Titlebook: High Performance Computingfor Computational Science -- VECPAR 2010; 9th International Co José M. Laginha M. Palma,Michel Daydé,João Correia

cogent

PRISE

Accelerating GPU Kernels for Dense Linear Algebravelop new kernels (e.g. syrk, symv) that are up to 20× faster than the currently available kernels. We present these kernels and also show their acceleration effect to higher level dense linear algebra routines. The accelerated kernels are now freely available through the MAGMA BLAS library.

Arb853

Intrepid

The Parallel Revolution Has Started: Are You Part of the Solution or Part of the Problem?C. Catanzaro, J. J. Gebis, P. Husbands, K. Keutzer, D. A. Patterson, W. L. Plishker, J. Shalf, S. W. Williams, and K. A. Yelick. The landscape of parallel computing research: A view from Berkeley. Technical Report UCB/EECS-2006-183, EECS Department, University of California, Berkeley, December 18 20

人工制品

Stress-Fracture

匍匐

diabetes

Ataxia

Performance and Numerical Accuracy Evaluation of Heterogeneous Multicore Systems for Krylov Orthogon the influence of the different floating arithmetic handling of these accelerators with Gram-Schmidt orthogonalization using single and double precision. We observe for dense matrices a loss of at worst 1 digit for CUDA-enabled GPUs as well as a speed-up of 20x, and 2 digits for the Cell processor f

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