Enabling technologies and software for scientific computing
The Innovative Computing Laboratory (ICL) aspires to be a world leader in enabling technologies and software for scientific computing. Our vision is to provide high performance tools to tackle science’s most challenging problems and to play a major role in the development of standards for scientific computing in general.
ICL is a research laboratory in the College of Engineering at the University of Tennessee and serves as the cornerstone laboratory of the Center for Information Technology Research (CITR), one of UT’s nine Centers of Excellence.
Matrix Algebra on GPU and Multicore Architectures (MAGMA) is a collection of next-generation linear algebra (LA) libraries for heterogeneous architectures. The MAGMA package supports interfaces for current LA packages and standards (e.g., LAPACK and BLAS) to allow computational scientists to easily port any LA-reliant software components to heterogeneous architectures. MAGMA allows applications to fully exploit the power of current heterogeneous systems of multi/many-core CPUs and multi-GPUs/coprocessors to deliver the fastest possible time to accurate solution within given energy constraints.
New for 2016, MAGMA 2.2 features LAPACK-compliant routines for multicore CPUs enhanced with NVIDIA GPUs, and includes more than 400 routines, covering one-sided dense matrix factorizations and solvers, and two-sided factorizations and eigen/singular-value problem solvers, as well as a subset of highly optimized BLAS for GPUs. Tuning and support are added for the newest NVIDIA Pascal P100 GPU. The MAGMA Sparse and MAGMA Batched packages were added with the MAGMA 1.6 release and continuously extended and improved since then. MAGMA provides multiple-precision arithmetic support (S/D/C/Z, including mixed precision). Most of the algorithms are hybrid, using both multicore CPUs and GPUs, but starting with the 1.6 release, GPU-specific algorithms were added.