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Papers presented within this volume cover a wide range of topics related to programming distributed memory machines. Distributed memory architectures, although having the potential to supply the very high levels of performance required to support future computing needs, present awkward programming problems. The major issue is to design methods which enable compilers to generate efficient distributed memory programs from relatively machine independent program specifications. This book is the compilation of papers describing a wide range of research efforts aimed at easing the task of programming distributed memory machines.
Scalable parallel systems or, more generally, distributed memory systems offer a challenging model of computing and pose fascinating problems regarding compiler optimization, ranging from language design to run time systems. Research in this area is foundational to many challenges from memory hierarchy optimizations to communication optimization. This unique, handbook-like monograph assesses the state of the art in the area in a systematic and comprehensive way. The 21 coherent chapters by leading researchers provide complete and competent coverage of all relevant aspects of compiler optimization for scalable parallel systems. The book is divided into five parts on languages, analysis, communication optimizations, code generation, and run time systems. This book will serve as a landmark source for education, information, and reference to students, practitioners, professionals, and researchers interested in updating their knowledge about or active in parallel computing.
The articles in this volume are revised versions of the best papers presented at the Fifth Workshop on Languages and Compilers for Parallel Computing, held at Yale University, August 1992. The previous workshops in this series were held in Santa Clara (1991), Irvine (1990), Urbana (1989), and Ithaca (1988). As in previous years, a reasonable cross-section of some of the best work in the field is presented. The volume contains 35 papers, mostly by authors working in the U.S. or Canada but also by authors from Austria, Denmark, Israel, Italy, Japan and the U.K.
The editors provide a review of the programming environments for parallel computers with the help of worldwide specialists in each domain. Four different domains were discussed at the workshop, and they each form a part of this book.
Parallel Language and Compiler Research in Japan offers the international community an opportunity to learn in-depth about key Japanese research efforts in the particular software domains of parallel programming and parallelizing compilers. These are important topics that strongly bear on the effectiveness and affordability of high performance computing systems. The chapters of this book convey a comprehensive and current depiction of leading edge research efforts in Japan that focus on parallel software design, development, and optimization that could be obtained only through direct and personal interaction with the researchers themselves.
Containing over 300 entries in an A-Z format, the Encyclopedia of Parallel Computing provides easy, intuitive access to relevant information for professionals and researchers seeking access to any aspect within the broad field of parallel computing. Topics for this comprehensive reference were selected, written, and peer-reviewed by an international pool of distinguished researchers in the field. The Encyclopedia is broad in scope, covering machine organization, programming languages, algorithms, and applications. Within each area, concepts, designs, and specific implementations are presented. The highly-structured essays in this work comprise synonyms, a definition and discussion of the topic, bibliographies, and links to related literature. Extensive cross-references to other entries within the Encyclopedia support efficient, user-friendly searchers for immediate access to useful information. Key concepts presented in the Encyclopedia of Parallel Computing include; laws and metrics; specific numerical and non-numerical algorithms; asynchronous algorithms; libraries of subroutines; benchmark suites; applications; sequential consistency and cache coherency; machine classes such as clusters, shared-memory multiprocessors, special-purpose machines and dataflow machines; specific machines such as Cray supercomputers, IBM’s cell processor and Intel’s multicore machines; race detection and auto parallelization; parallel programming languages, synchronization primitives, collective operations, message passing libraries, checkpointing, and operating systems. Topics covered: Speedup, Efficiency, Isoefficiency, Redundancy, Amdahls law, Computer Architecture Concepts, Parallel Machine Designs, Benmarks, Parallel Programming concepts & design, Algorithms, Parallel applications. This authoritative reference will be published in two formats: print and online. The online edition features hyperlinks to cross-references and to additional significant research. Related Subjects: supercomputing, high-performance computing, distributed computing
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.
Since its first volume in 1960, Advances in Computers has presented detailed coverage of innovations in hardware and software and in computer theory, design, and applications. It has also provided contributorswith a medium in which they can examine their subjects in greater depth and breadth than that allowed by standard journal articles. As a result, many articles have become standard references that continue to be of significant, lasting value despite the rapid growth taking place in the field.
This volume contains the papers presented at the 13th International Workshop on Languages and Compilers for Parallel Computing. It also contains extended abstracts of submissions that were accepted as posters. The workshop was held at the IBM T. J. Watson Research Center in Yorktown Heights, New York. As in previous years, the workshop focused on issues in optimizing compilers, languages, and software environments for high performance computing. This continues a trend in which languages, compilers, and software environments for high performance computing, and not strictly parallel computing, has been the organizing topic. As in past years, participants came from Asia, North America, and Europe. This workshop re?ected the work of many people. In particular, the members of the steering committee, David Padua, Alex Nicolau, Utpal Banerjee, and David Gelernter, have been instrumental in maintaining the focus and quality of the workshop since it was ?rst held in 1988 in Urbana-Champaign. The assistance of the other members of the program committee – Larry Carter, Sid Chatterjee, Jeanne Ferrante, Jans Prins, Bill Pugh, and Chau-wen Tseng – was crucial. The infrastructure at the IBM T. J. Watson Research Center provided trouble-free logistical support. The IBM T. J. Watson Research Center also provided ?nancial support by underwriting much of the expense of the workshop. Appreciation must also be extended to Marc Snir and Pratap Pattnaik of the IBM T. J. Watson Research Center for their support.
This volume presents revised versions of the 32 papers accepted for the Seventh Annual Workshop on Languages and Compilers for Parallel Computing, held in Ithaca, NY in August 1994. The 32 papers presented report on the leading research activities in languages and compilers for parallel computing and thus reflect the state of the art in the field. The volume is organized in sections on fine-grain parallelism, align- ment and distribution, postlinear loop transformation, parallel structures, program analysis, computer communication, automatic parallelization, languages for parallelism, scheduling and program optimization, and program evaluation.