Sandia National Laboratories (SNL), also known as Sandia, is one of three research and development laboratories of the United States Department of Energy's National Nuclear Security Administration (NNSA). Headquartered in Kirtland Air Force Base in Albuquerque, New Mexico, it has a second principal facility next to Lawrence Livermore National Laboratory in Livermore, California, and a test facility in Waimea, Kauai, Hawaii. Sandia is owned by the U.S. federal government but privately managed and operated by National Technology and Engineering Solutions of Sandia, a wholly owned subsidiary of Honeywell International.
Parallel Virtual Machine (PVM) is a software tool for parallel networking of computers. It is designed to allow a network of heterogeneous Unix and/or Windows machines to be used as a single distributed parallel processor. Thus large computational problems can be solved more cost effectively by using the aggregate power and memory of many computers. The software is very portable; the source code, available free through netlib, has been compiled on everything from laptops to Crays.
Netlib is a repository of software for scientific computing maintained by AT&T, Bell Laboratories, the University of Tennessee and Oak Ridge National Laboratory. Netlib comprises many separate programs and libraries. Most of the code is written in C and Fortran, with some programs in other languages.
Jack Joseph Dongarra is an American computer scientist and mathematician. He is a University Distinguished Professor Emeritus of Computer Science in the Electrical Engineering and Computer Science Department at the University of Tennessee. He holds the position of a Distinguished Research Staff member in the Computer Science and Mathematics Division at Oak Ridge National Laboratory, Turing Fellowship in the School of Mathematics at the University of Manchester, and is an adjunct professor and teacher in the Computer Science Department at Rice University. He served as a faculty fellow at the Texas A&M University Institute for Advanced Study (2014–2018). Dongarra is the founding director of the Innovative Computing Laboratory at the University of Tennessee. He was the recipient of the Turing Award in 2021.
LAPACK is a standard software library for numerical linear algebra. It provides routines for solving systems of linear equations and linear least squares, eigenvalue problems, and singular value decomposition. It also includes routines to implement the associated matrix factorizations such as LU, QR, Cholesky and Schur decomposition. LAPACK was originally written in FORTRAN 77, but moved to Fortran 90 in version 3.2 (2008). The routines handle both real and complex matrices in both single and double precision. LAPACK relies on an underlying BLAS implementation to provide efficient and portable computational building blocks for its routines.
Basic Linear Algebra Subprograms (BLAS) is a specification that prescribes a set of low-level routines for performing common linear algebra operations such as vector addition, scalar multiplication, dot products, linear combinations, and matrix multiplication. They are the de facto standard low-level routines for linear algebra libraries; the routines have bindings for both C and Fortran. Although the BLAS specification is general, BLAS implementations are often optimized for speed on a particular machine, so using them can bring substantial performance benefits. BLAS implementations will take advantage of special floating point hardware such as vector registers or SIMD instructions.
The GNU Scientific Library is a software library for numerical computations in applied mathematics and science. The GSL is written in C; wrappers are available for other programming languages. The GSL is part of the GNU Project and is distributed under the GNU General Public License.
Linaro DDT is a commercial C, C++ and Fortran 90 debugger. It is widely used for debugging parallel Message Passing Interface (MPI) and threaded programs, including those running on clusters of Linux machines.
The Parallel Virtual File System (PVFS) is an open-source parallel file system. A parallel file system is a type of distributed file system that distributes file data across multiple servers and provides for concurrent access by multiple tasks of a parallel application. PVFS was designed for use in large scale cluster computing. PVFS focuses on high performance access to large data sets. It consists of a server process and a client library, both of which are written entirely of user-level code. A Linux kernel module and pvfs-client process allow the file system to be mounted and used with standard utilities. The client library provides for high performance access via the message passing interface (MPI). PVFS is being jointly developed between The Parallel Architecture Research Laboratory at Clemson University and the Mathematics and Computer Science Division at Argonne National Laboratory, and the Ohio Supercomputer Center. PVFS development has been funded by NASA Goddard Space Flight Center, The DOE Office of Science Advanced Scientific Computing Research program, NSF PACI and HECURA programs, and other government and private agencies. PVFS is now known as OrangeFS in its newest development branch.
Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) is a molecular dynamics program from Sandia National Laboratories. LAMMPS makes use of Message Passing Interface (MPI) for parallel communication and is free and open-source software, distributed under the terms of the GNU General Public License.
The National Energy Research Scientific Computing Center (NERSC) is a high-performance computing (supercomputer) research facility that was founded in 1974. The National User Facility is operated by Lawrence Berkeley National Laboratory for the United States Department of Energy Office of Science.
LAPACK++, the Linear Algebra PACKage in C++, is a computer software library of algorithms for numerical linear algebra that solves systems of linear equations and eigenvalue problems.
Lis is a scalable parallel software library to solve discretized linear equations and eigenvalue problems that mainly arise from the numerical solution of partial differential equations using iterative methods. Although it is designed for parallel computers, the library can be used without being conscious of parallel processing.
Global Arrays, or GA, is the library developed by scientists at Pacific Northwest National Laboratory for parallel computing. GA provides a friendly API for shared-memory programming on distributed-memory computers for multidimensional arrays. The GA library is a predecessor to the GAS languages currently being developed for high-performance computing.
Message passing is an inherent element of all computer clusters. All computer clusters, ranging from homemade Beowulfs to some of the fastest supercomputers in the world, rely on message passing to coordinate the activities of the many nodes they encompass. Message passing in computer clusters built with commodity servers and switches is used by virtually every internet service.
Arm MAP, is an application profiler produced by Allinea Software now part of Arm. of Warwick, United Kingdom, for profiling the performance of C, C++, Fortran 90 and Python software. It is widely used for its multithreaded and multiprocess capabilities such as profiling parallel Message Passing Interface (MPI) or OpenMP applications, including those running on clusters of Linux machines, and for scalar (sequential) code.
Qbox is an open-source software package for atomic-scale simulations of molecules, liquids and solids. It implements first principles molecular dynamics, a simulation method in which inter-atomic forces are derived from quantum mechanics. Qbox is released under a GNU General Public License (GPL) with documentation provided at http://qboxcode.org. It is available as a FreeBSD port.
Performance portability refers to the ability of computer programs and applications to operate effectively across different platforms. Developers of performance portable applications seek to support multiple platforms without impeding performance, and ideally while minimizing platform-specific code.
