Posted in 2022

Finite difference method - Laplacian part 1

• 14 November 2022
Justin Chang , Rajat Arora , Thomas Gibson , Sean Miller , Ossian O’Reilly
English
Applications & models
HPC Memory Performance Profiling Scientific Computing

14 Nov, 2022 by Justin Chang, Rajat Arora, Thomas Gibson, Sean Miller, Ossian O’Reilly.

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AMD matrix cores

• 14 November 2022
Gina Sitaraman , Damon McDougall , Rene Van Oostrum , Nicholas Malaya , Noel Chalmers , Ossian O’Reilly
English
Software tools & optimizations
Compiler Linear Algebra Memory HPC Optimization

Matrix multiplication is a fundamental aspect of linear algebra and it is an ubiquitous computation within High Performance Computing (HPC) Applications. Since the introduction of AMD’s CDNA Architecture, Generalized Matrix Multiplication (GEMM) computations are now hardware-accelerated through Matrix Core Processing Units. Matrix Core accelerated GEMM kernels lie at the heart of BLAS libraries like rocBLAS but they can also be programmed directly by developers. Applications that are throughput bound by GEMM computation can achieve additional speedups by utilizing Matrix Cores.

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