parallel jobs w/wo GPU
|24
|32
| rowspan="2" |192 GB
| rowspan="2" |6 GB
| rowspan="2" |Skylake, 2.10 GHz
|-
|2
|32
2xV100(16GB) GPU, PCIe
|-
|Karle
|SMP
|Visualization, MATLAB/Mathematica
|1
|36*
|768 GB
|21 GB
|Haswell, 2.30 GHz
|-
|Chizen
|Gateway
|2
| colspan="5" rowspan="2" |NA
|-
|MHN
|Login Nodes
|2
|}

==Partitions and jobs==
The only way to submit job(s) to HPCC servers is through SLURM batch system. Any job despite of its type (interactive, batch, serial, parallel etc.) must be submitted via SLURM. The latter allocates the requested resources on proper server and starts the job(s) according to predefined strict fair share policy. Computational resources (cpu-cores, memory, GPU) are organized in partitions. The main partition is called production. This is routing partition which distributes the jobs in several sub-partitions depend on job’s requirements. Thus the serial job submitted in '''production''' will land in '''partsequential''' partition. No SLURM Pro scripts should be ever used and all existing SLURM scripts must be converted to SLURM before use. The table below shows the limitations of the partitions.
{| class="wikitable"
|+
!Partition
!Max cores/job
!Max jobs/user
!Total cores/group
!Time limits
|-
|production
|128
|50
|256
|240 Hours
|-
|partedu
|16
|2
|216
|72 Hours
|-
|partcryo
|40
|40
|40
|240 Hours
|-
|partmath
|128
|128
|128
|240 Hours
|-
|partmatlab
|1972
|50
|1972
|240 Hours
|-
|partdev
|16
|16
|16
|4 Hours
|}
o '''production''' is the main partition with assigned resources across all servers (except Math and Cryo).It is routing partition so the actual job(s) will be placed in proper sub-partition automatically. Users may submit sequential, thread parallel or distributed parallel jobs with or without GPU.

o '''partedu''' partition is only for education. Assigned resources are on educational server Herbert. Partedu is accessible only to students (graduate and/or undergraduate) and their professors who are registered for a class supported by HPCC. Access to this partition is limited by the duration of the class.

o '''partcryo''' is partition used to start jobs on CRYO server. Users whose projects require and/or benefit from availability of 8 GPU interconnected via SXM interface (not PCIe) must apply for access to this partition at hpchelp@csi.cuny.edu.

o '''partmatlab''' partition allows to run MATLAB's Distributes Parallel Server across main cluster. Note however that parallel toolbox programs can be submitted via production partition, but only as thread parallel jobs.

o '''partdev''' is dedicated to development. All HPCC users have access to this partition with assigned resources of one computational node with 16 cores, 64 GB of memory and 2 GPU (K20m). This partition has time limit of 4 hours.

== Hours of Operation ==
The second and fourth Tuesday mornings in the month from 8:00AM to 12PM are normally reserved (but not always used) for scheduled maintenance. Please plan accordingly. <br/ >
Unplanned maintenance to remedy system related problems may be scheduled as needed. Reasonable attempts will be made to inform users running on those systems when these needs arise.

== User Support ==
Users are encouraged to read this Wiki carefully. In particular, the sections on compiling and running
parallel programs, and the section on the SLURM batch queueing system will give you the essential
knowledge needed to use the CUNY HPC Center systems. We have strived to maintain the most uniform
user applications environment possible across the Center's systems to ease the transfer of applications
and run scripts among them. Still, there are some differences, particularly with the SGI (ANDY) and Cray (SALK)
systems.

The CUNY HPC Center staff, along with outside vendors, offer regular courses and workshops to the CUNY
community in parallel programming techniques, HPC computing architecture, and the essentials of using our
systems. Please follow our mailings on the subject and feel free to inquire about such courses. We regularly
schedule training visits and classes at the various CUNY campuses. Please let us know if such a training visit
is of interest. In the past, topics have include an overview of parallel programming, GPU programming and
architecture, using the evolutionary biology software at the HPC Center, the SLURM queueing system at the
CUNY HPC Center, Mixed GPU-MPI and OpenMP programming, etc. Staff has also presented guest lectures
at formal classes throughout the CUNY campuses.

Users with further questions or requiring immediate assistance in use of the systems should create a ticket using their HPC account login at:

[https://hpchelp.csi.cuny.edu hpchelp.csi.cuny.edu]

If you have problems accessing your account and cannot login to the ticketing service, please send an email to:

[mailto:hpchelp@csi.cuny.edu hpchelp@csi.cuny.edu]

== Warnings and modes of operation ==

1. hpchelp@csi.cuny.edu is for questions and accounts help communication '''only''' and does not accept tickets. For tickets please use the ticketing system mentioned above. This ensures that the person on staff with the most appropriate skill set and job related responsibility will respond to your questions. During the business week you should expect a 48h response, quite often even same day response. During the weekend you may not get any response.

2. '''E-mails to hpchelp@csi.cuny.edu must have a valid CUNY e-mail as reply address.''' Messages originated from public mailers (google, hotmail, etc) are filtered out.

3. '''Do not send questions to individual CUNY HPC Center staff members directly.''' These will be returned to the sender with a polite request to submit a ticket or email the Helpline. This applies to replies to initial questions as well.

The CUNY HPC Center staff members are focused on providing high quality support to its user community, but compared
to other HPC Centers of similar size '''our staff is extremely lean'''. Please make full use of the tools that we have provided (especially
the Wiki), and feel free to offer suggestions for improved service. We hope and expect your experience in using
our systems will be predictably good and productive.

== User Manual ==

An old version of the user manual can be downloaded at: http://cunyhpc.csi.cuny.edu/publications/User_Manual.pdf. Note that this manual provides SLURM batch scripts as examples. Currently CUNY-HPCC uses SLURM so users must check the brief SLURM manual distributed with new accounts or ask CUNY-HPCC for a copy of the latter.

File:HPCC structure.png

2022-11-07T17:37:46Z

James: James uploaded a new version of File:HPCC structure.png

Main Page

2022-11-07T17:35:37Z

James:

[[File:CUNY-HPCC-HEADER-LOGO.jpg]]

__TOC__

[[Image:hpcc-panorama3.png]]

The City University of New York (CUNY) High Performance Computing Center (HPCC) is located on the
campus of the College of Staten Island, 2800 Victory Boulevard, Staten Island, New York 10314. HPCC
goals are to:

:*Support the scientific computing needs of CUNY faculty, their collaborators at other universities, and their public and private sector partners, and CUNY students and research staff.
:*Create opportunities for the CUNY research community to develop new partnerships with the government and private sectors; and
:*Leverage the HPC Center capabilities to acquire additional research resources for its faculty and graduate students in existing and major new programs.

==Organization of systems and data storage (architecture)==

All user data and project data are kept on Data Storage and Management System ('''DSMS''') which is mounted only on login node(s) of all servers. Consequently, no jobs can be started directly from '''DSMS''' storage. Instead, all jobs must be submitted from a separate (fast but small) '''/scratch''' file system mounted on all computational nodes and on all login nodes. As the name suggests, the '''/scratch''' file system is not home directory for accounts nor can be used for long term data preservation. Users must use "staging" procedure described below to ensure preservation of their data, codes and parameters files. The figure below is a schematic of the environment.

Upon registering with HPCC every user will get 2 directories:

:• '''<font face="courier">/scratch/<font color="red"><userid></font color></font>''' – this is temporary workspace on the HPC systems
:• '''<font face="courier">/global/u/<font color="red"><userid></font color></font>''' – space for “home directory”, i.e., storage space on the DSMS for program, scripts, and data

:• In some instances a user will also have use of disk space on the DSMS in '''<font face="courier">/cunyZone/home/<font color="red"><projectid></font color></font>''' (IRods).

The '''/global/u/<userid>''' directory has quota (see below for details) while the '''/scratch/<userid>''' do not have. However the '''/scratch''' space is cleaned up following the rules described below. There are no guarantees of any kind that files in '''/scratch''' will be preserved during the hardware crashes or cleaning up. Access to all HPCC resources is provided by bastion host called ''''''chizen'''''. The Data Transfer Node called '''Cea''' allows file transfer from/to remote sites directly to/from '''<font face="courier">/global/u/<font color="red"><userid></font color></font>''' or to/from '''<font face="courier">/scratch/<font color="red"><userid></font color></font>'''

[[Image:HPCC_structure.png]]

==HPC systems==

The HPC Center operates variety of architectures in order to support complex and demanding workflows. The deployed systems include: distributed memory (also referred to as “cluster”) computers, symmetric multiprocessor (also referred as SMP) and shared memory (also reffred as NUMA machines).

''Computational Systems'':

'''SMP''' servers have several processors (working under a single operating system) which "share everything". Thus all cpu-cores allocate a common memory block via shared bus or data path. SMP servers support all combinations of memory VS cpu (up to the limits of the particular computer). The SMP servers are commonly used to run sequential or thread parallel (e.g. OpenMP) jobs and they may have or may not have GPU. Currently, HPCC operates 3 SMP servers named '''Math, Cryo ''' and '''Karle'''. Karle is a server which does not have GPU and is used for visualizations, visual analytics and interactive MATLAB/Mathematica jobs. '''Math''' is a condominium server without GPU as well. Cryo (CPU+GPU server) is specialized server designed to support large scale multi-core multi-GPU jobs.

'''Cluster''' is defined as a single system comprizing a set of SMP servers interconnected with high performance network. Specific software coordinates programs on and/or across those in order to perform computationally intensive tasks. Each SMP member of the cluster is called a node. All nodes run independent copies of the same operating system (OS). Some or all of the nodes may incorporate GPU. The main cluster at HPCC is a hybrid (CPU+GPU) cluster called '''Penzias'''. Sixty six (66) of Penzias nodes have 2 x GPU K20m, and the 3 fat nodes (nodes with large number of CPU-cores and memory) of the cluster do not have GPU. In addition HPCC operates the cluster '''Herbert''' dedicated only to education.

'''Distributed shared memory''' computer is tightly coupled server in which the memory is physically distributed, but it is logically unified as a single block. The system resembles SMP, but the number of cpu cores and the amounts of memory possible is far beyond limitations of the SMP. Because the memory is distributed, the access times across address space are non-uniform. Thus, this architecture is called Non Uniform Memory Access (NUMA) architecture. Similarly to SMP, the '''NUMA''' systems are typically used for applications such as data mining and decision support system in which processing can be parceled out to a number of processors that collectively work on a common data. HPCC operates the '''NUMA''' server called '''Appel'''. This server does not have GPU.

'' Infrastructure systems'':

o Master Head Node ('''MHN''') is a redundant login node from which all jobs on all servers start. This server is not directly accessible from outside CSI campus.

o '''Chizen''' is a redundant gateway server which provides access to protected HPCC domain.

o '''Cea''' is a file transfer node allowing transfer of files between users’ computers to/from /scratch space or to/from /global/u/<usarid>. '''Cea''' is accessible directly (not only via '''Chizen'''), but allows only limited set of shell commands.

'''Table 1''' below provides a quick summary of the attributes of each of the systems available at the HPC Center.
{| class="wikitable"
|+
!System
!Type
!Type of Jobs
!Nodes
!Cores/node & GPU
!Mem/node
!Mem/core
!Multi-core Processor
|-
| rowspan="4" |Penzias
| rowspan="4" |Hybrid Cluster
|Sequential & Parallel jobs w/wo GPU
|66
|16
2xK20m GPU, PCIe
|64 GB
|4 GB
|Sand Bridge, EP 2.20 GHz
|-
| rowspan="3" |Sequential & Parallel jobs
| rowspan="3" |1
|24
|1500 GB
|62 GB
| rowspan="3" |Haswell, 2.30 GHz
|-
|36
|768 GB
|21 GB
|-
|24
|768 GB
|32 GB
|-
|Appel
|NUMA
|Massive Parallel, sequential
|1
|384
|11 TB
|28 GB
|Ivy Bridge, 3 GHz
|-
|Cryo
|SMP
|Sequential and Parallel jobs, with GPU
|1
|40 8xV100 (32GB) GPU, XSM
|1500 GB
|37 GB
|Skylake, 2.40 GHz
|-
| rowspan="2" |Blue Moon
| rowspan="2" |Hybrid Cluster
| rowspan="2" |Sequential and Parallel jobs w/wo GPU
|24
|32
| rowspan="2" |192 GB
| rowspan="2" |6 GB
| rowspan="2" |Skylake, 2.10 GHz
|-
|2
|32
2xV100(16GB) GPU, PCIe
|-
|Karle
|SMP
|Visualization, MATLAB/Mathematica
|1
|36*
|768 GB
|21 GB
|Haswell, 2.30 GHz
|-
|Chizen
|Gateway
|2
| colspan="5" rowspan="2" |NA
|-
|MHN
|Login Nodes
|2
|}

==Partitions and jobs==
The only way to submit job(s) to HPCC servers is through SLURM batch system. Any job despite of its type (interactive, batch, serial, parallel etc.) must be submitted via SLURM. The latter allocates the requested resources on proper server and starts the job(s) according to predefined strict fair share policy. Computational resources (cpu-cores, memory, GPU) are organized in partitions. The main partition is called production. This is routing partition which distributes the jobs in several sub-partitions depend on job’s requirements. Thus the serial job submitted in '''production''' will land in '''partsequential''' partition. No SLURM Pro scripts should be ever used and all existing SLURM scripts must be converted to SLURM before use. The table below shows the limitations of the partitions.
{| class="wikitable"
|+
!Partition
!Max cores/job
!Max jobs/user
!Total cores/group
!Time limits
|-
|production
|128
|50
|256
|240 Hours
|-
|partedu
|16
|2
|216
|72 Hours
|-
|partcryo
|40
|40
|40
|240 Hours
|-
|partmath
|128
|128
|128
|240 Hours
|-
|partmatlab
|1972
|50
|1972
|240 Hours
|-
|partdev
|16
|16
|16
|4 Hours
|}
o '''production''' is the main partition with assigned resources across all servers (except Math and Cryo).It is routing partition so the actual job(s) will be placed in proper sub-partition automatically. Users may submit sequential, thread parallel or distributed parallel jobs with or without GPU.

o '''partedu''' partition is only for education. Assigned resources are on educational server Herbert. Partedu is accessible only to students (graduate and/or undergraduate) and their professors who are registered for a class supported by HPCC. Access to this partition is limited by the duration of the class.

o '''partcryo''' is partition used to start jobs on CRYO server. Users whose projects require and/or benefit from availability of 8 GPU interconnected via SXM interface (not PCIe) must apply for access to this partition at hpchelp@csi.cuny.edu.

o '''partmatlab''' partition allows to run MATLAB's Distributes Parallel Server across main cluster. Note however that parallel toolbox programs can be submitted via production partition, but only as thread parallel jobs.

o '''partdev''' is dedicated to development. All HPCC users have access to this partition with assigned resources of one computational node with 16 cores, 64 GB of memory and 2 GPU (K20m). This partition has time limit of 4 hours.

== Hours of Operation ==
The second and fourth Tuesday mornings in the month from 8:00AM to 12PM are normally reserved (but not always used) for scheduled maintenance. Please plan accordingly. <br/ >
Unplanned maintenance to remedy system related problems may be scheduled as needed. Reasonable attempts will be made to inform users running on those systems when these needs arise.

== User Support ==
Users are encouraged to read this Wiki carefully. In particular, the sections on compiling and running
parallel programs, and the section on the SLURM batch queueing system will give you the essential
knowledge needed to use the CUNY HPC Center systems. We have strived to maintain the most uniform
user applications environment possible across the Center's systems to ease the transfer of applications
and run scripts among them. Still, there are some differences, particularly with the SGI (ANDY) and Cray (SALK)
systems.

The CUNY HPC Center staff, along with outside vendors, offer regular courses and workshops to the CUNY
community in parallel programming techniques, HPC computing architecture, and the essentials of using our
systems. Please follow our mailings on the subject and feel free to inquire about such courses. We regularly
schedule training visits and classes at the various CUNY campuses. Please let us know if such a training visit
is of interest. In the past, topics have include an overview of parallel programming, GPU programming and
architecture, using the evolutionary biology software at the HPC Center, the SLURM queueing system at the
CUNY HPC Center, Mixed GPU-MPI and OpenMP programming, etc. Staff has also presented guest lectures
at formal classes throughout the CUNY campuses.

Users with further questions or requiring immediate assistance in use of the systems should create a ticket using their HPC account login at:

[https://hpchelp.csi.cuny.edu hpchelp.csi.cuny.edu]

If you have problems accessing your account and cannot login to the ticketing service, please send an email to:

[mailto:hpchelp@csi.cuny.edu hpchelp@csi.cuny.edu]

== Warnings and modes of operation ==

1. hpchelp@csi.cuny.edu is for questions and accounts help communication '''only''' and does not accept tickets. For tickets please use the ticketing system mentioned above. This ensures that the person on staff with the most appropriate skill set and job related responsibility will respond to your questions. During the business week you should expect a 48h response, quite often even same day response. During the weekend you may not get any response.

2. '''E-mails to hpchelp@csi.cuny.edu must have a valid CUNY e-mail as reply address.''' Messages originated from public mailers (google, hotmail, etc) are filtered out.

3. '''Do not send questions to individual CUNY HPC Center staff members directly.''' These will be returned to the sender with a polite request to submit a ticket or email the Helpline. This applies to replies to initial questions as well.

The CUNY HPC Center staff members are focused on providing high quality support to its user community, but compared
to other HPC Centers of similar size '''our staff is extremely lean'''. Please make full use of the tools that we have provided (especially
the Wiki), and feel free to offer suggestions for improved service. We hope and expect your experience in using
our systems will be predictably good and productive.

== User Manual ==

An old version of the user manual can be downloaded at: http://cunyhpc.csi.cuny.edu/publications/User_Manual.pdf. Note that this manual provides SLURM batch scripts as examples. Currently CUNY-HPCC uses SLURM so users must check the brief SLURM manual distributed with new accounts or ask CUNY-HPCC for a copy of the latter.

2022-10-27T19:49:20Z

James: Text replacement - "[pP][bB][sS]" to "SLURM"

Currently, BEST is available on ANDY at the CUNY HPC Center.

To run BEST, first a NEXUS-formatted, DNA sequence comparison input file (e.g. a '.nex' file)
must be created using MrBayes. See the section on MrBayes below for this. Here is an
example NEXUS input file:

<pre>
#NEXUS

begin data;
dimensions ntax=17 nchar=432;
format datatype=dna missing=?;
matrix
human ctgactcctgaggagaagtctgccgttactgccctgtggggcaaggtgaacgtggatgaagttggtggtgaggccctgggcaggctgctggtggtctacccttggacccagaggttctttgagtcctttggggatctgtccactcctgatgctgttatgggcaaccctaaggtgaaggctcatggcaagaaagtgctcggtgcctttagtgatggcctggctcacctggacaacctcaagggcacctttgccacactgagtgagctgcactgtgacaagctgcacgtggatcctgagaacttcaggctcctgggcaacgtgctggtctgtgtgctggcccatcactttggcaaagaattcaccccaccagtgcaggctgcctatcagaaagtggtggctggtgtggctaatgccctggcccacaagtatcac
tarsier ctgactgctgaagagaaggccgccgtcactgccctgtggggcaaggtagacgtggaagatgttggtggtgaggccctgggcaggctgctggtcgtctacccatggacccagaggttctttgactcctttggggacctgtccactcctgccgctgttatgagcaatgctaaggtcaaggcccatggcaaaaaggtgctgaacgcctttagtgacggcatggctcatctggacaacctcaagggcacctttgctaagctgagtgagctgcactgtgacaaattgcacgtggatcctgagaatttcaggctcttgggcaatgtgctggtgtgtgtgctggcccaccactttggcaaagaattcaccccgcaggttcaggctgcctatcagaaggtggtggctggtgtggctactgccttggctcacaagtaccac
bushbaby ctgactcctgatgagaagaatgccgtttgtgccctgtggggcaaggtgaatgtggaagaagttggtggtgaggccctgggcaggctgctggttgtctacccatggacccagaggttctttgactcctttggggacctgtcctctccttctgctgttatgggcaaccctaaagtgaaggcccacggcaagaaggtgctgagtgcctttagcgagggcctgaatcacctggacaacctcaagggcacctttgctaagctgagtgagctgcattgtgacaagctgcacgtggaccctgagaacttcaggctcctgggcaacgtgctggtggttgtcctggctcaccactttggcaaggatttcaccccacaggtgcaggctgcctatcagaaggtggtggctggtgtggctactgccctggctcacaaataccac
hare ctgtccggtgaggagaagtctgcggtcactgccctgtggggcaaggtgaatgtggaagaagttggtggtgagaccctgggcaggctgctggttgtctacccatggacccagaggttcttcgagtcctttggggacctgtccactgcttctgctgttatgggcaaccctaaggtgaaggctcatggcaagaaggtgctggctgccttcagtgagggtctgagtcacctggacaacctcaaaggcaccttcgctaagctgagtgaactgcattgtgacaagctgcacgtggatcctgagaacttcaggctcctgggcaacgtgctggttattgtgctgtctcatcactttggcaaagaattcactcctcaggtgcaggctgcctatcagaaggtggtggctggtgtggccaatgccctggctcacaaataccac
rabbit ctgtccagtgaggagaagtctgcggtcactgccctgtggggcaaggtgaatgtggaagaagttggtggtgaggccctgggcaggctgctggttgtctacccatggacccagaggttcttcgagtcctttggggacctgtcctctgcaaatgctgttatgaacaatcctaaggtgaaggctcatggcaagaaggtgctggctgccttcagtgagggtctgagtcacctggacaacctcaaaggcacctttgctaagctgagtgaactgcactgtgacaagctgcacgtggatcctgagaacttcaggctcctgggcaacgtgctggttattgtgctgtctcatcattttggcaaagaattcactcctcaggtgcaggctgcctatcagaaggtggtggctggtgtggccaatgccctggctcacaaataccac
cow ctgactgctgaggagaaggctgccgtcaccgccttttggggcaaggtgaaagtggatgaagttggtggtgaggccctgggcaggctgctggttgtctacccctggactcagaggttctttgagtcctttggggacttgtccactgctgatgctgttatgaacaaccctaaggtgaaggcccatggcaagaaggtgctagattcctttagtaatggcatgaagcatctcgatgacctcaagggcacctttgctgcgctgagtgagctgcactgtgataagctgcatgtggatcctgagaacttcaagctcctgggcaacgtgctagtggttgtgctggctcgcaattttggcaaggaattcaccccggtgctgcaggctgactttcagaaggtggtggctggtgtggccaatgccctggcccacagatatcat
sheep ctgactgctgaggagaaggctgccgtcaccggcttctggggcaaggtgaaagtggatgaagttggtgctgaggccctgggcaggctgctggttgtctacccctggactcagaggttctttgagcactttggggacttgtccaatgctgatgctgttatgaacaaccctaaggtgaaggcccatggcaagaaggtgctagactcctttagtaacggcatgaagcatctcgatgacctcaagggcacctttgctcagctgagtgagctgcactgtgataagctgcacgtggatcctgagaacttcaggctcctgggcaacgtgctggtggttgtgctggctcgccaccatggcaatgaattcaccccggtgctgcaggctgactttcagaaggtggtggctggtgttgccaatgccctggcccacaaatatcac
pig ctgtctgctgaggagaaggaggccgtcctcggcctgtggggcaaagtgaatgtggacgaagttggtggtgaggccctgggcaggctgctggttgtctacccctggactcagaggttcttcgagtcctttggggacctgtccaatgccgatgccgtcatgggcaatcccaaggtgaaggcccacggcaagaaggtgctccagtccttcagtgacggcctgaaacatctcgacaacctcaagggcacctttgctaagctgagcgagctgcactgtgaccagctgcacgtggatcctgagaacttcaggctcctgggcaacgtgatagtggttgttctggctcgccgccttggccatgacttcaacccgaatgtgcaggctgcttttcagaaggtggtggctggtgttgctaatgccctggcccacaagtaccac
elephseal ttgacggcggaggagaagtctgccgtcacctccctgtggggcaaagtgaaggtggatgaagttggtggtgaagccctgggcaggctgctggttgtctacccctggactcagaggttctttgactcctttggggacctgtcctctcctaatgctattatgagcaaccccaaggtcaaggcccatggcaagaaggtgctgaattcctttagtgatggcctgaagaatctggacaacctcaagggcacctttgctaagctcagtgagctgcactgtgaccagctgcatgtggatcccgagaacttcaagctcctgggcaatgtgctggtgtgtgtgctggcccgccactttggcaaggaattcaccccacagatgcagggtgcctttcagaaggtggtagctggtgtggccaatgccctcgcccacaaatatcac
rat ctaactgatgctgagaaggctgctgttaatgccctgtggggaaaggtgaaccctgatgatgttggtggcgaggccctgggcaggctgctggttgtctacccttggacccagaggtactttgatagctttggggacctgtcctctgcctctgctatcatgggtaaccctaaggtgaaggcccatggcaagaaggtgataaacgccttcaatgatggcctgaaacacttggacaacctcaagggcacctttgctcatctgagtgaactccactgtgacaagctgcatgtggatcctgagaacttcaggctcctgggcaatatgattgtgattgtgttgggccaccacctgggcaaggaattcaccccctgtgcacaggctgccttccagaaggtggtggctggagtggccagtgccctggctcacaagtaccac
mouse ctgactgatgctgagaagtctgctgtctcttgcctgtgggcaaaggtgaaccccgatgaagttggtggtgaggccctgggcaggctgctggttgtctacccttggacccagcggtactttgatagctttggagacctatcctctgcctctgctatcatgggtaatcccaaggtgaaggcccatggcaaaaaggtgataactgcctttaacgagggcctgaaaaacctggacaacctcaagggcacctttgccagcctcagtgagctccactgtgacaagctgcatgtggatcctgagaacttcaggctcctaggcaatgcgatcgtgattgtgctgggccaccacctgggcaaggatttcacccctgctgcacaggctgccttccagaaggtggtggctggagtggccactgccctggctcacaagtaccac
hamster ctgactgatgctgagaaggcccttgtcactggcctgtggggaaaggtgaacgccgatgcagttggcgctgaggccctgggcaggttgctggttgtctacccttggacccagaggttctttgaacactttggagacctgtctctgccagttgctgtcatgaataacccccaggtgaaggcccatggcaagaaggtgatccactccttcgctgatggcctgaaacacctggacaacctgaagggcgccttttccagcctgagtgagctccactgtgacaagctgcacgtggatcctgagaacttcaagctcctgggcaatatgatcatcattgtgctgatccacgacctgggcaaggacttcactcccagtgcacagtctgcctttcataaggtggtggctggtgtggccaatgccctggctcacaagtaccac
marsupial ttgacttctgaggagaagaactgcatcactaccatctggtctaaggtgcaggttgaccagactggtggtgaggcccttggcaggatgctcgttgtctacccctggaccaccaggttttttgggagctttggtgatctgtcctctcctggcgctgtcatgtcaaattctaaggttcaagcccatggtgctaaggtgttgacctccttcggtgaagcagtcaagcatttggacaacctgaagggtacttatgccaagttgagtgagctccactgtgacaagctgcatgtggaccctgagaacttcaagatgctggggaatatcattgtgatctgcctggctgagcactttggcaaggattttactcctgaatgtcaggttgcttggcagaagctcgtggctggagttgcccatgccctggcccacaagtaccac
duck tggacagccgaggagaagcagctcatcaccggcctctggggcaaggtcaatgtggccgactgtggagctgaggccctggccaggctgctgatcgtctacccctggacccagaggttcttcgcctccttcgggaacctgtccagccccactgccatccttggcaaccccatggtccgtgcccatggcaagaaagtgctcacctccttcggagatgctgtgaagaacctggacaacatcaagaacaccttcgcccagctgtccgagctgcactgcgacaagctgcacgtggaccctgagaacttcaggctcctgggtgacatcctcatcatcgtcctggccgcccacttcaccaaggatttcactcctgactgccaggccgcctggcagaagctggtccgcgtggtggcccacgctctggcccgcaagtaccac
chicken tggactgctgaggagaagcagctcatcaccggcctctggggcaaggtcaatgtggccgaatgtggggccgaagccctggccaggctgctgatcgtctacccctggacccagaggttctttgcgtcctttgggaacctctccagccccactgccatccttggcaaccccatggtccgcgcccacggcaagaaagtgctcacctcctttggggatgctgtgaagaacctggacaacatcaagaacaccttctcccaactgtccgaactgcattgtgacaagctgcatgtggaccccgagaacttcaggctcctgggtgacatcctcatcattgtcctggccgcccacttcagcaaggacttcactcctgaatgccaggctgcctggcagaagctggtccgcgtggtggcccatgccctggctcgcaagtaccac
xenlaev tggacagctgaagagaaggccgccatcacttctgtatggcagaaggtcaatgtagaacatgatggccatgatgccctgggcaggctgctgattgtgtacccctggacccagagatacttcagtaactttggaaacctctccaattcagctgctgttgctggaaatgccaaggttcaagcccatggcaagaaggttctttcagctgttggcaatgccattagccatattgacagtgtgaagtcctctctccaacaactcagtaagatccatgccactgaactgtttgtggaccctgagaactttaagcgttttggtggagttctggtcattgtcttgggtgccaaactgggaactgccttcactcctaaagttcaggctgcttgggagaaattcattgcagttttggttgatggtcttagccagggctataac
xentrop tggacagctgaagaaaaagcaaccattgcttctgtgtgggggaaagtcgacattgaacaggatggccatgatgcattatccaggctgctggttgtttatccctggactcagaggtacttcagcagttttggaaacctctccaatgtctccgctgtctctggaaatgtcaaggttaaagcccatggaaataaagtcctgtcagctgttggcagtgcaatccagcatctggatgatgtgaagagccaccttaaaggtcttagcaagagccatgctgaggatcttcatgtggatcccgaaaacttcaagcgccttgcggatgttctggtgatcgttctggctgccaaacttggatctgccttcactccccaagtccaagctgtctgggagaagctcaatgcaactctggtggctgctcttagccatggctacttc
;
end;

begin mrbayes;
charset non_coding = 1-90 358-432;
charset coding = 91-357;
partition region = 2:non_coding,coding;
set partition = region;
lset applyto=(2) nucmodel=codon;
prset ratepr=variable;
mcmc ngen=5000 nchains=1 samplefreq=10;
end;
</pre>

Next, a SLURM batch script must be created to run your job. The first script below shows a MPI parallel script
for the above '.nex' input file. Note that the number of processors that can be used by the job is limited to
the number of chains in the input file. Here, we have just 2 chains and therefore can only request 2 processors.
If you make the mistake of asking for more processors than input file chains, you will get the following error
message:

<pre>
The number of chains must be at least as great
as the number of processors (in this case 4)
</pre>

Also, to include all required environmental variables and the path to the BEST executable run the modules load
command (the modules utility is discussed in detail above):

<pre>
module load best
</pre>

Here is the MPI parallel SLURM batch script for BEST that request 2 processors, one for each chain in the input file:

<pre>
#!/bin/bash
#SBATCH --partition production
#SBATCH --job-name BEST_parallel
#SBATCH --nodes=2
#SBATCH --ntasks=1
#SBATCH --mem=2880

# Find out name of master execution host (compute node)
echo -n ">>>> SLURM Master compute node is: "
hostname

# You must explicitly change to the working directory in SLURM
cd $SLURM_SUBMIT_DIR

# Use 'mpirun' and point to the MPI parallel executable to run
echo ">>>> Begin BEST Parallel Run ..."
mpirun -np mbbest ./bglobin.nex > best_mpi.out 2>&1
echo ">>>> End BEST Parallel Run ..."
</pre>

This script can be dropped into a file (say 'best_mpi.job) on ANDY and run with:

<pre>
qsub best_mpi.job
</pre>

It should take less five minutes to run and will produce SLURM output and error files beginning
with the job name 'BEST_parallel'. The primary BEAST application results will be written into
the user-specified file at the end of the BEST command line after the greater-than sign. Here
it is named 'best_mpi.out'. The expression '2>&1' combines Unix standard output from the
program with Unix standard error. Users should always explicitly specify the name of the
application's output file in this way to ensure that it is written directly into the user's working
directory which has much more disk space than the SLURM spool directory on /var.

Details on the meaning of the SLURM script are covered below in the SLURM section. The most important
lines are the '#SBATCH --nodes ntasks=1 mem=2880'. The
first instructs SLURM to select 2 resource 'chunks' each with 1 processor (core) and 2,880 MBs of
memory in it for the job. The second instructs SLURM to place this job wherever the least used
resources are found (freely). The master compute node that it finally selects to run your job
will be printed in the SLURM output file by the 'hostname' command.

The CUNY HPC Center also provides a serial version of BEST. A SLURM batch script for running the
serial version of BEST follows:

<pre>
#!/bin/bash
#SBATCH --partition production
#SBATCH --job-name BEST_serial
#SBATCH --nodes=1
#SBATCH --ntasks=1
#SBATCH --mem=2880

# Find out name of master execution host (compute node)
echo -n ">>>> SLURM Master compute node is: "
hostname

# You must explicitly change to the working directory in SLURM
cd $SLURM_SUBMIT_DIR

# Just point to the serial executable to run
echo ">>>> Begin BEST Serial Run ..."
mbbest_serial ./bglobin.nex > best_ser.out 2>&1
echo ">>>> End BEST Serial Run ..."
</pre>

Applications Index

2022-10-27T19:49:18Z

James: Text replacement - "[pP][bB][sS]" to "SLURM"

<div class="noautonum">__TOC__</div>
'''The purpose of this page is to provide an all-inclusive, alphabetical list of available applications, tools, and libraries.'''

For information about using modules to run your applications go to [[Using Modules To Run Your Applications]]. For a list of applications sorted by academic relevance go to [http://wiki.csi.cuny.edu/cunyhpc/index.php?title=Applications_Index/Academic_relevance Academic Relevance].

<div class="mw-collapsible mw-collapsed">
== A ==
<div class="mw-collapsible-content">

'''<p style="font-size:17px;" >ADCIRC</p>'''
<div class="toccolours mw-collapsible mw-collapsed">
ADCIRC is a system of programs for solving time-dependent, free-surface, circulation and transport problems in two and three dimensions.
<div class="mw-collapsible-content"> These programs utilize the finite element method in space allowing the use of highly flexible, unstructured grids. The ADCIRC distribution includes and integrates the METIS tool for unstructured grid generation. In addition, ADCIRC includes a distribution of SWAN to which it can be coupled to add a shore wave simulation model. Typical ADCIRC applications have included: (i) modeling tides and wind driven circulation, (ii) analysis of hurricane storm surge and flooding, (iii) dredging feasibility and material disposal studies, (iv) larval transport studies, (v) near shore marine operations. For more detail on using ADCIRC, please visit the ADCIRC website here [http://adcirc.org/index.html] and read the ADCIRC manual [http://adcirc.org/documentv49/ADCIRC_title_page.html]. Details on using SWAN with ADCIRC can be found here [http://www.caseydietrich.com/swanadcirc] and at the SWAN web site [http://swanmodel.sourceforge.net]. More information about use and set-up can be found here [[ADCIRC]].
</div>
</div>

'''<p style="font-size:17px;" >AMBER (Assisted Model Building with Energy Refinement)</p>'''
Amber is the collective name for a suite of programs for classical bio-molecular simulations.
The name "Amber" also denotes the family of potentials (force fields) used with Amber
software. Here we discuss only simulation packages, but not the force fields or free tools
available via AmberTools package. Details and submission scripts can be found at: http://wiki.csi.cuny.edu/cunyhpc/index.php/Applications_Environment/amber

'''<p style="font-size:17px;" >ANVIO</p>'''
Anvio is a tool for an analysis and visualization platform for genomics data. Anvio allows various types of workflows to be
established. [[ANVIO]]

'''<p style="font-size:17px;" >AUGUSTUS</p>'''
AUGUSTUS is a program that predicts genes in eukaryotic genomic sequences. Augustus is a gene-finding software based on Hidden Markov Models (HMMs),
described in papers by Stanke and Waack (2003) and Stanke et al (2006) and Stanke et al (2006b) and Stanke et al (2008).The local version of the program is installed on
Penzias. More information can be found here: [[AUGUSTUS]]

'''<p style="font-size:17px;" >AUTODOCK</p>'''
<div class="toccolours mw-collapsible mw-collapsed">
AutoDock is a suite of automated docking tools.
<div class="mw-collapsible-content"> It is designed to predict how small molecules, such as substrates or drug candidates, bind to a receptor of known 3D structure. AutoDock actually consists of two main programs: ''autodock'' itself performs the docking of the ligand to a set of grids describing the target protein; ''autogrid'' pre-calculates these grids. More information about the software may be found at the autodock web-page [http://autodock.scripps.edu/]. Details and submission scripts can be found at: http://wiki.csi.cuny.edu/cunyhpc/index.php/Applications_Environment/autodock
</div>
</div>
</div>
</div>

<div class="mw-collapsible mw-collapsed">

== B ==
<div class="mw-collapsible-content">

'''<p style="font-size:17px;" >BAMOVA</p>'''
Bamova is a package used to do genetic analysis of a wide range of organisms on the basis of
next-generation sequence data. The software implements Bayesian Analysis of Molecular Variance and
different likelihood models for three different types of molecular data
(including two models for high throughput sequence data). For more detail on BAMOVA please visit the BAMOVA web site [http://www.uwyo.edu/buerkle/software/bamova] and manual
here [http://www.uwyo.edu/buerkle/software/bamova/bamova_manual_1.0.pdf]. Further information can also be found here [[BAMOVA]].

'''<p style="font-size:17px;" >BAYESCAN</p>'''
<div class="toccolours mw-collapsible mw-collapsed">
BAYESCAN is Population Genomics Software package. It identifies outlier loci and is applicable
to both, dominant and codominant data.
<div class="mw-collapsible-content">This program, BayeScan aims at identifying candidate loci under natural selection from genetic data, using differences in allele frequencies between populations. BayeScan is based on the multinomial-Dirichlet model. One of the scenarios covered consists of an island model in which subpopulation allele frequencies are correlated through a common migrant gene pool from which they differ in varying degrees. The difference in allele frequency between this common gene pool and each subpopulation is measured by a subpopulation-
specific FST coefficient. Therefore, this formulation can consider realistic ecological scenarios where the effective size and the immigration rate may differ among subpopulations.
More detailed information on Bayescan can be found at the web site here [http://cmpg.unibe.ch/software/bayescan/index.html] and in the manual here [http://cmpg.unibe.ch/software/bayescan/files/BayeScan2.1_manual.pdf]. More information about our installation can be found here [[BAYESCAN]].
</div>
</div>

'''<p style="font-size:17px;" >BEAST</p>'''
<div class="toccolours mw-collapsible mw-collapsed">
BEAST is a powerful and flexible evolutionary analysis package for molecular sequence variation.
<div class="mw-collapsible-content">
The package implements a family of Markov chain Monte Carlo (MCMC) algorithms for Bayesian phylogenetic inference, divergence time dating, coalescent analysis, phylogeography and related molecular evolutionary analyses. It is a cross-platform Java program for Bayesian MCMC analysis of molecular sequences. It is entirely orientated towards rooted, time-measured phylogenies inferred using strict or relaxed molecular clock models. It can be used as a method of reconstructing phylogenies, but is also a framework for testing evolutionary hypotheses without conditioning on a single tree topology. BEAST uses MCMC to average over tree space, so that each tree is weighted proportional to its posterior probability. The distribution includes a simple to use user-interface program called 'BEAUti' for setting up standard analyses and a suite of programs for analysing the results. For more detail on BEAST (and BEAUTi) please visit the BEAST web site [http://beast.bio.ed.ac.uk/Main_Page]. More information about our installation can be found here [http://wiki.csi.cuny.edu/cunyhpc/index.php/Template:BEAST BEAST].
</div>
</div>

'''<p style="font-size:17px;" >BEST</p>'''
<div class="toccolours mw-collapsible mw-collapsed">
BEST is an application aimed to estimate gene trees and the species tree from multilocus sequences.
<div class="mw-collapsible-content">
The program uses information from multiple gene trees and performs a Bayesian analysis to estimate the
topology of the species tree, divergence times and population sizes.

It provides a new approach for estimating the mutation-rate-
based, phylogenetic relationships among species. Its method accounts for deep coalescence,
but not for other complicating issues such as horizontal transfer or gene duplication. The
program works in conjunction within the popular Bayesian phylogenetics package, MrBayes
(Ronquist and Huelsenbeck, Bioinformatics, 2003). BEST's parameters are defined using
the 'prset' command from MrBayes. Details on BEST's capabilities and options are avialable
at the BEST web site here [http://www.stat.osu.edu/~dkp/BEST/introduction]. More information
about our installation is available here [[BEST]].
</div>
</div>

'''<p style="font-size:17px;" >BOWTIE2</p>'''
<div class="toccolours mw-collapsible mw-collapsed">
BOWTIE2 is an ultrafast and memory-efficient tool for aligning sequencing reads to long reference sequences. It is particularly good at aligning reads of about 50 up to 100s or 1,000s of characters, and particularly good at aligning to relatively long (e.g. mammalian) genomes.
<div class="mw-collapsible-content">
BOWTIE2 indexes the genome with an FM Index to keep its memory
footprint small: for the human genome, its memory footprint is typically around 3.2 GB. BOWTIE2 supports gapped,
local, and paired-end alignment modes. BOWTIE2 is part of a sequence alignment and analysis tool chain developed
at John Hopkins, University of California at Berkeley, and Harvard, and distributed through the Center for Bioinformatics
and Computational Biology. The other tools in this collection, CUFFLINKS, SAMTOOLS, and TOPHAT are also installed at
the CUNY HPC Center. Additional information can be found at the BOWTIE2 home page here [http://bowtie-bio.sourceforge.net/bowtie2/index.shtml].
Information about our installation can be found here [[BOWTIE2]].
</div>
</div>

'''<p style="font-size:17px;" >BPP2</p>'''
<div class="toccolours mw-collapsible mw-collapsed">
BPP2 uses a Bayesian modeling approach to generate the posterior probabilities of species assignments taking into account uncertainties due to unknown gene trees and the ancestral coalescent process. For tractability, it relies on a user-specified guide tree to avoid integrating over all possible species delimitations.
<div class="mw-collapsible-content">
Additional information can be found at the download site here [http://abacus.gene.ucl.ac.uk/software.html]. More information about our installation can be found here [[BPP2]].</div>
</div>

'''<p style="font-size:17px;" >BROWNIE</p>'''
BROWNIE is a program for analyzing rates of continuous character evolution and looking for substantial rate differences in different parts of a tree using likelihood
ratio tests and Akaike Information Criterion (AIC) statistics. It now also implements many other methods for examining trait evolution and methods for doing species
delimitation. More information about our installation can be found here [[BROWNIE]].

</div>
</div>

<div class="mw-collapsible mw-collapsed">

== C ==
<div class="mw-collapsible-content">

'''<p style="font-size:17px;" >CGAL</p>'''
<div class="toccolours mw-collapsible mw-collapsed">
The Computational Geometry Algorithms Library (CGAL), offers data structures and algorithms.
<div class="mw-collapsible-content">
Examples of these are triangulations (2D constrained triangulations, and Delaunay triangulations and periodic triangulations in
2D and 3D), Voronoi diagrams (for 2D and 3D points, 2D additively weighted Voronoi diagrams, and segment Voronoi diagrams), polygons
(Boolean operations, offsets, straight skeleton), polyhedra (Boolean operations), arrangements of curves and their applications
(2D and 3D envelopes, Minkowski sums), mesh generation (2D Delaunay mesh generation and 3D surface and volume mesh
generation, skin surfaces), geometry processing (surface mesh simplification, subdivision and parameterization, as well as
estimation of local differential properties, and approximation of ridges and umbilics), alpha shapes, convex hull
algorithms (in 2D, 3D and dD), search structures (kd trees for nearest neighbor search, and range and segment trees),
interpolation (natural neighbor interpolation and placement of streamlines), shape analysis, fitting, and distances
(smallest enclosing sphere of points or spheres, smallest enclosing ellipsoid of points, principal component analysis), and
kinetic data structures.

The library is installed on PENZIAS.

More information can be found here http://wiki.csi.cuny.edu/cunyhpc/index.php/Applications_Environment/CGAL.
</div>
</div>

'''<p style="font-size:17px;" >CONSED</p>'''
<div class="toccolours mw-collapsible mw-collapsed">
CONSED is a DNA sequence analysis finishing tool that provides sequence viewing, editing, alignment, and
assembly capabilities from a X Windows graphical user interface (GUI).
<div class="mw-collapsible-content">
It makes extensive use of other non-graphical
and underlying sequence analysis tools including PHRED, PHRAP, and CROSSMATCH that may also be used separately
and are described else where in this document. It also includes a viewer called BAMVIEW. The CONSED tool chain is
developed and maintained at the University of Washington and is described
more completely here [http://bozeman.mbt.washington.edu/consed/consed.html]
CONSED is provided at the CUNY HPC Center under an academic license that allows use, but not the copying or out
bound transfer of any of the executables or files distributed under this academic license. The license is not
transferable in any way and users wishing to run the application at their own site must acquire a license directly
from the authors.

The CUNY HPC Center supports CONSED version 23.0 for interactive use on KARLE. CONSED 23.0 and the tool
chain described above is also installed on ANDY to allow for the batch use of underlying support tools mention above
and described in detail below. In general, running GUI-based applications on ANDY's login node is discouraged. There
should be little need to do this as KARLE is on the periphery of the CUNY HPC network making login there direct and
KARLE shares its HOME directory file system with ANDY making files created on either system immediately available on
the other.

Rather than rewrite portions of the CONSEND manual here, users are directed to the manual's "Quick Tour" section
here [http://bozeman.mbt.washington.edu/consed/distributions/README.23.0.txt] and asked to walk through some
of the exercises after logging into KARLE. If problems or questions come up, please post them to "hpchelp@csi.cuny.edu".
The CONSED 23.0 distribution is installed on KARLE in the following directory:

<pre>
/share/apps/consed/default
</pre>

All the files in the distribution can be found there.

</div>
</div>

'''<p style="font-size:17px;" >CP2K</p>'''
<div class="toccolours mw-collapsible mw-collapsed">
CP2K is a program to perform atomistic and molecular simulations of solid state, liquid, molecular, and biological
systems.
<div class="mw-collapsible-content">
It provides a general framework for different methods such as e.g., density functional theory (DFT) using
a mixed Gaussian and plane waves approach (GPW) and classical pair and many-body potentials. CP2K provides
state-of-the-art methods for efficient and accurate atomistic simulations. More information about our installation
can be found here [[CP2K]].
</div>
</div>

'''<p style="font-size:17px;" >CUFFLINKS</p>'''
<div class="toccolours mw-collapsible mw-collapsed">
CUFFLINKS assembles transcripts, estimates their abundances, and tests for differential expression and regulation in
RNA-Seq samples.
<div class="mw-collapsible-content">
It accepts aligned RNA-Seq reads and assembles the alignments into a parsimonious set of transcripts.
CUFFLINKS then estimates the relative abundances of these transcripts based on how many reads support each one, taking
into account biases in library preparation protocols. CUFFLINKS is part of a sequence alignment and analysis tool chain developed
at John Hopkins, University of California at Berkeley, and Harvard, and distributed through the Center for Bioinformatics
and Computational Biology. The other tools in this collection, BOWTIE, SAMTOOLS, and TOPHAT are also installed at
the CUNY HPC Center.Additional information can be found at the CUFFLINKS home page here [http://abacus.gene.ucl.ac.uk/software.html].
More information about our installation can be found here [[CUFFLINKS]].
</div>
</div>
</div>
</div>

<div class="mw-collapsible mw-collapsed">
== D ==
<div class="mw-collapsible-content">

'''<p style="font-size:17px;" >DL_POLY</p>'''
<div class="toccolours mw-collapsible mw-collapsed">
DL_POLY is a general purpose molecular dynamics simulation package developed at Daresbury Laboratory by W. Smith, T.R. Forester and I.T. Todorov.
<div class="mw-collapsible-content">
Both serial and parallel versions are available. The original package was developed by the Molecular Simulation Group (now part of the Computational Chemistry Group, MSG) at Daresbury Laboratory under the auspices of the Engineering and Physical Sciences Research Council (EPSRC) for the EPSRC's Collaborative Computational Project for the Computer Simulation of Condensed Phases ( CCP5). Later developments were also supported by the Natural Environment Research Council through the eMinerals project. The package is the property of the Central Laboratory of the Research Councils, UK. More information about our installation and use can be found here [[DL_POLY]].
</div>
</div>
</div>
</div>

<div class="mw-collapsible mw-collapsed">
== E ==
<div class="mw-collapsible-content">

'''<p style="font-size:17px;" >ExaML</p>'''
<div class="toccolours mw-collapsible mw-collapsed">
ExaML stands for Exascale Maximum Likelihood (ExaML) code for phylogenetic inference using MPI.
<div class="mw-collapsible-content">
The code is installed only on Penzias and implements the popular RAxML search algorithm for maximum likelihood based inference of phylogenetic trees.

It uses a radically new MPI parallelization approach that yields improved paralll efficiency, in particular on partitioned multi-gene or whole-genome datasets.

When using ExaML please cite the following paper:

Alexey M. Kozlov, Andre J. Aberer, Alexandros Stamatakis: "ExaML Version 3: A Tool for Phylogenomic Analyses on Supercomputers." Bioinformatics (2015) 31 (15): 2577-2579.

It is up to 4 times faster than RAxML-Light [1].

As RAxML-Light, ExaML also implements checkpointing, SSE3, AVX vectorization and memory saving techniques.

[1] A. Stamatakis, A.J. Aberer, C. Goll, S.A. Smith, S.A. Berger, F. Izquierdo-Carrasco: "RAxML-Light: A Tool for computing TeraByte Phylogenies", Bioinformatics 2012; doi: 10.1093/bioinformatics/bts309.

The run script for parallel job is analogous to one for running RAxML on Penzias and Andy.
</div>
</div>

'''<p style="font-size:17px;" >ExaBayes</p>'''
<div class="toccolours mw-collapsible mw-collapsed">
ExaBayes is a software package for Bayesian tree inference. It is particularly suitable for large-scale analyses on computer clusters. It is installed on Penzias server at HPCC center.
The installed package is MPI parallel version.
<div class="mw-collapsible-content">
''Availability:''' PENZIAS
'''Module file:'''exabayes

'''Citation''':

Fredrik Ronquist, Maxim Teslenko, Paul van der Mark, Daniel L Ayres, Aaron Darling, Sebastian Höhna, Bret Larget, Liang Liu, Marc a Suchard, and John P Huelsenbeck. MrBayes 3.2: efficient Bayesian phylogenetic inference and model choice across a large model space. Systematic biology, 61(3):539--42, May 2012.

Alexei J Drummond, Marc a Suchard, Dong Xie, and Andrew Rambaut. Bayesian phylogenetics with BEAUti and the BEAST 1.7. Molecular biology and evolution, 29(8):1969--73, August 2012.

Clemens Lakner, Paul van der Mark, John P Huelsenbeck, Bret Larget, and Fredrik Ronquist. Efficiency of Markov chain Monte Carlo tree proposals in Bayesian phylogenetics. Systematic biology, 57(1):86--103, February 2008.

'''Use:''' The example SLURM script to run the FDPPDIV on PENZIAS is given below

<pre>
#!/bin/bash
#SLURM -q production
#SLURM -N <name_of_job>
#SLURM -l select=1:ncpus=2
#SLURM -l place=free
#SLURM -V

# You must explicitly change to the working directory in SLURM
cd $SLURM_O_WORKDIR

mpirun -np 2 exabayes <input_file> > output_file
</pre>

More information about application along with sample workflows are available on ExaBayes web site:

<pre>
http://sco.h-its.org/exelixis/web/software/exabayes/manual/index.html#sec-11
</pre>

</div>
</div>
</div>
</div>

<div class="mw-collapsible mw-collapsed">
== F ==
<div class="mw-collapsible-content">

'''<p style="font-size:17px;" >FDPPDIV</p>'''
<div class="toccolours mw-collapsible mw-collapsed">
FDPPDiv is a program for estimating divergence times on a fixed, rooted tree topology.
<div class="mw-collapsible-content">
FDPPDiv offers two alternative approaches to divergence time estimation.
The DPPDiv part refers to the Dirichlet Process Prior (DPP) model for divergence
time estimation, and the F prefix (for Fossil) refers to the new Fossil Birth-Death approach.
More information about our installation can be found here [[FDPPDIV]].
</div>
</div>
</div>
</div>

<div class="mw-collapsible mw-collapsed">
== G ==
<div class="mw-collapsible-content">

'''<p style="font-size:17px;" >GAMESS-US</p>'''
<div class="toccolours mw-collapsible mw-collapsed">
GAMESS is a program for ab initio molecular quantum chemistry.
<div class="mw-collapsible-content">
Briefly, GAMESS can compute SCF wavefunctions ranging from RHF, ROHF, UHF, GVB, and MCSCF. Correlation corrections to these SCF wavefunctions include Configuration Interaction, second order perturbation Theory, and Coupled-Cluster approaches, as well as the Density Functional Theory approximation. Excited states can be computed by CI, EOM, or TD-DFT procedures. Nuclear gradients are available, for automatic geometry optimization, transition state searches, or reaction path following. Computation of the energy hessian permits prediction of vibrational frequencies, with IR or Raman intensities. Solvent effects may be modeled by the discrete Effective Fragment potentials, or continuum models such as the Polarizable Continuum Model. Numerous relativistic computations are available, including infinite order two component scalar corrections, with various spin-orbit coupling options. The Fragment Molecular Orbital method permits use of many of these sophisticated treatments to be used on very large systems, by dividing the computation into small fragments. Nuclear wavefunctions can also be computed, in VSCF, or with explicit treatment of nuclear orbitals by the NEO code. More information, including code, can be found here [[GAMESS-US]].

</div>
</div>

'''<p style="font-size:17px;" >GARLI</p>'''
<div class="toccolours mw-collapsible mw-collapsed">
GARLI is a program that performs phylogenetic inference using the maximum-likelihood criterion.
<div class="mw-collapsible-content">
Several sequence types are supported, including nucleotide, amino acid and codon. Version 2.0 adds support for
partitioned models and morphology-like data types. It is usable on all operating systems, and is written and
maintained by Derrick Zwickl at the University of Texas at Austin. Additional information can be found
on the GARLI Wiki here [https://www.nescent.org/wg_garli/Main_Page]. More information about our installation
can be found here [[GARLI]].
</div>
</div>

'''<p style="font-size:17px;" >GAUSS</p>'''
<div class="toccolours mw-collapsible mw-collapsed">
An easy-to-use data analysis, mathematical and statistical environment based on the powerful, fast and efficient GAUSS Matrix Programming Language.
<div class="mw-collapsible-content">
GAUSS is used to solve real world problems and data analysis problems of exceptionally large
scale. GAUSS is currently available on ANDY. At the CUNY HPC Center
GAUSS is typically run in serial mode. (Note: GAUSS should not be confused with the
computational chemistry application Gaussian.) More information about our installation can
be found here [[GAUSS]].
</div>
</div>

'''<p style="font-size:17px;" >Gaussian09</p>'''
<div class="toccolours mw-collapsible mw-collapsed">
Gaussian09 is third-party, commercially licensed software from Gaussian, Inc. It is a set of programs for calculating electronic structure.
<div class="mw-collapsible-content">
Gaussian09 is available for general use only on ANDY. The Gaussian User Guide can be found here at [[http://www.gaussian.com]]. More information about our installation can be found here [[GAUSSIAN09]].
</div>
</div>

'''<p style="font-size:17px;" >GMP</p>'''
GMP is a library for arbitrary precision arithmetic, operating on signed integers, rational numbers, and
floating-point numbers. There is no practical limit to the precision except the ones implied by the
available memory in the machine GMP runs on. GMP has a rich set of functions, and the functions have a
regular interface. The library is installed on PENZIAS.

'''<p style="font-size:17px;" >Gnuplot</p>'''
<div class="toccolours mw-collapsible mw-collapsed">
Gnuplot is a portable command-line driven graphing utility. It is installed on the following systems:
<div class="mw-collapsible-content">
:* Karle under /usr/bin/gnuplot
:* Andy under /share/apps/gnuplot/default/bin/gnuplot

Extensive documentation of gnuplot is available at the [http://www.gnuplot.info/ gnuplot's homepage].
</div>
</div>

'''<p style="font-size:17px;" >GenomePop2</p>'''
<div class="toccolours mw-collapsible mw-collapsed">
GenomePop2 is a newer and specialized version of the older program GenomePop.
<div class="mw-collapsible-content">
GenomePop2 is designed to manage SNPs under more flexible and useful settings that are controlled by the user.
If you need models with more than 2 alleles you should use the older GenomePop version of the program.

GenomePop2 allows the forward simulation of sequences of biallelic positions. As in the previous version, a number of evolutionary
and demographic settings are allowed. Several populations under any migration model can be implemented. Each population consists
of a number N of individuals. Each individual is represented by one (haploids) or two (diploids) chromosomes with constant or variable
(hotspots) recombination between binary sites. The fitness model is multiplicative with each derived allele having a multiplicate effect
of (1-s * h-E) onto the global fitness value. By default E=0 and h=0.5 in diploids, but 1 in homozygotes or in haploids. Selective nucleotide
sites undergoing directional selection (positive or negative) in different populations can be defined. In addition, bottlenecks and/or
population expansion scenarios can be settled by the user during a desired number of generations. Several runs can be executed and
a sample of user-defined size is obtained for each run and population. For more detail on how to use GenomePop2, please visit the
web site here [http://webs.uvigo.es/acraaj/GenomePop2.htm]. More information about our installation can be found here [[GENOMEPOP2]].
</div>
</div>

'''<p style="font-size:17px;" >GROMACS</p>'''
<div class="toccolours mw-collapsible mw-collapsed">
GROMACS (Groningen Machine for Chemical Simulations)
<div class="mw-collapsible-content">
GROMACS is a full-featured suite of free software, licensed under the GNU
General Public License to perform molecular dynamics simulations -- in other words, to simulate the behavior of molecular
systems with hundreds to millions of particles using Newton's equations of motion. It is primarily used for research on
proteins, lipids, and polymers, but can be applied to a wide variety of chemical and biological research questions.

Details and submission scripts for production runs can be found at:
http://wiki.csi.cuny.edu/cunyhpc/index.php/Applications_Environment/gromacs
Please note that preparing molecular system for simulation via GROMACS tools, cannot be done on login node. Instead the users must either use their own workstation or use interactive or development queues.

</div>
</div>

'''<p style="font-size:17px;" >GPAW</p>'''
<div class="toccolours mw-collapsible mw-collapsed">
GPAW is a density-functional theory (DFT) Python code based on the projector-augmented wave (PAW) method and the atomic simulation environment (ASE).
<div class="mw-collapsible-content">
It uses real-space uniform grids and multigrid methods, atom-centered basis-functions or
plane-waves. GPAW calculations are controlled through scripts written in the programming language
Python. GPAW relies on the Atomic Simulation Environment (ASE), which is a Python package
that helps to describe atoms. The ASE package also handles molecular dynamics, analysis,
visualization, geometry optimization and more. More information about our installation can
be found here [[GPAW]].
</div>
</div>
</div>
</div>

<div class="mw-collapsible mw-collapsed">

== H ==
<div class="mw-collapsible-content">

'''<p style="font-size:17px;" >Hapsembler</p>'''
<div class="toccolours mw-collapsible mw-collapsed">
Hapsembler is a haplotype-specific genome assembly toolkit that is designed for genomes that are rich in SNPs and other types of polymorphism. Hapsembler can be used to assemble reads from a variety of platforms including Illumina and Roche/454.
<div class="mw-collapsible-content"> Hapsembler is currently installed on Appel system. In order to access velvet binaries load the velvet module with
<pre>
module load hapsembler
</pre>
</div>
</div>

'''<p style="font-size:17px;" >HOOMD</p>'''
<div class="toccolours mw-collapsible mw-collapsed">
Performs general purpose particle dynamics simulations, taking advantage of NVIDIA GPUs to attain a level of performance
equivalent to many processor cores on a fast cluster.
<div class="mw-collapsible-content">
Unlike some other applications in the particle and molecular dynamics space, HOOMD developers have worked to implement
all of the code's computationally intensive kernels on the GPU, although currently only single node, single-GPU or
OpenMP-GPU runs are possible. There is no MPI-GPU or distributed parallel GPU version available at this time.

HOOMD's object-oriented design patterns make it both versatile and expandable. Various types of potentials, integration methods
and file formats are currently supported, and more are added with each release. The code is available and open source, so anyone
can write a plugin or change the source to add additional functionality. Simulations are configured and run using simple python
scripts, allowing complete control over the force field choice, integrator, all parameters, how many time steps are run, etc.
The scripting system is designed to be as simple as possible to the non-programmer.

The HOOMD development effort is led by the Glotzer group at the University of Michigan, but many groups from different universities
have contributed code that is now part of the HOOMD main package, see the credits page for the full list. The HOOMD website and
documentation are available here [http://codeblue.umich.edu/hoomd-blue/about.html]. More information about our installation can be
found here [[HOOMD]].
</div>
</div>

'''<p style="font-size:17px;" >HOPSPACK</p>'''
<div class="toccolours mw-collapsible mw-collapsed">
HOPSPACK stands for Hybrid Optimization Parallel Search Package designed to help users to solve wide range of derivative free optimization problems.
<div class="mw-collapsible-content">The later can be noisy, non-convex or non-smooth ones. The basic optimization problem addressed is to minimize objective function on n unknowns f(x) subject to constrains: $A_I$th>Ax ≥ bi Aex = be ci(x) ≥ 0 ce(x) = 0 l≤x≤u
The first two constraints specify linear inequalities and equalities with coefficient matrices AI and AE. The next two constraints describe nonlinear inequalities and equalities captured in functions cI(x) and cE(x). The final constraints denote lower and upper bounds on the variables. HOPSPACK allow variables to be continuous or integer-valued and has provisions for multi-objective optimization problems. In general, functions f(x),cI(x), and cE(x) can be noisy and nonsmooth, although most algorithms perform best on determinate functions with continuous derivatives.

The users are allowed to design and implement their own solver either by writing their own code or by building existing solvers already in a framework. Because all solvers (called citizens) are members of the same global class they can share assigned resources.
The main features of the package are:

- Only function values are required for the optimization.
- The user must provide a separate program that can evaluate the objective and nonlinear constraint functions at a given point.
- A robust implementation of the Generating Set Search (GSS) solver is supplied, including the capability to handle linear constraints.
- Multiple solvers can run simultaneously and are easily configured to share information.
- Solvers may share a cache of computed function and constraint evaluations to eliminate duplicate work.
- Solvers can initiate and control sub-problems
Continuation -> [[HOPSACK]].
</div>
</div>

'''<p style="font-size:17px;" >HONDO PLUS</p>'''
<div class="toccolours mw-collapsible mw-collapsed">
Hondo Plus is a versatile electronic structure code that combines work from
the original Hondo application developed by Harry King in the lab of Michel Dupuis
and John Rys, and that of numerous subsequent contributers.

<div class="mw-collapsible-content">
It is currently distributed from the research lab of Dr. Donald Truhlar at the University
of Minnesota. Part of the advantage of Hondo Plus is the availability of source
implementations of a wide variety of model chemistries developed over its life time
that researchers can adapt to their particular needs. The license to use the code requires
a literature citation which is documented in the Hondo Plus 5.1 manual found
at:

http://comp.chem.umn.edu/hondoplus/HONDOPLUS_Manual_v5.1.2007.2.17.pdf

More information about our installation can be found here [[HONDO PLUS]].
</div>
</div>

'''<p style="font-size:17px;" >HUMAnN2</p>'''
HUMAnN is a pipeline for efficiently and accurately profiling the presence/absence and abundance of microbial pathways in a community from metagenomic or metatranscriptomic sequencing data (typically millions of short DNA/RNA reads). HUMAnN2 is the next generation of HUMAnN (HMP Unified Metabolic Analysis Network). Details and submission scripts can be found at: http://wiki.csi.cuny.edu/cunyhpc/index.php/Applications_Environment/humann2
</div>

<div class="mw-collapsible mw-collapsed">

== I ==
<div class="mw-collapsible-content">

'''<p style="font-size:17px;" >IMa2</p>'''

<div class="toccolours mw-collapsible mw-collapsed">
The IMa2 application performs basic calculations ‘Isolation with Migration’ using Bayesian inference and Markov
chain Monte Carlo methods.
<div class="mw-collapsible-content">
The only major conceptual addition to IMa2 that makes it different from the
original IMa program is that it can handle data from multiple populations. This requires that the user
specify a phylogenetic tree. Importantly, the tree must be rooted, and the sequence in time of internal
nodes must be known and specified. More information on the IMa2 and IMa can be found in the user
manual here [http://lifesci.rutgers.edu/%7Eheylab/ProgramsandData/Programs/IMa2/Using_IMa2_8_24_2011.pdf].
Information about our installation can be found here [[IMA2]].
</div>
</div>

'''<p style="font-size:17px;" >I-TASSER</p>'''
I-TASSER is a platform for protein structure and function predictions. 3D models are built based on multiple-threading alignments by LOMETS and iterative template fragment assembly simulations; function inslights are derived by matching the 3D models with BioLiP protein function database. Details and submission scripts can be found at: http://wiki.csi.cuny.edu/cunyhpc/index.php/Applications_Environment/itasser

</div>

<div class="mw-collapsible mw-collapsed">

== J ==
<div class="mw-collapsible-content">

'''<p style="font-size:17px;" >JULIA</p>'''
Julia is a high-level, high-performance dynamic programming language for technical computing, with syntax that is familiar to users of other technical computing environments. Julia is installed on Penzias.
<br />
</div>
<div class="mw-collapsible mw-collapsed">

== L ==
<div class="mw-collapsible-content">

'''<p style="font-size:17px;" >LAMARC</p>'''
<div class="toccolours mw-collapsible mw-collapsed">
LAMARC is a program which estimates population-genetic parameters such as population size, population growth rate,
recombination rate, and migration rates.
<div class="mw-collapsible-content">
It approximates a summation over all possible genealogies that could explain
the observed sample, which may be sequence, SNP, microsatellite, or electrophoretic data. LAMARC and its sister program
MIGRATE are successor programs to the older programs Coalesce, Fluctuate, and Recombine, which are no longer being
supported. These programs are memory-intensive, but can run effectively on workstations. They are supported on a variety
of operating systems. For more detail on LAMARC please visit the website here [http://evolution.genetics.washington.edu/lamarc/index.html],
read this paper [http://evolution.genetics.washington.edu/lamarc/download/bioinformatics2006-lamarc2.0.pdf], and look
at the documentation here [http://evolution.genetics.washington.edu/lamarc/documentation/index.html]. More information
about our installation can be found here [[LAMARC]].
</div>
</div>

'''<p style="font-size:17px;" >LAMMPS</p>'''
<div class="toccolours mw-collapsible mw-collapsed">
LAMMPS is a classical molecular dynamics code that models an ensemble of particles in a liquid, solid, or gaseous state.
<div class="mw-collapsible-content">

It can model atomic, polymeric, biological, metallic, granular, and coarse-grained systems using a variety of force fields and boundary conditions.
LAMMPS runs efficiently on single-processor desktop or laptop machines, but is also designed for parallel computers, including clusters with and without GPUs.
It will run on any parallel machine that compiles C++ and supports the MPI message-passing library. This includes distributed- or shared-memory parallel
machines and Beowulf-style clusters. LAMMPS can model systems with only a few particles up to millions or billions. LAMMPS is a freely-available open-source
code, distributed under the terms of the GNU Public License, which means you can use or modify the code however you wish. LAMMPS is designed to be easy to
modify or extend with new capabilities, such as new force fields, atom types, boundary conditions, or diagnostics. A complete description of LAMMPS can be found
in its on-line manual here [http://lammps.sandia.gov/doc/Manual.html] or from the full PDF manual here [http://lammps.sandia.gov/doc/Manual.pdf]. Information
about our installation can be found here [[LAMMPS]].
</div>
</div>

'''<p style="font-size:17px;" >LS-DYNA</p>'''
<div class="toccolours mw-collapsible mw-collapsed">

From its early development in the 1970s, LS-DYNA has evolved into a general purpose material
stress, collision, and crash analysis program with many built-in material and structural element
models.

<div class="mw-collapsible-content">

In recent years, the code has also been adapted for both OpenMP and MPI parallel execution
on a variety of platforms. The most recent version, LS-DYNA 7.1.2, is installed on
ANDY at the CUNY HPC Center under an academic license held by the City College of New York.
The use of this license to do work that is commercial in anyway is prohibited.

Details on LS-DYNA's use, input deck construction, and execution options can be found in the LS-DYNA
manual here [http://ftp.lstc.com/user/manuals/ls-dyna_971_manual_k_rev1.pdf]. All files related
to the HPC Center installation of version 971 (executables and example inputs) are located in:

/share/apps/lsdyna/default/[bin,examples]

More information about our installation can be found here [[LSDYNA]].

</div>
</div>
</div>

<div class="mw-collapsible mw-collapsed">
== M ==
<div class="mw-collapsible-content">

'''<p style="font-size:17px;" >MAGMA</p>'''

MAGMA is a library similar to LAPACK but for hybrid architectures. MAGMA provides implementations for CUDA, Intel Xeon Phi, and OpenCL.
On CUNY HPCC systems, MAGMA is installed in its CUDA variant only on Penzias.

'''<p style="font-size:17px;" >MATHEMATICA</p>'''
<div class="toccolours mw-collapsible mw-collapsed">
“Mathematica” is a fully integrated technical computing system that combines fast, high-precision numerical and symbolic computation with data visualization and programming capabilities.
<div class="mw-collapsible-content">
Mathematica is currently installed on the CUNY HPC Center's ANDY cluster (andy.csi.cuny.edu) and KARLE standalone server (karle.csi.cuny.edu). The basics of running Mathematica on CUNY HPC systems are present here. Additional information on how to use Mathematica can be found at http://www.wolfram.com/learningcenter/

More information is available in this wiki, find it here [[MATHEMATICA]].
</div>
</div>

'''<p style="font-size:17px;" >MATLAB</p>'''
<div class="toccolours mw-collapsible mw-collapsed">
The MATLAB high-performance language for technical computing
integrates computation, visualization, and programming in an
easy-to-use environment where problems and solutions are expressed in
familiar mathematical notation.
<div class="mw-collapsible-content">
Typical uses include:
<pre>
Math and computation

Algorithm development

Data acquisition

Modeling, simulation, and prototyping

Data analysis, exploration, and visualization

Scientific and engineering graphics

Application development, including graphical user interface building
</pre>

More information about our installation can be found here [[MATLAB]]
</div>
</div>

'''<p style="font-size:17px;" >MET (Model Evaluation Tools)</p>'''
<div class="toccolours mw-collapsible mw-collapsed">
MET was developed by the National Center for Atmospheric Research (NCAR) Developmental Testbed Center (DTC) through the generous support of the U.S. Air Force Weather Agency (AFWA) and the National Oceanic and Atmospheric Administration (NOAA).
<div class="mw-collapsible-content">MET is designed to be a highly-configurable, state-of-the-art suite of verification tools. It was developed using output from the Weather Research and Forecasting (WRF) modeling system but may be applied to the output of other modeling systems as well.

MET provides a variety of verification techniques, including:

*Standard verification scores comparing gridded model data to point-based observations
*Standard verification scores comparing gridded model data to gridded observations
*Spatial verification methods comparing gridded model data to gridded observations using neighborhood, object-based, and intensity-scale decomposition approaches
*Probabilistic verification methods comparing gridded model data to point-based or gridded observations

More information about use and set-up can be found here [[MET]]

</div>
</div>

'''<p style="font-size:17px;" >Migrate</p>'''
<div class="toccolours mw-collapsible mw-collapsed">
Migrate estimates population parameters, effective population sizes and migration rates
of n populations, using genetic data. It uses a coalescent theory approach taking into
account the history of mutations and the uncertainty of the genealogy.
<div class="mw-collapsible-content">The estimates of the parameter values are achieved by either a Maximum likelihood (ML) approach or Bayesian
inference (BI). Migrate's output is presented in an TEXT file and in a PDF file. The PDF file
eventually will contain all possible analyses including histograms of posterior distributions.
More information about our installation can be found here [[MIGRATE]]
</div>
</div>

'''<p style="font-size:17px;" >MPFR</p>'''
<div class="toccolours mw-collapsible mw-collapsed">
The MPFR library is a C library for multiple-precision floating-point computations with correct rounding. MPFR has continuously been supported by
the INRIA and the current main authors come from the Caramel and AriC project-teams at Loria (Nancy, France) and LIP (Lyon, France) respectively; see
more on the credit page.
<div class="mw-collapsible-content">

MPFR is based on the GMP multiple-precision library. The main goal of MPFR is to provide a library for multiple-precision
floating-point computation which is both efficient and has a well-defined semantics. It copies the good ideas from the ANSI/IEEE-754 standard for
double-precision floating-point arithmetic (53-bit significant). The library is installed on PENZIAS.

</div>
</div>

'''<p style="font-size:17px;" >MRBAYES</p>'''
<div class="toccolours mw-collapsible mw-collapsed">
MrBayes is a program for the Bayesian estimation of phylogeny. Bayesian inference of
phylogeny is based upon a quantity called the posterior probability distribution of trees,
which is the probability of a tree conditioned on certain observations.
<div class="mw-collapsible-content">
The conditioning is
accomplished using Bayes's theorem. The posterior probability distribution of trees is
impossible to calculate analytically; instead, MrBayes uses a simulation technique called
Markov chain Monte Carlo (or MCMC) to approximate the posterior probabilities of trees.
More information about our installation can be found here [[MRBAYES]]
</div>
</div>

'''<p style="font-size:17px;" >msABC</p>'''
<div class="toccolours mw-collapsible mw-collapsed">
msABC is a program for simulating various neutral evolutionary demographic scenarios
based on the software ms (Hudson 2002). msABC extends ms, calculating a multitude of
summary statistics.
<div class="mw-collapsible-content">
Therefore, msABC is suitable for performing the sampling step of an
Approximate Bayesian Computation analysis (ABC), under various neutral demographic
models. The main advantages of msABC are (i) use of various prior distributions, such as
uniform, Gaussian, log-normal, gamma, (ii) implementation of a multitude summary statistics
for one or more populations, (iii) efficient implementation, which allows the analysis of
hundrends of loci and chromosomes even in a single computer, (iv) extended flexibility, such
as simulation of loci of variable size and simulation of missing data.
More information about our installation can be found here [[msABC]]
</div>
</div>

'''<p style="font-size:17px;" >MSMS</p>'''

<div class="toccolours mw-collapsible mw-collapsed">
MSMS is a tool to generate sequence samples under both neutral models and single locus selection models.
MSMS permits the full range of demographic models provided by its relative MS (Hudson, 2002).
<div class="mw-collapsible-content">
In particular, it allows for multiple demes with arbitrary migration patterns, population growth and decay in each deme, and
for population splits and mergers. Selection (including dominance) can depend on the deme and also change
with time.
More information about our installation can be found here [[MSMS]]
</div>
</div>
</div>

<div class="mw-collapsible mw-collapsed">

== N ==
<div class="mw-collapsible-content">

'''<p style="font-size:17px;" >NAMD</p>'''
<div class="toccolours mw-collapsible mw-collapsed">
NAMD is a parallel molecular dynamics code designed for high-performance simulation
of large biomolecular systems. [http://www.ks.uiuc.edu/Research/namd].
<div class="mw-collapsible-content">
The main server for Molecular Dynamics Calculations is PENZIAS which supports both GPU and non GPU versions of NAMD.
However the MPI only (no GPU support) parallel versions of NAMD are also installed on SALK and ANDY.
More information about our installation can be found here [[NAMD]]
</div>
</div>

'''<p style="font-size:17px;" >Network Simulator-2 (NS2)</p>'''
<div class="toccolours mw-collapsible mw-collapsed">
NS2 is a discrete event simulator targeted at networking research. NS2 provides
substantial support for simulation of TCP, routing, and multicast protocols over
wired and wireless (local and satellite) networks.
<div class="mw-collapsible-content">
It is installed on BOB at the CUNY HPC Center. For more detailed information look here [http://www.isi.edu/nsnam/ns/ here].
More information about our installation can be found here [[NS2]]
</div>
</div>

'''<p style="font-size:17px;" >NWChem</p>'''
<div class="toccolours mw-collapsible mw-collapsed">
NWChem is an ab initio computational chemistry software package which also includes molecular dynamics (MM, MD) and coupled, quantum mechanical and molecular dynamics functionality (QM-MD).
<div class="mw-collapsible-content">
NWChem has been developed by the Molecular Sciences Software group at the Department of Energy's EMSL. The software is available on PENZIAS and ANDY.
More information about our installation can be found here [[NWChem]]
</div>
</div>

</div>

<div class="mw-collapsible mw-collapsed">
== O ==
<div class="mw-collapsible-content">

'''<p style="font-size:17px;" >Octopus</p>'''
<div class="toccolours mw-collapsible mw-collapsed">
Octopus is a pseudopotential real-space package aimed at the simulation of the electron-ion dynamics of one-, two-, and three-dimensional ﬁnite systems subject to time-dependent electromagnetic ﬁelds.
<div class="mw-collapsible-content">
The program is based on time-dependent density-functional theory (TDDFT) in the Kohn-Sham scheme. All quantities are expanded in a regular mesh in real space, and the simulations are performed in real time. The program has been successfully used to calculate linear and non-linear absorption spectra, harmonic spectra, laser induced fragmentation, etc. of a variety of systems.
More information about our installation can be found here [[OCTOPUS]]
</div>
</div>

'''<p style="font-size:17px;" >OpenMM</p>'''
<div class="toccolours mw-collapsible mw-collapsed">
OpenMM is both a library and a stand-alone application which provides tools for modern molecular modeling simulation. As a library it can be hooked into any code, allowing that code to do molecular modeling with minimal extra coding.
<div class="mw-collapsible-content">
Moreover, OpenMM has a strong emphasis on hardware acceleration via GPU, thus providing not just a consistent API, but much greater performance than what one could get from just about any other code available. OpenMM was developed as a part of Physics-Based Simulation project with project leader prof. Pande.
</div>
</div>

'''<p style="font-size:17px;" >OpenFOAM</p>'''
<div class="toccolours mw-collapsible mw-collapsed">
OpenFOAM is before everything a library which users may incorporate in their own code(s). The OpenFOAM is installed on PENZIAS.
<div class="mw-collapsible-content">
More information about our installation can be found here [[OpenFOAM]]
</div>
</div>

'''<p style="font-size:17px;" >OpenSees</p>'''
<div class="toccolours mw-collapsible mw-collapsed">
OpenSees, the Open System for Earthquake Engineering Simulation, is an object-oriented, open source software framework.
<div class="mw-collapsible-content">
It allows users to create both serial and parallel finite element computer applications for simulating the response of structural and geotechnical systems subjected to earthquakes and other hazards. OpenSees is primarily written in C++ and uses several Fortran and C numerical libraries for linear equation solving, and material and element routines. The software is installed on PENZIAS.
</div>
</div>

'''<p style="font-size:17px;" >ORCA</p>'''
<div class="toccolours mw-collapsible mw-collapsed">
The program ORCA is electronic structure program capable to carry out geometry optimizations and to predict a large number of spectroscopic parameters at different levels of theory.
<div class="mw-collapsible-content">
Besides the use of Hartee Fock theory, density functional theory (DFT) and semiempirical methods, high level ab initio quantum chemical methods, based on the configuration interaction and coupled cluster methods, are included into ORCA to an increasing degree.
More information about our installation can be found here [[ORCA]]
</div>
</div>
</div>

<div class="mw-collapsible mw-collapsed">
== P ==
<div class="mw-collapsible-content">

'''<p style="font-size:17px;" >ParGAP</p>'''
<div class="toccolours mw-collapsible mw-collapsed">
ParGAP is build on top of GAP system. The later is a system for computational discrete algebra, with particular emphasis on Computational Group Theory. GAP provides a programming language, a library of thousands of functions implementing algebraic algorithms written in the GAP language as well as large data libraries of algebraic objects.
<div class="mw-collapsible-content">
The ParGAP (Parallel GAP) package itself provides a way of writing parallel programs using the GAP language. Former names of the package were ParGAP/MPI and GAP/MPI; the word MPI refers to Message Passing Interface, a well-known standard for parallelism. ParGAP is based on the MPI standard, and this distribution includes a subset implementation of MPI, to provide a portable layer with a high level interface to BSD sockets.
More information about our installation can be found here [[ParGAP]]
</div>
</div>

'''<p style="font-size:17px;" >POPABC</p>'''
<div class="toccolours mw-collapsible mw-collapsed">
PopABC is a computer package to estimate historical demographic parameters of closely related species/populations (e.g. population size, migration rate, mutation rate, recombination rate, splitting events) within a Isolation with migration model.
<div class="mw-collapsible-content">
The software performs coalescent simulation in the framework of approximate Bayesian computation (ABC, Beaumont et al, 2002). PopABC can also be used to perform Bayesian model choice to discriminate between different demographic scenarios. The program can be used either for research or for education and teaching purposes. Further details and a manual can be found at the POPABC website here [http://code.google.com/p/popabc]
More information about our installation can be found here [[POPABC]]
</div>
</div>

'''<p style="font-size:17px;" >PHOENICS</p>'''
<div class="toccolours mw-collapsible mw-collapsed">
PHOENICS is an integrated Computational Fluid Dynamics (CFD) package for the preparation, simulation, and visualization of
processes involving fluid flow, heat or mass transfer, chemical reaction, and/or combustion in engineering equipment, building
design, and the environment. More detail is available at the CHAM website, here http://www.cham.co.uk.
<div class="mw-collapsible-content">
Although we expect most users to pre- and post-process their jobs on office-local clients, the CUNY HPC Center has installed
the Unix version of the ''entire'' PHOENICS package on ANDY. PHOENICS is installed in /share/apps/phoenics/default where all
the standard PHOENICS directories are located (d_allpro, d_earth, d_enviro, d_photo, d_priv1, d_satell, etc.). Of particular interest
on ANDY is the MPI parallel version of the 'earth' executable 'parexe' which makes full use of the parallel processing power of the
ANDY cluster for larger individual jobs. While the parallel scaling properties of PHOENICS jobs will vary depending on the job size,
processor type, and the cluster interconnect, larger work loads will generally scale and run efficiently on from 8 to 32 processors,
while smaller problems will scale efficiently only up to about 4 processors. More detail on parallel PHOENICS is available at
http://www.cham.co.uk/products/parallel.php. Aside from the tightly coupled MPI parallelism of 'parexe', users can run multiple
instances of the non-parallel modules on ANDY (including the serial 'earexe' module) when a parametric approach can be used
to solve their problems.
More information about our installation can be found here [[PHOENICS]]

</div>
</div>

'''<p style="font-size:17px;" >PHRAP-PHRED</p>'''
<div class="toccolours mw-collapsible mw-collapsed">
PHRAP and PHRED are part of the DNA sequence analysis tool set that also includes the programs
CROSSMATCH and SWAT. These tools are describe in detail here [http://www.phrap.org/phredphrapconsed.html],
but a brief description of both, extracted from their manuals, follows.
<div class="mw-collapsible-content">
PHRED and PHRAP (along with CONSED) can be used for both small sequence assemblies and larger shotgun analyses. This makes the
tools a perhaps under-utilized set for smaller non-genomic groups. Some variables may need to be adjusted,
particularly in CONSED, but researchers that have multiple sequences from a small locus can use the
suite, starting from their chromatogram files.
More information about our installation can be found here [[PHRAP-PHRED]]
</div>
</div>

'''<p style="font-size:17px;" >PyRAD</p>'''
<div class="toccolours mw-collapsible mw-collapsed">
Reduced-representation genomic sequence data (e.g., RADseq, GBS, ddRAD) are commonly used to study population-level research questions and consequently most software packages for assembling or analyzing such data are designed for sequences with little variation across samples.
<div class="mw-collapsible-content">
Phylogenetic analyses typically include species with deeper divergence times (more variable loci across samples) and thus a different approach to clustering and identifying orthologs will perform better. pyRAD is intended for use with any type of restriction-site associated DNA. It currently supports RAD, ddRAD, PE-ddRAD, GBS, PE-GBS, EzRAD, PE-EzRAD, 2B-RAD, nextRAD, and can be extended to other types.
More information about our installation can be found here [[PyRAD]]
</div>
</div>

'''<p style="font-size:17px;" >Python</p>'''
<div class="toccolours mw-collapsible mw-collapsed">
Python is a programming language that lets you work more quickly and integrate your systems more effectively. You can learn to use Python and see almost immediate gains in productivity and lower maintenance costs. [http://www.python.org/]
<div class="mw-collapsible-content">
There are two supported versions installed on Andy system:

* Python 3.1.3 located under /share/apps/python/3.1.3/bin
* Python 2.7.3 located under /share/apps/epd/7.3-2/bin

More information about our installation can be found here [[PYTHON]]

</div>
</div>

'''<p style="font-size:17px;" >Installing Python packages</p>'''
<div class="toccolours mw-collapsible mw-collapsed">
Users may install python packages/modules in their own space. Many packages available in Python repositories can be installed easily with PIP manager, which is available in any of Anaconda and Miniconda builds.
<div class="mw-collapsible-content">
Users must remember that using PIP without first loading the module for python will cause the installed modules to match system python on login node only. However the python interpreter available (after login module) on all nodes is installed in /share/usr/compilers/python space. Thus when installing packages in user space it is very important to follow the procedure outlined below. The given example demonstrates how users can install package "guppy" in their own space:

For Python 2.7.13 in Anaconda build:

<pre>
module load python/2.7.13_anaconda
pip install guppy --user
</pre>

For Python 3.6.0 in Anaconda build

<pre>
module load python/3.6.0_anaconda
pip install guppy --user
</pre>

For Python 2.7.13 in Miniconda

<pre>
module load python/miniconda2
pip install guppy --user
</pre>

For Python 3.6.0 in Miniconda 3

<pre>
module load python/miniconda3
pip install guppy --user
</pre>

To check if the package is properly installed type:

<pre>
pip list | grep guppy
</pre>

</div>
</div>
</div>

<div class="mw-collapsible mw-collapsed">
== Q ==
<div class="mw-collapsible-content">

'''<p style="font-size:17px;" >QIIME</p>'''
<div class="toccolours mw-collapsible mw-collapsed">
QIIME (pronounced "chime") stands for Quantitative Insights Into Microbial Ecology. QIIME is a pipeline application that uses numerous third-party applications.
<div class="mw-collapsible-content">

QIIME takes users from their raw sequencing output through initial analyses such as OTU picking, taxonomic assignment, and construction of phylogenetic trees from representative sequences of OTUs, and through downstream statistical analysis, visualization, and production of publication-quality graphics.
More information about our installation can be found here [[QIIME]]
</div>
</div>
</div>

<div class="mw-collapsible mw-collapsed">
== R ==
<div class="mw-collapsible-content">

'''<p style="font-size:17px;" >R</p>'''

<div class="toccolours mw-collapsible mw-collapsed">
R is a free software environment for statistical computing and graphics.
<div class="mw-collapsible-content">
'''<p style="font-size:15px;" >General Notes</p>'''

R language has become a de facto standard among statisticians for the development of statistical software, and is widely used for statistical software development and data analysis. R is available on the following HPCC's servers: Karle, Penzias, Appel and Andy. Karle is the only machine where R can be used without submitting jobs to SLURM manager. On all other systems users must submit their R jobs via SLURM batch scheduler.
More information about our installation can be found here [[R]]
</div>
</div>

'''<p style="font-size:17px;" >RAXML</p>'''
<div class="toccolours mw-collapsible mw-collapsed">
Randomized Axelerated Maximum Likelihood (RAxML) is a program for sequential and parallel
maximum likelihood based inference of large phylogenetic trees. It is a descendent of fastDNAml
which in turn was derived from Joe Felsentein’s DNAml which is part of the PHYLIP package.
<div class="mw-collapsible-content">
RAxML is installed at the CUNY HPC Center on ANDY. Multiple versions are available. RAxML is available in both serial and MPI parallel versions. The MPI-parallel version should be run on four or more cores. RaxML parallel MPI version is installed on Penzias.
More information about our installation can be found here [[RAXML]]
</div>
</div>
</div>

<div class="mw-collapsible mw-collapsed">
== S ==
<div class="mw-collapsible-content">

'''<p style="font-size:17px;" >SAGE</p>'''
<div class="toccolours mw-collapsible mw-collapsed">
Sage can be used to study elementary and advanced, pure and applied mathematics.
<div class="mw-collapsible-content">
This includes a huge range of mathematics, including basic algebra, calculus, elementary to very
advanced number theory, cryptography, numerical computation, commutative algebra, group
theory, combinatorics, graph theory, exact linear algebra and much more.
More information about our installation can be found here [[SAGE]]
</div>
</div>

'''<p style="font-size:17px;" >SAMTOOLS</p>'''
<div class="toccolours mw-collapsible mw-collapsed">
SAMTOOLS provide various utilities for manipulating alignments in the SAM format, including sorting,
merging, indexing and generating alignments in a per-position format.
<div class="mw-collapsible-content">
SAM (Sequence Alignment/Map) format is a generic format for storing large nucleotide sequence alignments. SAM is compact format
aims to be a format that:

<pre>
Is flexible enough to store all the alignment information generated by various alignment programs;

Is simple enough to be easily generated by alignment programs or converted from existing formats;

Allows most of operations on the alignment to work without loading the whole alignment into memory;

Allows the file to be indexed by genomic position to efficiently retrieve all reads aligning to a locus.
</pre>

More information about our installation can be found here [[SAMTOOLS]]
</div>
</div>

'''<p style="font-size:17px;" >SAS</p>'''
<div class="toccolours mw-collapsible mw-collapsed">
SAS (pronounced "sass", originally Statistical Analysis System) is an integrated system of software products provided by SAS Institute Inc.
<div class="mw-collapsible-content">
It enables the programmer to perform:
:* data entry, retrieval, management, and mining
:* report writing and graphics
:* statistical analysis
:* business planning, forecasting, and decision support
:* operations research and project management
:* quality improvement
:* applications development
:* data warehousing (extract, transform, load)
:* platform independent and remote computing
More information about our installation can be found here [[SAS]]
</div>
</div>

'''<p style="font-size:17px;" >Stata/MP</p>'''
<div class="toccolours mw-collapsible mw-collapsed">
Stata is a complete, integrated statistical package that provides tools for data analysis, data management, and graphics. Stata/MP takes advantage of multiprocessor computers. CUNY HPC Center is licensed to use Stata on up to 8 cores.
<div class="mw-collapsible-content">
Currently Stata/MP is available for users on Karle (karle.csi.cuny.edu).
More information about our installation can be found here [[STATA]]
</div>
</div>

'''<p style="font-size:17px;" >Structurama</p>'''
<div class="toccolours mw-collapsible mw-collapsed">
Structurama is a program for inferring population structure from genetic data. The program assumes that the sampled loci
are in linkage equilibrium and that the allele frequencies for each population are drawn from a Dirichlet probability distribution. Two different models for population structure are implemented.
<div class="mw-collapsible-content">
First, Structurama offers the method of Pritchard et al. (2000) in which the number of populations is considered fixed. The program also allows the number of populations to be a random variable following a Dirichlet process prior(Pella and Masuda, 2006; Huelsenbeck and Andolfatto, 2007).
More information about our installation can be found here [[STRUCTURAMA]]
</div>
</div>

'''<p style="font-size:17px;" >Structure</p>'''
<div class="toccolours mw-collapsible mw-collapsed">
The program Structure is a free software package for using multi-locus genotype data to investigate
population structure. Its uses include inferring the presence of distinct populations, assigning individuals
to populations, studying hybrid zones, identifying migrants and admixed individuals, and estimating
population allele frequencies in situations where many individuals are migrants or admixed.
<div class="mw-collapsible-content">It can be applied to most of the commonly-used genetic markers, including SNPS, microsatellites, RFLPs and AFLPs. More detailed information about Structure can be found at the web site here [http://pritch.bsd.uchicago.edu/structure.html]. Structure is installed on ANDY at the CUNY HPC Center. Structure is a serial program.
More information about our installation can be found here [[STRUCTURE]]
</div>
</div>
</div>

<div class="mw-collapsible mw-collapsed">

== T ==
<div class="mw-collapsible-content">

'''<p style="font-size:17px;" >Thrust Library (CUDA)</p>'''
<div class="toccolours mw-collapsible mw-collapsed">
Thrust is a C++ template library for CUDA based on the Standard Template Library (STL). Thrust allows you
to implement high performance parallel applications with minimal programming effort through a high-level
interface that is fully interoperable with CUDA C.
<div class="mw-collapsible-content">
As of CUDA, Thrust has been integrated into the default
CUDA distribution. The HPC Center is currently running CUDA as the default on PENZIAS which includes
Thrust library. More information about our installation can be found here [[THRUST]]
</div>
</div>

'''<p style="font-size:17px;" >TOPHAT</p>'''
<div class="toccolours mw-collapsible mw-collapsed">
TOPHAT is a fast splice junction mapper for RNA-Seq reads. It aligns RNA-Seq reads to mammalian-sized
genomes using the ultra high-throughput short read aligner Bowtie, and then analyzes the mapping results
to identify splice junctions between exons.
<div class="mw-collapsible-content">
TOPHAT is part of a sequence alignment and analysis tool chain developed at John Hopkins, University of California at Berkeley, and Harvard, and distributed through the Center for Bioinformatics and Computational Biology.
More information about our installation can be found here [[TOPHAT]]
</div>
</div>

'''<p style="font-size:17px;" >Trinity</p>'''
<div class="toccolours mw-collapsible mw-collapsed">
Trinity, developed at the Broad Institute and the Hebrew University of Jerusalem, represents a novel method for the efficient and robust de novo reconstruction of transcriptomes from RNA-seq data.
<div class="mw-collapsible-content">
Trinity combines three independent software modules: Inchworm, Chrysalis, and Butterfly, applied sequentially to process large volumes of RNA-seq reads. Trinity partitions the sequence data into many individual de Bruijn graphs, each representing the transcriptional complexity at at a given gene or locus, and then processes each graph independently to extract full-length splicing isoforms and to tease apart transcripts derived from paralogous genes.
More information about our installation can be found here [[TRINITY]]
</div>
</div>
</div>

<div class="mw-collapsible mw-collapsed">
== U ==
<div class="mw-collapsible-content">

'''<p style="font-size:17px;" >USEARCH</p>'''
<div class="toccolours mw-collapsible mw-collapsed">
USEARCH is a unique sequence analysis tool with thousands of users world-wide.
<div class="mw-collapsible-content">
USEARCH offers search and clustering algorithms that are often orders of magnitude faster than BLAST.
More information about our installation can be found here [[USEARCH]]
</div>
</div>
</div>

<div class="mw-collapsible mw-collapsed">
== V ==
<div class="mw-collapsible-content">

'''<p style="font-size:17px;" >VELVET</p>'''
Velvet is a set of algorithms for ''de novo'' short read assembly using de Bruijn graphs. It was developed at the European Bioinformatics Institute, Cambridge, UK. More information about our installation can be found here [[VELVET]].

'''<p style="font-size:17px;" >VSEARCH</p>'''
<div class="toccolours mw-collapsible mw-collapsed">
VSEARCH is a open source alternative to USEARCH.
<div class="mw-collapsible-content">
VSEARCH stands for vectorized search, as the tool takes advantage of parallelism in the form of SIMD vectorization as well as multiple threads to perform accurate alignments at high speed. VSEARCH uses an optimal global aligner (full dynamic programming Needleman-Wunsch), in contrast to USEARCH which by default uses a heuristic seed and extend aligner. This usually results in more accurate alignments and overall improved sensitivity (recall) with VSEARCH, especially for alignments with gaps.

Additional details on VSEARCH can be found at: [https://github.com/torognes/vsearch this link]

VSEARCH is installed on Penzias HPC cluster. To start using VSEARCH load corresponding module first:

<pre>
module load vsearch
</pre>

</div>
</div>

'''<p style="font-size:17px;" >VMD</p>'''
<div class="toccolours mw-collapsible mw-collapsed">
VMD is a molecular visualization program for displaying, animating, and analyzing large biomolecular systems using 3-D graphics and built-in scripting.
<div class="mw-collapsible-content">
It was developed by The Theoretical and Computational Biophysics Group at the University of Illinois. It is documented on the [http://www.ks.uiuc.edu/Research/vmd/ TCB's homepage].

VMD is installed on Karle. To use it within command-line interface login to Karle as usual and start VMD by typing "vmd" followed by return. Or alternatively use the full path:
"/share/apps/vmd/default/bin/vmd"

In order to use VMD in GUI-mode, login to Karle with -X option (see [http://wiki.csi.cuny.edu/cunyhpc/index.php/Main_Page#X11_Forwarding_or_Tunneling this article]
for details) and start VMD as described above.
</div>
</div>
</div>

<div class="mw-collapsible mw-collapsed">

== W ==
<div class="mw-collapsible-content">

'''<p style="font-size:17px;" >WRF</p>'''
<div class="toccolours mw-collapsible mw-collapsed">
The Weather Research and Forecasting (WRF) model is a specific computer program with dual use for both weather
forecasting and weather research.
<div class="mw-collapsible-content">
It was created through a partnership that includes the National Oceanic and Atmospheric
Administration (NOAA), the National Center for Atmospheric Research (NCAR), and more than 150 other organizations
and universities in the United States and abroad. WRF is the latest numerical model and application to be adopted by NOAA's
National Weather Service as well as the U.S. military and private meteorological services. It is also being adopted by
government and private meteorological services worldwide. More information about our installation can be found here [[WRF]]

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== X ==
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'''<p style="font-size:17px;" >Xmgrace</p>'''
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Grace is a WYSIWYG 2D plotting tool for the X Window System and M*tif. Xmgrace is developed at Plasma Laboratory, Weizmann Institute of Science. More information about it's capabilities can be found at the web page http://plasma-gate.weizmann.ac.il/Grace/

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Grace is installed on Karle. To use it within command-line interface login to Karle as usual and start Grace by typing "xmgrace" followed by return. Or alternatively use the full path: "/share/apps/xmgrace/default/grace/bin/xmgrace"
In order to use Grace in GUI-mode, login to Karle with -X option (see [http://wiki.csi.cuny.edu/cunyhpc/index.php/Main_Page#X11_Forwarding_or_Tunneling this article]
for details) and start Xmgrace as described above.
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