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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
AI for Computer Architecture: Principles, Practice, and Prospects

AI for Computer Architecture: Principles, Practice, and Prospects

Chen, Lizhong
Penney, Drew
Jiménez, Daniel

Paperback

Series: Synthesis Lectures on Computer Architecture

General Computers

ISBN10: 3031006429
ISBN13: 9783031006425
Publisher: Springer Nature
Published: Nov 6 2020
Pages: 124
Weight: 0.57
Height: 0.31 Width: 7.50 Depth: 9.25
Language: English
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.

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