建國科技大學圖書館 |

語系: 繁體中文

說明(常見問題)

圖書館個人資料蒐集告知聲明

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Workload modeling for computer syste...

Feitelson, Dror G.

Workload modeling for computer systems performance evaluation

紀錄類型:	書目-語言資料,印刷品 : 單行本
作者:	FeitelsonDror G.,
出版地:	New York, NY, USA
出版者:	Cambridge University Press;
出版年:	c2015.
面頁冊數:	xv, 551 p.ill. (chiefly col.) : 27 cm.;
標題:	Electronic digital computers - Evaluation. -
標題:	Electronic digital computers - Workload -
摘要註:	"Reliable performance evaluations require the use of representative workloads. This is no easy task since modern computer systems and their workloads are complex, with many interrelated attributes and complicated structures. Experts often use sophisticated mathematics to analyze and describe workload models, making these models difficult for practitioners to grasp. This book aims to close this gap by emphasizing the intuition and the reasoning behind the definitions and derivations related to the workload models. It provides numerous examples from real production systems, with hundreds of graphs. Using this book, readers will be able to analyze collected workload data and clean it if necessary, derive statistical models that include skewed marginal distributions and correlations, and consider the need for generative models and feedback from the system. The descriptive statistics techniques covered are also useful for other domains"--Provided by publisher.
ISBN:	9781107078239
內容註:	Machine generated contents note: 1. Introduction; 2. Workload data; 3. Statistical distributions; 4. Fitting distributions to data; 5. Heavy tails; 6. Correlations in workloads; 7. Self-similarity and long-range dependence; 8. Hierarchical generative models; 9. Case studies; 10. Summary and outlook.

Workload modeling for computer systems performance evaluation
Feitelson, Dror G.

Workload modeling for computer systems performance evaluation / Dror G. Feitelson. - New York, NY, USA : Cambridge University Press, c2015.. - xv, 551 p. ; ill. (chiefly col.) ; 27 cm..
Machine generated contents note: 1. Introduction; 2. Workload data; 3. Statistical distributions; 4. Fitting distributions to data; 5. Heavy tails; 6. Correlations in workloads; 7. Self-similarity and long-range dependence; 8. Hierarchical generative models; 9. Case studies; 10. Summary and outlook..
Includes bibliographical references and index..
ISBN 9781107078239ISBN 1107078237
Electronic digital computersElectronic digital computers -- Evaluation. -- Workload

Workload modeling for computer systems performance evaluation
LDR:01892cam a2200205 450 001 390441
010 1 $a 9781107078239 $b hbk. $d NT1708
010 1 $a 1107078237 $b hbk.
100 $a 20140617d2015 k y0engy50 b
101 0 $a eng
102 $a us $b ny
105 $a a a 001yy
200 1 $a Workload modeling for computer systems performance evaluation $f Dror G. Feitelson.
210 $a New York, NY, USA $c Cambridge University Press $d c2015.
215 1 $a xv, 551 p. $c ill. (chiefly col.) $d 27 cm.
320 $a Includes bibliographical references and index.
327 0 $a Machine generated contents note: 1. Introduction; 2. Workload data; 3. Statistical distributions; 4. Fitting distributions to data; 5. Heavy tails; 6. Correlations in workloads; 7. Self-similarity and long-range dependence; 8. Hierarchical generative models; 9. Case studies; 10. Summary and outlook.
330 $a "Reliable performance evaluations require the use of representative workloads. This is no easy task since modern computer systems and their workloads are complex, with many interrelated attributes and complicated structures. Experts often use sophisticated mathematics to analyze and describe workload models, making these models difficult for practitioners to grasp. This book aims to close this gap by emphasizing the intuition and the reasoning behind the definitions and derivations related to the workload models. It provides numerous examples from real production systems, with hundreds of graphs. Using this book, readers will be able to analyze collected workload data and clean it if necessary, derive statistical models that include skewed marginal distributions and correlations, and consider the need for generative models and feedback from the system. The descriptive statistics techniques covered are also useful for other domains"--Provided by publisher.
606 $a Electronic digital computers $x Evaluation. $2 lc $3 36173
606 $a Electronic digital computers $x Workload $x Mathematical models. $2 lc $3 381933
676 $a 004 $v 23
680 $a QA76.9.E94 $b F43 2015
700 1 $a Feitelson $b Dror G. $3 381932
801 0 $a cw $b CTU $c 20200710 $g AACR2