GCoM-Reference-Cited by-同舟云学术

GCoM

Published:2022-06-11 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 49th Annual International Symposium on Computer Architecture
language:
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Author:

Lee Jounghoo¹,Ha Yeonan¹,Lee Suhyun¹,Woo Jinyoung²,Lee Jinho¹,Jang Hanhwi²,Kim Youngsok¹

Affiliation:

1. Yonsei University, Seoul, South Korea

2. Ajou University, Suwon, South Korea

Funder

Yonsei Signature Research Cluster Program (2022-22-0002)

National Research Foundation of Korea (NRF)

Institute of Information & communications Technology Planning & Evaluation (IITP)

Ministry of Education (MOE) of Korea

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3470496.3527384

Reference56 articles.

1. Advanced Micro Devices , Inc . 2016 . RADEON: Dissecting the Polaris Architecture. https://www.amd.com/system/files/documents/polaris-whitepaper.pdf. Advanced Micro Devices, Inc. 2016. RADEON: Dissecting the Polaris Architecture. https://www.amd.com/system/files/documents/polaris-whitepaper.pdf.

2. Johnathan Alsop , Matthew D. Sinclair , Rakesh Komuravelli , and Sarita V. Adve . 2016. GSI: A GPU Stall Inspector to Characterize the Sources of Memory Stalls for Tightly Coupled GPUs . In Proc. 2016 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS). Johnathan Alsop, Matthew D. Sinclair, Rakesh Komuravelli, and Sarita V. Adve. 2016. GSI: A GPU Stall Inspector to Characterize the Sources of Memory Stalls for Tightly Coupled GPUs. In Proc. 2016 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS).

3. Hybrid, scalable, trace-driven performance modeling of GPGPUs

4. Yehia Arafa , Abdel-Hameed A. Badawy , Gopinath Chennupati , Nandakishore Santhi , and Stephan Eidenbenz . 2019. PPT-GPU: Scalable GPU Performance Modeling . IEEE Computer Architecture Letters (CAL) 18 ( 2019 ). Yehia Arafa, Abdel-Hameed A. Badawy, Gopinath Chennupati, Nandakishore Santhi, and Stephan Eidenbenz. 2019. PPT-GPU: Scalable GPU Performance Modeling. IEEE Computer Architecture Letters (CAL) 18 (2019).

5. Cross-architecture performance prediction (XAPP) using CPU code to predict GPU performance

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