English | 2020 | ISBN-13 : 978-1681739847 | 144 Pages | True PDF | 10.21 MB
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 strats 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- 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 strats and identify areas for future work, based on optimized implementation strats, opportune extensions to existing work, and ambitious long term possibilities. Taken together, these strats and techniques present a promising future for increasingly automated computer architecture designs.
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