FTTN: Feature-Targeted Testing for Numerical Properties of NVIDIA & AMD Matrix Accelerators

NVIDIA Tensor Cores and AMD Matrix Cores (together called Matrix Accelerators) are of growing interest in high-performance computing and machine learning owing to their high performance. Unfortunately, some of their crucial numerical attributes pertaining to departures from full IEEE floating-point...

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Bibliographic Details

Published in:	IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing pp. 39 - 46
Main Authors:	Li, Xinyi, Li, Ang, Fang, Bo, Swirydowicz, Katarzyna, Laguna, Ignacio, Gopalakrishnan, Ganesh
Format:	Conference Proceeding
Language:	English
Published:	IEEE 06.05.2024
Subjects:	AMD GPUs Cloud computing Clustering algorithms Codes Correctness Portability floating-point arithmetic High performance computing Iterative algorithms Machine learning Matrix Units NVIDIA GPUs Reliability Tensor Cores Tensors Testing
ISSN:	2993-2114
Online Access:	Get full text
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