Computer Architecture for Scientists

Principles and Performance

Inbunden, Engelska, 2022

859 kr

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The dramatic increase in computer performance has been extraordinary, but not for all computations: it has key limits and structure. Software architects, developers, and even data scientists need to understand how exploit the fundamental structure of computer performance to harness it for future applications. Ideal for upper level undergraduates, Computer Architecture for Scientists covers four key pillars of computer performance and imparts a high-level basis for reasoning with and understanding these concepts: Small is fast - how size scaling drives performance; Implicit parallelism - how a sequential program can be executed faster with parallelism; Dynamic locality - skirting physical limits, by arranging data in a smaller space; Parallelism - increasing performance with teams of workers. These principles and models provide approachable high-level insights and quantitative modelling without distracting low-level detail. Finally, the text covers the GPU and machine-learning accelerators that have become increasingly important for mainstream applications.

Produktinformation

Utgivningsdatum2022-03-10
Mått174 x 250 x 16 mm
Vikt640 g
FormatInbunden
SpråkEngelska
Antal sidor264
FörlagCambridge University Press
ISBN9781316518533

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Andrew A. Chien is William Eckhardt Professor at the University of Chicago, Director of the CERES Center for Unstoppable Computing, and a Senior Scientist at Argonne National Laboratory. Since 2017, he has served as Editor-in-Chief of the Communications of the ACM. He is currently a member of the National Science Foundation's CISE Directorate Advisory Board. Chien is a global research leader in parallel computing, computer architecture, clusters, and cloud computing, and has received numerous awards for his research. In 1994 he was named a National Science Foundation Young Investigator. Dr. Chien served as Vice President of Research at Intel Corporation from 2005-2010, and on advisory boards for the National Science Foundation, Department of Energy, Japan RWCP, and distinguished universities such as Stanford, UC Berkeley, EPFL, and the University of Washington. From 1998-2005, he was SAIC Chair Professor at UCSD, and prior to that, a professor at the University of Illinois. Dr. Chien is a Fellow of the ACM, Fellow of the IEEE, and Fellow of the AAAS, and earned his PhD, MS, and BS from the Massachusetts Institute of Technology.

Preface; 1. Computing and the transformation of society; 2. Instruction sets, software, and instruction execution; 3. Processors: small is fast and scaling; 4. Sequential abstraction, but parallel implementation; 5. Memories: exploiting dynamic locality; 6. The general-purpose computer; 7. Beyond sequential: parallelism in multi-core and the Cloud; 8. Accelerators: customized architectures for performance; 9. Computing performance: past, present, and future; References, Index.

'Andrew Chien's Computer Architecture for Scientists: Principles and Practice is a timely and much-needed treatment of how computer architecture impacts the scalability and performance of the computing systems and the data-driven processes that operate at the upper levels of the software stack. Aimed at software engineers and data scientists, this book provides a holistic and principled coverage of technology-agnostic concepts that govern the interplay between hardware capabilities and software performance. Understanding this interplay is crucial as it allows practitioners not only to reason about the performance of the systems they develop, but in fact to design these systems in a way that leverages the architectural features of the hardware systems on which they are built.' Azer Bestavros, Associate Provost for Computing and Data Sciences, Boston University