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Matrix Algebra on GPU: An interview with MAGMA lead developers

Nov 16, 2011, 05:03 (0 Talkback[s])
(Other stories by edwood)

[ Thanks to Edwood Ocasio for this link. ]

"Jack: MAGMA (Matrix Algebra on GPU and Multicore Architectures) is a collection of next generation linear algebra (LA) 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.

"The main benefits of using MAGMA are that MAGMA can enable applications to fully exploit the power of current heterogeneous systems of multi/manycore CPUs and multiGPUs, and deliver the fastest possible time to an accurate solution within given energy constraints.

"By combining the strengths of different architectures, MAGMA overcomes bottlenecks associated with just multicore or GPUs, to significantly outperform corresponding packages for any of these homogeneous components taken separately. MAGMA's one-sided factorizations (and linear solvers) on a single Fermi GPU (and a basic CPU host) can outperform state-of-the-art CPU libraries on high-end multi-socket, multicore nodes (e.g., using up to 48 modern cores). The benefits for the two-sided factorizations (bases for eigenproblem and SVD solvers) are even greater, as the performance can exceed 10X the performance of systems with 48 modern CPU cores. Architecture-specific performances and comparisons can be found through the MAGMA site."

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