Automatic Parallelization: New Approaches to Code Generation, Data Distribution, and Performance Prediction

Springer Science & Business Media
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Distributed-memory multiprocessing systems (DMS), such as Intel's hypercubes, the Paragon, Thinking Machine's CM-5, and the Meiko Computing Surface, have rapidly gained user acceptance and promise to deliver the computing power required to solve the grand challenge problems of Science and Engineering. These machines are relatively inexpensive to build, and are potentially scalable to large numbers of processors. However, they are difficult to program: the non-uniformity of the memory which makes local accesses much faster than the transfer of non-local data via message-passing operations implies that the locality of algorithms must be exploited in order to achieve acceptable performance. The management of data, with the twin goals of both spreading the computational workload and minimizing the delays caused when a processor has to wait for non-local data, becomes of paramount importance. When a code is parallelized by hand, the programmer must distribute the program's work and data to the processors which will execute it. One of the common approaches to do so makes use of the regularity of most numerical computations. This is the so-called Single Program Multiple Data (SPMD) or data parallel model of computation. With this method, the data arrays in the original program are each distributed to the processors, establishing an ownership relation, and computations defining a data item are performed by the processors owning the data.
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Springer Science & Business Media
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Published on
Dec 6, 2012
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Computers / Computer Science
Computers / Information Technology
Computers / Information Theory
Computers / Programming / Algorithms
Language Arts & Disciplines / Library & Information Science / General
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Jimmy Soni
Winner of the Neumann Prize for the History of Mathematics

**Named a best book of the year by Bloomberg and Nature**

**'Best of 2017' by The Morning Sun**

"We owe Claude Shannon a lot, and Soni & Goodman’s book takes a big first step in paying that debt." —San Francisco Review of Books

"Soni and Goodman are at their best when they invoke the wonder an idea can instill. They summon the right level of awe while stopping short of hyperbole." —Financial Times

"Jimmy Soni and Rob Goodman make a convincing case for their subtitle while reminding us that Shannon never made this claim himself." —The Wall Street Journal

"Soni and Goodman have done their research...A Mind at Play reveals the remarkable human behind some of the most important theoretical and practical contributions to the information age." —Nature

"A Mind at Play shows us that you don't need to be a genius to learn from a genius. Claude Shannon's inventive, vibrant life demonstrates how vital the act of play can be to making the most of work." —Inc.

“A charming account of one of the twentieth century’s most distinguished scientists…Readers will enjoy this portrait of a modern-day Da Vinci.” —Fortune

In their second collaboration, biographers Jimmy Soni and Rob Goodman present the story of Claude Shannon—one of the foremost intellects of the twentieth century and the architect of the Information Age, whose insights stand behind every computer built, email sent, video streamed, and webpage loaded. Claude Shannon was a groundbreaking polymath, a brilliant tinkerer, and a digital pioneer. He constructed the first wearable computer, outfoxed Vegas casinos, and built juggling robots. He also wrote the seminal text of the digital revolution, which has been called “the Magna Carta of the Information Age.” In this elegantly written, exhaustively researched biography, Soni and Goodman reveal Claude Shannon’s full story for the first time. With unique access to Shannon’s family and friends, A Mind at Play brings this singular innovator and always playful genius to life.
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