GPU Instruction Hotspots Detection Based on Binary Instrumentation Approach

Author:

Gorshkov Anton V.ORCID,Berezalsky Michael,Fedorova JuliaORCID,Levit-Gurevich Konstantin,Itzhaki NoamORCID

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computational Theory and Mathematics,Hardware and Architecture,Theoretical Computer Science,Software

Cited by 9 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. DrGPUM: Guiding Memory Optimization for GPU-Accelerated Applications;Proceedings of the 28th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, Volume 3;2023-03-25

2. A Hotspot-Driven Semi-automated Competitive Analysis Framework for Identifying Compiler Key Optimizations;Proceedings of the 32nd ACM SIGPLAN International Conference on Compiler Construction;2023-02-17

3. Flexible Binary Instrumentation Framework to Profile Code Running on Intel GPUs;2022 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS);2022-05

4. Profiling Intel Graphics Architecture with Long Instruction Traces;2022 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS);2022-05

5. ValueExpert: exploring value patterns in GPU-accelerated applications;Proceedings of the 27th ACM International Conference on Architectural Support for Programming Languages and Operating Systems;2022-02-22

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