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Books on the topic 'In-memory compute'

Author: Grafiati
Published: 6 September 2023

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1

Memory storage patterns in parallel processing. Boston: Kluwer Academic, 1987.

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2

Miller, R. K. Neural networks: Implementing associative memory models in neurocomputers. Lilburn, GA: Fairmont Press, 1990.

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3

Miller, Richard Kendall. Neural networks: Implementing associative memory models in neurocomputers. Lilburn, GA: Fairmont Press, 1990.

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4

Kanerva, Pentti. Parallel structures in human and computer memory. Moffett Field, Calif: Research Institute for Advanced Computer Science, 1986.

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5

Donovan, Kevin. Performance of shared memory in a parallel computer. New York: Courant Institute of Mathematical Sciences, New York University, 1990.

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6

Mace, Mary E. Memory Storage Patterns in Parallel Processing. Boston, MA: Springer US, 1987.

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7

David, Hutchison. Mathematical Methods in Computer Science: Essays in Memory of Thomas Beth. Berlin, Heidelberg: Springer Berlin Heidelberg, 2008.

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8

Dickey, Susan. Designing VLSI network nodes to reduce memory traffic in a shared memory parallel computer. New York: Courant Institute of Mathematical Sciences, New York University, 1986.

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9

Cheriton, David R. The unified management of memory in the V distributed system. Stanford, Calif: Dept. of Computer Science, Stanford University, 1988.

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10

Nikil, Dutt, and Nicolau Alexandru, eds. Memory issues in embedded systems-on-chip: Optimizations and exploration. Boston: Kluwer Academic, 1999.

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11

Memory management in a multimedia world. Corte Madera, Calif: Waite Group Press, 1994.

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12

Feygin, G. Survivor sequence memory management in Viterbi Decoders. Toronto: Computer Systems Research Institute, University of Toronto, 1991.

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13

Plattner, Hasso. In-Memory Data Management: Technology and Applications. 2nd ed. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012.

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14

Memory as a programming concept in C and C++. Cambridge: Cambridge University Press, 2004.

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15

Panda, Preeti Ranjan. Memory Issues in Embedded Systems-on-Chip: Optimizations and Exploration. Boston, MA: Springer US, 1999.

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16

A, Chernenko V., ed. Advances in shape memory materials: Magnetic shape memory alloys: special topic volume, invited papers only. Stafa-Zurich, Switzerland: Trans Tech Publications, 2008.

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17

1969-, Zeier Alexander, and SpringerLink (Online service), eds. In-Memory Data Management: An Inflection Point for Enterprise Applications. Berlin, Heidelberg: Springer-Verlag Berlin Heidelberg, 2011.

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18

C, Cohen Gerald, and Langley Research Center, eds. Interpreter composition issues in the formal verification of a processor-memory module. Hampton, Va: National Aeronautics and Space Administration, Langley Research Center, 1994.

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19

Kent, Fuchs W., and United States. National Aeronautics and Space Administration., eds. Ensuring correct rollback recovery in distributed shared memory systems. [Washington, DC: National Aeronautics and Space Administration, 1995.

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20

Voronkov, Andrei. Programming Logics: Essays in Memory of Harald Ganzinger. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013.

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21

Tartalja, Igor. The cache coherence problem in shared-memory multiprocessors: Software solutions. Los Alamitos, Calif: IEEE Computer Society Press, 1996.

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22

Structural econometrics: Essays in methodology and applications in memory of Sanghamitra Das. New Delhi: Oxford University Press, 2010.

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23

Dutta, Bhaskar, and Sanghamitra Das. Structural econometrics: Essays in methodology and applications in memory of Sanghamitra Das. New Delhi: Oxford University Press, 2010.

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24

Aydinian, Harout. Information Theory, Combinatorics, and Search Theory: In Memory of Rudolf Ahlswede. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013.

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25

Bonacina, Maria Paola. Automated Reasoning and Mathematics: Essays in Memory of William W. McCune. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013.

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26

Commission, United States International Trade. In the matter of certain memory devices with increased capacitance and products containing same. Washington, DC: U.S. International Trade Commission, 1996.

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27

Wästlund, Erik. Experimental studies of human-computer interaction: Working on memory and mental workload in complex cognition. Gothenburg: Dept. of Psychology, Gothenburg University, Sweden, 2007.

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28

Banerjee, Writam. Nanocrystals in Nonvolatile Memory. Jenny Stanford Publishing, 2018.

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29

Banerjee, Writam. Nanocrystals in Nonvolatile Memory. Jenny Stanford Publishing, 2018.

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30

Memory Storage Patterns in Parallel Processing. Springer, 2014.

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31

(Editor), Oded Goldreich, Arnold L. Rosenberg (Editor), and Alan L. Selman (Editor), eds. Theoretical Computer Science: Essays in Memory of Shimon Even (Lecture Notes in Computer Science). Springer, 2006.

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32

Nanocrystals in Non-Volatile Memory. Taylor & Francis Group, 2018.

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33

Goldreich, Oded, Alan L. Selman, and Arnold L. Rosenberg. Theoretical Computer Science: Essays in Memory of Shimon Even. Springer London, Limited, 2006.

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34

Korotkevitch, Dmitri. Expert SQL Server in-Memory OLTP. Apress, 2015.

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35

Korotkevitch, Dmitri. Expert SQL Server In-Memory OLTP. Apress, 2017.

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36

Kenner, Richard, Allan Gottlieb, and Susan Dickey. Designing VLSI Network Nodes to Reduce Memory Traffic in a Shared Memory Parallel Computer. Creative Media Partners, LLC, 2018.

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37

Case, Andrew, Aaron Walters, Michael Hale Ligh, and Jamie Levy. Art of Memory Forensics: Detecting Malware and Threats in Windows, Linux, and Mac Memory. Wiley & Sons, Incorporated, John, 2014.

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38

Case, Andrew, Aaron Walters, Michael Hale Ligh, and Jamie Levy. Art of Memory Forensics: Detecting Malware and Threats in Windows, Linux, and Mac Memory. Wiley & Sons, Incorporated, John, 2014.

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39

Alessandrini, Victor. Shared Memory Application Programming: Concepts and Strategies in Multicore Application Programming. Elsevier Science & Technology Books, 2015.

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40

Alessandrini, Victor. Shared Memory Application Programming: Concepts and Strategies in Multicore Application Programming. Elsevier Science & Technology Books, 2015.

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41

Stenström, Per, Wood David A, Somayeh Sardashti, and Angelos Arelakis. Primer on Compression in the Memory Hierarchy. Morgan & Claypool Publishers, 2015.

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42

Primer on Compression in the Memory Hierarchy. Springer International Publishing AG, 2015.

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43

Stenström, Per, Wood David A, Somayeh Sardashti, and Angelos Arelakis. Primer on Compression in the Memory Hierarchy. Morgan & Claypool Publishers, 2015.

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44

Petersen, Wesley, and Peter Arbenz. Introduction to Parallel Computing. Oxford University Press, 2004. http://dx.doi.org/10.1093/oso/9780198515760.001.0001.

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In the last few years, courses on parallel computation have been developed and offered in many institutions in the UK, Europe and US as a recognition of the growing significance of this topic in mathematics and computer science. There is a clear need for texts that meet the needs of students and lecturers and this book, based on the author's lecture at ETH Zurich is an ideal practical student guide to scientific computing on parallel computers working up from a hardware instruction level, to shared memory machines and finally to distributed memory machines. Aimed at advanced undergraduate and graduate students in applied mathematics, computer science and engineering, subjects covered include linear algebra, fast Fourier transform, and Monte-Carlo simulations, including examples in C and in some cases Fortran. This book is also ideal for practitioners and programmers.
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45

Panda, Preeti Ranjan, Nikil D. Dutt, and Alexandru Nicolau. Memory Issues in Embedded Systems-On-Chip: Optimizations and Exploration. Springer, 1998.

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46

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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47

Case, Andrew, Aaron Walters, Michael Hale Ligh, and Jamie Levy. Art of Memory Forensics: Detecting Malware and Threats in Windows, Linux, and Mac Memory. Wiley & Sons, Incorporated, John, 2014.

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48

Kolodner, Janet L. Retrieval and Organizational Strategies in Conceptual Memory: A Computer Model. Taylor & Francis Group, 2014.

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49

Retrieval and Organizational Strategies in Conceptual Memory: A Computer Model. Taylor & Francis Group, 2014.

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50

Kolodner, Janet L. Retrieval and Organizational Strategies in Conceptual Memory: A Computer Model. Taylor & Francis Group, 2016.

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