Transactional Memory

James R. Larus · Ravi Rajwar

2022년 12월 · Springer Nature

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The advent of multicore processors has renewed interest in the idea of incorporating transactions into the programming model used to write parallel programs. This approach, known as transactional memory, offers an alternative, and hopefully better, way to coordinate concurrent threads. The ACI (atomicity, consistency, isolation) properties of transactions provide a foundation to ensure that concurrent reads and writes of shared data do not produce inconsistent or incorrect results. At a higher level, a computation wrapped in a transaction executes atomically – either it completes successfully and commits its result in its entirety or it aborts. In addition, isolation ensures the transaction produces the same result as if no other transactions were executing concurrently. Although transactions are not a parallel programming panacea, they shift much of the burden of synchronizing and coordinating parallel computations from a programmer to a compiler, runtime system, and hardware. The challenge for the system implementers is to build an efficient transactional memory infrastructure. This book presents an overview of the state of the art in the design and implementation of transactional memory systems, as of early summer 2006.

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James Larus is a Research Area Manager for programming languages and tools at Microsoft Research. He manages the Advanced Compiler Technology, Human Interaction in Programming, Runtime Analysis and Design, and Software Reliability Research groups and co-lead the Singularity research project. He joined Microsoft Research as a Senior Researcher in 1998 to start and, for five years, lead the Software Productivity Tools (SPT) group, which was one of the most innovative and productive groups in the areas of program analysis and programming tools. Before joining Microsoft, Larus was an Assistant and Associate Professor at the University of Wisconsin-Madison, where he co-led the Wisconsin Wind Tunnel research project with Professors Mark Hill and David Wood. This DARPA and NSF-funded project investigated new approaches to simulating, building, and programming parallel shared-memory computers. In addition, Larus's research covered a number of areas: new and efficient techniques for measuring and recording executing programs' behavior, tools for analyzing and manipulating compiled and linked programs, programming languages, tools for verifying program correctness, compiler analysis and optimization, and custom cache coherence protocols. Larus received a PhD from the University of California at Berkeley in 1989, and an AB from Harvard in 1980. Ravi Rajwar is a researcher in the Corporate Technology Group at Intel Corporation. His research interests include theoretical and practical aspects of computer architecture. Most recently, he has investigated resource-efficient microprocessors and architectural support for improving programmability of parallel software. Rajwar received a PhD from the University of Wisconsin-Madison in 2002, a MS from the University of Wisconsin-Madison in 1998, and a BE from the University of Roorkee, India, in 1994, all in Computer Science.