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Books on the topic 'Parallel Hardware Architecture'

Author: Grafiati

Published: 4 June 2021

Last updated: 12 February 2022

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1

Pal, Singh Jaswinder, and Gupta Anoop, eds. Parallel computer architecture: A hardware/software approach. Morgan Kaufmann Publishers, 1999.

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2

Parallel processing architectures and VLSI hardware. Prentice-Hall, 1989.

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3

Hennessy, John L. Computer Organization and Design: The Hardware/Software Interface. Morgan Kaufmann, 1994.

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4

Hennessy, John L. Computer organization and design: The hardware/software interface. Morgan Kaufmann, 1994.

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5

Hennessy, John L. Computer organization and design: The hardware/software interface. Morgan Kaufmann Publishers, 1994.

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6

Hardware/software co-design for heterogeneous multi-core platforms: The hArtes toolchain. Springer, 2012.

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7

Olariu, Stephan, G. Conte, Denis Caromel, et al. Parallel and Distributed Processing: 11th IPPS/SPDP99 Workshops Held in Conjunction with the 13th International Parallel Processing Symposium and 10th Symposium on Parallel and Distributed Processing San Juan, Puerto Rico, USA, April 1216, 1999 Proceedings. Springer-Verlag, 1999.

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8

Arndt, Bode, and Dal Cin Mario 1940-, eds. Parallel computer architectures: Theory, hardware, software, applications. Springer-Verlag, 1993.

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9

Beyer, Dale A. Memory optimization for a parallel sorting hardware architecture. 1997.

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10

Gupta, Anoop, David Culler, and J. P. Singh. Parallel Computer Architecture: A Hardware/Software Approach (The Morgan Kaufmann Series in Computer Architecture and Design). Morgan Kaufmann, 1998.

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11

Bode, Arndt. Parallel Computer Architectures: Theory, Hardware, Software, Applications (Lecture Notes in Computer Science). Springer, 1993.

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12

Michael, Schlansker, and Hewlett-Packard Laboratories, eds. Achieving high levels of instruction-level parallelism with reduced hardware complexity. Hewlett-Packard Laboratories, Technical Publications Dept., 1996.

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13

Epstein, Avi. Parallel Hardware Architectures For The Life Sciences. Delft Univ Pr, 2004.

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14

Bisseling, Rob H. Parallel Scientific Computation. Oxford University Press, 2020. http://dx.doi.org/10.1093/oso/9780198788348.001.0001.

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This book explains how to use the bulk synchronous parallel (BSP) model to design and implement parallel algorithms in the areas of scientific computing and big data. Furthermore, it presents a hybrid BSP approach towards new hardware developments such as hierarchical architectures with both shared and distributed memory. The book provides a full treatment of core problems in scientific computing and big data, starting from a high-level problem description, via a sequential solution algorithm to a parallel solution algorithm and an actual parallel program written in the communication library BSPlib. Numerical experiments are presented for parallel programs on modern parallel computers ranging from desktop computers to massively parallel supercomputers. The introductory chapter of the book gives a complete overview of BSPlib, so that the reader already at an early stage is able to write his/her own parallel programs. Furthermore, it treats BSP benchmarking and parallel sorting by regular sampling. The next three chapters treat basic numerical linear algebra problems such as linear system solving by LU decomposition, sparse matrix-vector multiplication (SpMV), and the fast Fourier transform (FFT). The final chapter explores parallel algorithms for big data problems such as graph matching. The book is accompanied by a software package BSPedupack, freely available online from the author’s homepage, which contains all programs of the book and a set of test programs.

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15

Hennessy, John L., and David A. Patterson. Computer Organization and Design: The Hardware/Software Interface. 2nd ed. Morgan Kaufmann, 1997.

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16

A, Patterson David, ed. Computer Organization and Design: The Hardware/Software Interface. 2nd ed. Morgan Kaufmann Publishers, 1998.

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17

Computer Organization and Design: The Hardware/Software Interface. Morgan Kaufmann Publishers, 2009.

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18

Bertels, Koen. Hardware/Software Co-design for Heterogeneous Multi-core Platforms: The hArtes Toolchain. Springer, 2011.

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19

Mesinger, Fedor, Miodrag Rančić, and R. James Purser. Numerical Methods in Atmospheric Models. Oxford University Press, 2018. http://dx.doi.org/10.1093/acrefore/9780190228620.013.617.

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The astonishing development of computer technology since the mid-20th century has been accompanied by a corresponding proliferation in the numerical methods that have been developed to improve the simulation of atmospheric flows. This article reviews some of the numerical developments concern the ongoing improvements of weather forecasting and climate simulation models. Early computers were single-processor machines with severely limited memory capacity and computational speed, requiring simplified representations of the atmospheric equations and low resolution. As the hardware evolved and memory and speed increased, it became feasible to accommodate more complete representations of the dynamic and physical atmospheric processes. These more faithful representations of the so-called primitive equations included dynamic modes that are not necessarily of meteorological significance, which in turn led to additional computational challenges. Understanding which problems required attention and how they should be addressed was not a straightforward and unique process, and it resulted in the variety of approaches that are summarized in this article. At about the turn of the century, the most dramatic developments in hardware were the inauguration of the era of massively parallel computers, together with the vast increase in the amount of rapidly accessible memory that the new architectures provided. These advances and opportunities have demanded a thorough reassessment of the numerical methods that are most successfully adapted to this new computational environment. This article combines a survey of the important historical landmarks together with a somewhat speculative review of methods that, at the time of writing, seem to hold out the promise of further advancing the art and science of atmospheric numerical modeling.

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