Evaluating Emerging AI/ML Accelerators: IPU, RDU, and NVIDIA/AMD GPUs-Reference-Cited by-同舟云学术

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Evaluating Emerging AI/ML Accelerators: IPU, RDU, and NVIDIA/AMD GPUs

Published:2024-05-07 Issue: Volume: Page:14-20
ISSN:
Container-title:Companion of the 15th ACM/SPEC International Conference on Performance Engineering
language:
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Author:

Peng Hongwu¹^ORCID,Ding Caiwen¹^ORCID,Geng Tong²^ORCID,Choudhury Sutanay³^ORCID,Barker Kevin³^ORCID,Li Ang³^ORCID

Affiliation:

1. University of Connecticut, Storrs, CT, USA

2. University of Rochester, Rochester, NY, USA

3. Pacific Northwest National Laboratory, Richland, WA, USA

Funder

Department of Energy Office of Science

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3629527.3651428

Reference29 articles.

1. Nvidia Corporation. [n.,d.] a. CUDA C Programming Guide. Retrived from https://docs.nvidia.com/cuda/cuda-c-programming-guide/index.html. Accessed: 2022, Oct. 30th.

2. Nvidia Corporation. [n. d.] b. NVIDIA A100 Tensor Core GPU Architecture unprecedented acceleration at every scale. Retrived from https://www.nvidia.com/content/dam/en-zz/Solutions/Data-Center/nvidia-ampere-architecture-whitepaper.pdf. Accessed: 2022 Oct. 30th.

3. Nvidia Corporation. [n.,d.] c. Nvidia Tesla V100 GPU Architecture, The World's Most Advanced Data Center GPU. Retrived from https://images.nvidia.com/content/volta-architecture/pdf/volta-architecture-whitepaper.pdf. Accessed: 2022, Oct. 30th.

4. Sambanova System Corporation. [n.,d.] d. SambaFlow - SambaNova Systems. Retrived from https://sambanova.ai/wp-content/uploads/2021/04/SambaNova_SambaFlow_Datasheet_English.pdf. Accessed: 2022, Oct. 30th.

5. The university of Florida sparse matrix collection

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