OrderLight: Lightweight Memory-Ordering Primitive for Efficient Fine-Grained PIM Computations-Reference-Cited by-同舟云学术

OrderLight: Lightweight Memory-Ordering Primitive for Efficient Fine-Grained PIM Computations

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:

Nag Anirban¹,Balasubramonian Rajeev²

Affiliation:

1. Uppsala University

2. University of Utah, United States of America

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3466752.3480103

Reference49 articles.

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3. PIM-enabled instructions

4. Soheil Bahrampour Naveen Ramakrishnan Lukas Schott and Mohak Shah. 2016. Comparative Study of Caffe Neon Theano and Torch for Deep Learning. arXiv preprint arXiv:1511.06435(2016). Soheil Bahrampour Naveen Ramakrishnan Lukas Schott and Mohak Shah. 2016. Comparative Study of Caffe Neon Theano and Torch for Deep Learning. arXiv preprint arXiv:1511.06435(2016).

5. Analyzing CUDA workloads using a detailed GPU simulator

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