AI for computer architecture : principles, practice, and prospects / Lizhong Chen, Drew Penney, Daniel Jiménez.
- 作者： Chen, Lizhong.
- 其他作者：
- 其他題名：
- Synthesis lectures in computer architecture ;
- 出版： [San Rafael, CA] : Morgan & Claypool Publishers 2021.
- 叢書名： Synthesis lectures on computer architecture ;#55
- 主題： Computer architecture. , Artificial intelligence. , Machine learning.
- ISBN： 9781681739847 (pbk.) :: USD49.95 、 1681739844 (pbk.) 、 9781681739861 (hbk.) 、 1681739860 (hbk.)
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讀者標籤：
- 系統號： 005272100 | 機讀編目格式
館藏資訊
Artificial intelligence has already enabled pivotal advances in diverse fields, yet its impact on computer architecture has only just begun. In particular, recent work has explored broader application to the design, optimization, and simulation of computer architecture. Notably, machine-learning-based strategies often surpass prior state-of-the-art analytical, heuristic, and human-expert approaches. This book reviews the application of machine learning in system-wide simulation and run-time optimization, and in many individual components such as caches/memories, branch predictors, networks-on-chip, and GPUs. The book further analyzes current practice to highlight useful design strategies and identify areas for future work, based on optimized implementation strategies, opportune extensions to existing work, and ambitious long term possibilities. Taken together, these strategies and techniques present a promising future for increasingly automated computer architecture designs.