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AI for computer architecture : = principles, practice, and prospects /

Record Type:	Language materials, printed : Monograph/item
Title/Author:	AI for computer architecture :/ Lizhong Chen, Drew Penney, Daniel Jiménez.
Reminder of title:	principles, practice, and prospects /
Author:	Chen, Lizhong.
other author:	Penney, Drew.
Published:	[San Rafael, Calif.] :Morgan & Claypool, : c2021.,
Description:	xvii, 124 p. :ill. ; : 24 cm.;
Subject:	Computer architecture. -
ISBN:	9781681739847 (pbk.) :

AI for computer architecture : = principles, practice, and prospects /
Chen, Lizhong.

AI for computer architecture :principles, practice, and prospects /Lizhong Chen, Drew Penney, Daniel Jiménez. - [San Rafael, Calif.] :Morgan & Claypool,c2021. - xvii, 124 p. :ill. ;24 cm. - Synthesis lectures on computer architecture,#551935-3235 ;.

Includes bibliographical references (p. 103-121).

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.

ISBN: 9781681739847 (pbk.) :NT1497

Nat. Bib. Agency Control No.: 020251065UkSubjects--Topical Terms:

528145
Computer architecture.

Dewey Class. No.: 006.3

AI for computer architecture : = principles, practice, and prospects /
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003 OCoLC
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008 220831s2021 caua b 000 0 eng d
016 7 $a 020251065 $2 Uk
020 $a 9781681739847 (pbk.) : $c NT1497
020 $a 9781681739861 (cloth)
020 $z 9781681739854 (ebook)
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035 $a 1224299893
040 $a YDX $b eng $c YDX $d YDX $d STF $d OCLCO $d OCLCF $d YDXIT $d OCLCO $d OSU $d OCLCO $d UKMGB $d OCLCO $d OCLCQ $d XII $d NFU
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100 1 $a Chen, Lizhong. $3 1370988
245 1 0 $a AI for computer architecture : $b principles, practice, and prospects / $c Lizhong Chen, Drew Penney, Daniel Jiménez.
260 # $a [San Rafael, Calif.] : $b Morgan & Claypool, $c c2021.
300 $a xvii, 124 p. : $b ill. ; $c 24 cm.
490 0 $a Synthesis lectures on computer architecture, $x 1935-3235 ; $v #55
504 $a Includes bibliographical references (p. 103-121).
520 # $a 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.
650 # 0 $a Computer architecture. $3 528145
650 # 0 $a Artificial intelligence. $3 559380
650 # 0 $a Machine learning. $3 561253
700 1 # $a Penney, Drew. $3 1370989
700 1 # $a Jiménez, Daniel, $d 1969- $3 1370990