Principal Kernel Analysis: A Tractable Methodology to Simulate Scaled GPU Workloads-Reference-Cited by-同舟云学术

Principal Kernel Analysis: A Tractable Methodology to Simulate Scaled GPU Workloads

Published:2021-10-17 Issue: Volume: Page:
ISSN:
Container-title:MICRO-54: 54th Annual IEEE/ACM International Symposium on Microarchitecture
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Author:

Avalos Baddouh Cesar¹,Khairy Mahmoud¹,Green Roland N.²,Payer Mathias³,Rogers Timothy G.¹

Affiliation:

1. Purdue University, United States

2. Cerebras Systems Inc., United States

3. EPFL, Switzerland

Funder

European Research Council

Defense Advanced Research Projects Agency

SRC/DARPA JUMP

NSF (National Science Foundation)

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3466752.3480100

Reference67 articles.

1. Visualizing complex dynamics in many-core accelerator architectures

2. MCM-GPU

3. Cesar Avalos. 2021. Micro2021 - Artifact - Principal Kernel Analysis Github Repo. https://github.com/cesar-avalos3/micro-2021-artifact Cesar Avalos. 2021. Micro2021 - Artifact - Principal Kernel Analysis Github Repo. https://github.com/cesar-avalos3/micro-2021-artifact

4. Cesar Avalos. 2021. Micro2021 - Artifact - Principal Kernel Analysis Zenodo Repo. https://doi.org/10.5281/zenodo.5150378 Cesar Avalos. 2021. Micro2021 - Artifact - Principal Kernel Analysis Zenodo Repo. https://doi.org/10.5281/zenodo.5150378

5. Baidu. 2017. DeepBench: Benchmarking Deep Learning Operations on Different Hardware. https://github.com/baidu-research/DeepBench Baidu. 2017. DeepBench: Benchmarking Deep Learning Operations on Different Hardware. https://github.com/baidu-research/DeepBench

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