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Books on the topic 'Computation-in-memory'

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Author: Grafiati

Published: 10 December 2022

Last updated: 28 January 2023

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1

Nishimura, Naomi. Asynchrony in shared memory parallel computation. Toronto: University of Toronto, Dept. of Computer Science, 1991.

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2

1903-1995, Church Alonzo, Anderson C. Anthony, and Zelëny Michael, eds. Logic, meaning, and computation: Essays in memory of Alonzo Church. Dordrecht: Kluwer Academic Publishers, 2001.

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3

O'Donnell, Timothy J. Productivity and reuse in language: A theory of linguistic computation and storage. Cambridge, Massachusetts: The MIT Press, 2015.

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4

Mihai, Oltean, and SpringerLink (Online service), eds. Optical Supercomputing: 4th International Workshop, OSC 2012, in Memory of H. John Caulfield, Bertinoro, Italy, July 19-21, 2012. Revised Selected Papers. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013.

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5

Nishimura, Naomi *. Asynchrony in shared memory parallel computation. 1991.

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6

Zelëny, Michael, and C. Anthony Anderson. Logic, Meaning and Computation: Essays in Memory of Alonzo Church. Springer London, Limited, 2012.

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7

1903-1995, Church Alonzo, Anderson C. Anthony, and Zelëny Michael, eds. Logic, meaning, and computation: Essays in memory of Alonzo Church. Dordrecht: Kluwer Academic Publishers, 2001.

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8

Anderson, C. Anthony. Logic, Meaning and Computation: Essays in Memory of Alonzo Church. Ingramcontent, 2012.

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9

Logic, Meaning and Computation : Essays in Memory of Alonzo Church (Synthese Library, 305) (Synthese Library). Springer, 2001.

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10

Launay, Jean-Pierre, and Michel Verdaguer. Electrons in Molecules. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198814597.001.0001.

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The book treats in a unified way electronic properties of molecules (magnetic, electrical, photophysical), culminating with the mastering of electrons, i.e. molecular electronics and spintronics and molecular machines. Chapter 1 recalls basic concepts. Chapter 2 describes the magnetic properties due to localized electrons. This includes phenomena such as spin cross-over, exchange interaction from dihydrogen to extended molecular magnetic systems, and magnetic anisotropy with single-molecule magnets. Chapter 3 is devoted to the electrical properties due to moving electrons. One considers first electron transfer in discrete molecular systems, in particular in mixed valence compounds. Then, extended molecular solids, in particular molecular conductors, are described by band theory. Special attention is paid to structural distortions (Peierls instability) and interelectronic repulsions in narrow-band systems. Chapter 4 treats photophysical properties, mainly electron transfer in the excited state and its applications to photodiodes, organic light emitting diodes, photovoltaic cells and water photolysis. Energy transfer is also treated. Photomagnetism (how a photonic excitation modifies magnetic properties) is introduced. Finally, Chapter 5 combines the previous knowledge for three advanced subjects: first molecular electronics in its hybrid form (molecules connected to electrodes acting as wires, diodes, memory elements, field-effect transistors) or in the quantum computation approach. Then, molecular spintronics, using, besides the charge, the spin of the electron. Finally the theme of molecular machines is presented, with the problem of the directionality control of their motion.

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11

Publishing, Benton Harvey. I Have a Memory Like an Elephant in Fact: Cute Elephant - Graph Paper, Graph Paper Pad, Graphing Paper, Computation Pads, Drafting Paper, Blueprint Paper, Quad Rised 5x5, Grid Paper for Math and Science Student. Independently Published, 2020.

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12

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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13

Busemeyer, Jerome R., Zheng Wang, James T. Townsend, and Ami Eidels, eds. The Oxford Handbook of Computational and Mathematical Psychology. Oxford University Press, 2015. http://dx.doi.org/10.1093/oxfordhb/9780199957996.001.0001.

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A comprehensive and authoritative review on most important developments in computational and mathematical psychology that have impacted many other fields in past decades. Written in tutorial style by leading scientists in each topic area, with an emphasis on examples and applications. Each chapter is self-contained and aims to engage readers with various levels of modeling experience. The Handbook covers the key developments in elementary cognitive mechanisms (e.g., signal detection, information processing, reinforcement learning), basic cognitive skills (e.g., perceptual judgment, categorization, episodic memory), higher-level cognition (e.g., Bayesian cognition, decision making, semantic memory, shape perception), modeling tools (e.g., Bayesian estimation and other new model comparison methods), and emerging new directions (e.g., neurocognitive modeling, applications to clinical psychology, quantum cognition) in computation and mathematical psychology. The chapters were written for a typical graduate student in virtually any area of psychology, cognitive science, and related social and behavioral sciences, such as consumer behavior and communication. We also expect it to be useful for readers ranging from advanced undergraduate students to experienced faculty members and researchers. Beyond being a handy reference book, it should be beneficial as a textbook for self-teaching, and for graduate level (or advanced undergraduate level) courses in computational and mathematical psychology.

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14

Nuerk, Hans-Christoph, Korbinian Moeller, and Klaus Willmes. Multi-digit Number Processing. Edited by Roi Cohen Kadosh and Ann Dowker. Oxford University Press, 2014. http://dx.doi.org/10.1093/oxfordhb/9780199642342.013.021.

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Only recently the focus in numerical cognition research has considered multi-digit number processing as a relatively new and yet understudied domain in mathematical cognition. In this chapter: (i) we argue that single-digit number processing is not sufficient to understand multi-digit number processing; (ii) provide an overview on which representations and effects have been investigated for multi-digit numbers; (iii) suggest a conceptual distinction between place-identification, place-value activation, and place-value computation; (iv) identify language influences on multi-digit number processing along that conceptual distinction; and (v) argue that for numerical development indices of multi-digit number processing may be more suitable predictors of later arithmetical performance than classical single-digit measure such as the distance effect or non-numerical variables (e.g., working memory). In the final section, we summarize the important issues in multi-digit number processing, outline future directions and try to encourage readers to contribute to a new, exciting, yet understudied domain of numerical cognition.

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15

Di Ventra, Massimiliano. MemComputing. Oxford University Press, 2022. http://dx.doi.org/10.1093/oso/9780192845320.001.0001.

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From the originator of MemComputing comes the very first book on this new computing paradigm that employs time non-locality (memory) to both process and store information. The book discusses the rationale behind MemComputing, its theoretical foundations, and wide-range applicability to combinatorial optimization problems, Machine Learning, and Quantum Mechanics. The book is ideal for graduate students in Physics, Computer Science, Electrical Engineering, and Mathematics as well as researchers in both academia and industry interested in unconventional computing. The author relies on extensive margin notes, important remarks, and several artworks to better explain the main concepts and clarify all the jargon, making the book as self-contained as possible. The reader will be guided from the basic notions to the more advanced ones with a writing style that is always clear and engaging. Along the way, the reader will appreciate the advantages of this computing paradigm and the major differences that set it apart from the prevailing Turing model of computation, and even Quantum Computing.

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16

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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17

Dolev, Shlomi, and Mihai Oltean. Optical Supercomputing: 4th International Workshop, OSC 2012, in Memory of H. John Caulfield, Bertinoro, Italy, July 19-21, 2012. Revised Selected Papers. Springer, 2013.

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