PETSc is a suite of data structures and routines for the scalable (parallel) solution of scientific applications modeled by partial differential equations. It supports MPI, and GPUs through CUDA or OpenCL, as well as hybrid MPI-GPU parallelism. The supported libraries include f2cblaslapack, superlu, ptso, metis, parmetis, mumps, hypre and scalapack.
OSC will be refreshing the software stack for Owens and Pitzer on May 19, 2020. This will be done in a system-wide downtime. During the software refresh, some default versions will be changed to be more up-to-date. Information about the new default versions, as well as all available versions of each software package will be included on the corresponding OSC software webpage. See https://www.osc.edu/supercomputing/software-list.
Gurobi is a mathematical optimization solver that supports a variety of programming and modeling languages.
The following versions of bedtools are available on OSC clusters:
OSC is refreshing the software stack for Owens and Ruby on September 4, 2018. This will be done by a rolling reboot. During the software refresh, some default versions are updated to be more up-to-date. Information about the old and new default versions, as well as all available versions of each software package will be included on the corresponding OSC software webpage. See https://www.osc.edu/supercomputing/software-list.
LAPACK (Linear Algebra PACKage) provides routines for solving systems of simultaneous linear equations, least-squares solutions of linear systems of equations, eigenvalue problems, and singular value problems.
A highly optimized implementation of LAPACK is available on all OSC clusters as part of the Intel Math Kernel Library (MKL). We recommend that you use MKL rather than building LAPACK for yourself. MKL is available to all OSC users.
The BLAS (Basic Linear Algebra Subprograms) are routines that provide standard building blocks for performing basic vector and matrix operations.
A highly optimized implementation of the BLAS is available on all OSC clusters as part of the Intel Math Kernel Library (MKL). We recommend that you use MKL rather than building the BLAS for yourself. MKL is available to all OSC users.
MAGMA is a collection of next generation linear algebra (LA) GPU accelerated libraries designed and implemented by the team that developed LAPACK and ScaLAPACK. MAGMA is for heterogeneous GPU-based architectures, it supports interfaces to current LA packages and standards, e.g., LAPACK and BLAS, to allow computational scientists to effortlessly port any LA-relying software components.
OSC is refreshing the software stack for Oakley and Ruby on February 22, 2017 (during the scheduled downtime). During the software refresh, some default versions are updated to be more up-to-date and some older versions are removed. Information about the old and new default versions, as well as all available versions of each software package will be included on the corresponding OSC software webpage. See https://www.osc.edu/supercomputing/software-list.
A hadoop cluster can be launched within the HPC environment, but managed by the PBS job scheduler using Myhadoop framework developed by San Diego Supercomputer Center. (Please see http://www.sdsc.edu/~allans/MyHadoop.pdf)
Apache Spark is an open source cluster-computing framework originally developed in the AMPLab at University of California, Berkeley but was later donated to the Apache Software Foundation where it remains today. In contrast to Hadoop's disk-based analytics paradigm, Spark has multi-stage in-memory analytics. Spark can run programs up-to 100x faster than Hadoop’s MapReduce in memory or 10x faster on disk. Spark support applications written in python, java, scala and R