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Matrix Engines for High Performance Computing:A Paragon of Performance
  or Grasping at Straws?

Matrix Engines for High Performance Computing:A Paragon of Performance or Grasping at Straws?

27 October 2020
Jens Domke
Emil Vatai
Aleksandr Drozd
Peng Chen
Yosuke Oyama
Lingqi Zhang
Shweta Salaria
Daichi Mukunoki
Artur Podobas
M. Wahib
Satoshi Matsuoka
ArXivPDFHTML

Papers citing "Matrix Engines for High Performance Computing:A Paragon of Performance or Grasping at Straws?"

2 / 2 papers shown
Title
Myths and Legends in High-Performance Computing
Myths and Legends in High-Performance Computing
Satoshi Matsuoka
Jens Domke
M. Wahib
Aleksandr Drozd
Torsten Hoefler
22
14
0
06 Jan 2023
Sparsity in Deep Learning: Pruning and growth for efficient inference
  and training in neural networks
Sparsity in Deep Learning: Pruning and growth for efficient inference and training in neural networks
Torsten Hoefler
Dan Alistarh
Tal Ben-Nun
Nikoli Dryden
Alexandra Peste
MQ
141
684
0
31 Jan 2021
1