A Quantitative Analysis and Guidelines of Data Streaming Accelerator in Modern Intel Xeon Scalable Processors-Reference-Cited by-同舟云学术

A Quantitative Analysis and Guidelines of Data Streaming Accelerator in Modern Intel Xeon Scalable Processors

Published:2024-04-27 Issue: Volume:4 Page:37-54
ISSN:
Container-title:Proceedings of the 29th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, Volume 2
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Author:

Kuper Reese¹^ORCID,Jeong Ipoom²^ORCID,Yuan Yifan³^ORCID,Wang Ren⁴^ORCID,Ranganathan Narayan⁵^ORCID,Rao Nikhil⁵^ORCID,Hu Jiayu⁶^ORCID,Kumar Sanjay⁴^ORCID,Lantz Philip⁴^ORCID,Kim Nam Sung⁷^ORCID

Affiliation:

1. University of Illinois at Urbana Champaign, Urbana, Illinois, United States of America

2. University of Illinois Urbana-Champaign, Urbana, Illinois, USA

3. Intel Labs, Hillsboro, Oregon, United States of America

4. Intel Labs, Hillsboro, Oregon, USA

5. Intel Labs, Bangalore, India

6. Tencent, Shanghai, China

7. UIUC, Urbana, Illinois, United States of America

Funder

Intel Corporation

Semiconductor Research Corporation

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3620665.3640401

Reference84 articles.

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4. Mohammad Alian, Yifan Yuan, Jie Zhang, Ren Wang, Myoungsoo Jung, and Nam Sung Kim. Data direct I/O characterization for future I/O system exploration. In 2020 IEEE International Symposium on Performance Analysis of Systems and Software, (ISPASS'20), 2020.

5. Facilitating efficient synchronization of asymmetric threads on hyper-threaded processors

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