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VENOM: A Vectorized N:M Format for Unleashing the Power of Sparse Tensor
  Cores

VENOM: A Vectorized N:M Format for Unleashing the Power of Sparse Tensor Cores

3 October 2023
Roberto L. Castro
Andrei Ivanov
Diego Andrade
Tal Ben-Nun
B. Fraguela
Torsten Hoefler
ArXivPDFHTML

Papers citing "VENOM: A Vectorized N:M Format for Unleashing the Power of Sparse Tensor Cores"

4 / 4 papers shown
Title
Navigating Extremes: Dynamic Sparsity in Large Output Spaces
Navigating Extremes: Dynamic Sparsity in Large Output Spaces
Nasib Ullah
Erik Schultheis
Mike Lasby
Yani Andrew Ioannou
Rohit Babbar
33
0
0
05 Nov 2024
Efficient Quantized Sparse Matrix Operations on Tensor Cores
Efficient Quantized Sparse Matrix Operations on Tensor Cores
Shigang Li
Kazuki Osawa
Torsten Hoefler
72
31
0
14 Sep 2022
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
139
684
0
31 Jan 2021
Scaling Laws for Neural Language Models
Scaling Laws for Neural Language Models
Jared Kaplan
Sam McCandlish
T. Henighan
Tom B. Brown
B. Chess
R. Child
Scott Gray
Alec Radford
Jeff Wu
Dario Amodei
226
4,453
0
23 Jan 2020
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