Owens cluster will be decommissioned on February 3, 2025. Some pages may still reference Owens after Owens is decommissioned , and we are in the process of gradually updating the content. Thank you for your patience during this transition
Bowtie1 is an ultrafast, memory-efficient short read aligner. It aligns short DNA sequences (reads) to the human genome at a rate of over 25 million 35-bp reads per hour. Bowtie indexes the genome with a Burrows-Wheeler index to keep its memory footprint small: typically about 2.2 GB for the human genome (2.9 GB for paired-end).
The following versions of Bowtie1 are available on OSC clusters:
While we provide a number of Perl modules, you may need a module we do not provide. If it is a commonly used module, or one that is particularly difficult to compile, you can contact OSC Help for assistance, but we have provided an example below showing how to build and install your own Perl modules. Note, these instructions use "bash" shell syntax; this is our default shell, but if you are using something else (csh, tcsh, etc), some of the syntax may be different.
NWChem aims to provide its users with computational chemistry tools that are scalable both in their ability to treat large scientific computational chemistry problems efficiently, and in their use of available parallel computing resources from high-performance parallel supercomputers to conventional workstation clusters.
The following versions of NWChem are available on OSC clusters:
An eligible principal investigator (PI) heads a project account and can authorize/remove user accounts under the project account (please check our Allocations and Accounts documentation for more details). This document shows you how to identify users on a project account and check the status of each user.
Submitting a job without specifying the proper shell will return a warning like below:
sbatch: WARNING: Job script lacks first line beginning with #! shell. Injecting '#!/bin/bash' as first line of job script.
If an error is encountered, the job is rejected.
It is required to specify an account for a job to run. Please use the --account=<project-code> option to do this.
Linaro MAP is a full scale profiler for HPC programs. We recommend using Linaro MAP after reviewing reports from Linaro Performance Reports. MAP supports pthreads, OpenMP, and MPI software on CPU, GPU, and MIC based architectures.
Linaro Performance Reports is a simple tool used to generate a single-page HTML or plain text report that presents the overall performance characteristics of HPC applications. It supports pthreads, OpenMP, or MPI code on CPU, GPU, and MIC based architectures.
MPI is a standard library for performing parallel processing using a distributed memory model. The Pitzer, Ascend, and Cardinal clusters at OSC can use the OpenMPI implementation of the Message Passing Interface (MPI).
PAPI provides the tool designer and application engineer with a consistent interface and methodology for use of the performance counter hardware found in most major microprocessors. PAPI enables software engineers to see, in near real time, the relation between software performance and processor events.
This software will be of interest only to HPC experts.
ParMETIS (Parallel Graph Partitioning and Fill-reducing Matrix Ordering) is an MPI-based parallel library that implements a variety of algorithms for partitioning unstructured graphs, meshes, and for computing fill-reducing orderings of sparse matrices. ParMETIS extends the functionality provided by METIS and includes routines that are especially suited for parallel AMR computations and large scale numerical simulations. The algorithms implemented in ParMETIS are based on the parallel multilevel k-way graph-partitioning, adaptive repartitioning, and parallel multi-constrained partitioning schemes developed in Karypis lab.
METIS (Serial Graph Partitioning and Fill-reducing Matrix Ordering) is a set of serial programs for partitioning graphs, partitioning finite element meshes, and producing fill reducing orderings for sparse matrices. The algorithms implemented in METIS are based on the multilevel recursive-bisection, multilevel k-way, and multi-constraint partitioning schemes developed in Karypis lab.
