David Padua – författare

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

This historical survey of parallel processing from 1980 to 2020 is a follow-up to the authors’ 1981 Tutorial on Parallel Processing, which covered the state of the art in hardware, programming languages, and applications. Here, we cover the evolution of the field since 1980 in: parallel computers, ranging from the Cyber 205 to clusters now approaching an exaflop, to multicore microprocessors, and Graphic Processing Units (GPUs) in commodity personal devices; parallel programming notations such as OpenMP, MPI message passing, and CUDA streaming notation; and seven parallel applications, such as finite element analysis and computer vision. Some things that looked like they would be major trends in 1981, such as big Single Instruction Multiple Data arrays disappeared for some time but have been revived recently in deep neural network processors. There are now major trends that did not exist in 1980, such as GPUs, distributed memory machines, and parallel processing in nearly every commodity device.This book is intended for those that already have some knowledge of parallel processing today and want to learn about the history of the three areas. In parallel hardware, every major parallel architecture type from 1980 has scaled-up in performance and scaled-out into commodity microprocessors and GPUs, so that every personal and embedded device is a parallel processor. There has been a confluence of parallel architecture types into hybrid parallel systems. Much of the impetus for change has been Moore’s Law, but as clock speed increases have stopped and feature size decreases have slowed down, there has been increased demand on parallel processing to continue performance gains. In programming notations and compilers, we observe that the roots of today’s programming notations existed before 1980. And that, through a great deal of research, the most widely used programming notations today, although the result of much broadening of these roots, remain close to target system architectures allowing the programmer to almost explicitly use the target’s parallelism to the best of their ability. The parallel versions of applications directly or indirectly impact nearly everyone, computer expert or not, and parallelism has brought about major breakthroughs in numerous application areas. Seven parallel applications are studied in this book.

This volume contains the proceedings of the Fourth Workshopon Languages andCompilers for Parallel Computing, held inSanta Clara, California, in August1991. The purpose of theworkshop, held every year since 1988, is to bring togetherthe leading researchers on parallel programming languagedesignand compilation techniques for parallel computers. The papers in this book cover several important topicsincluding: (1) languages and structures to representprograms internally in the compiler, (2) techniques toanalyzeand manipulate sequential loops in order to generatea parallel version, (3)techniques to detect and extractfine-grain parallelism, (4) scheduling and memory-managementissues in automatically generated parallel programs, (5)parallel programming language designs, and (6) compilationof explicitly parallel programs. Together, the papers give a good overview of the researchprojects underway in 1991 in this field.

The articles in this volume are revised versions of the bestpapers presented at the Fifth Workshop on Languages andCompilers for Parallel Computing, held at Yale University,August 1992. The previous workshops in this series were heldin Santa Clara (1991), Irvine (1990), Urbana (1989), andIthaca (1988). As in previous years, a reasonablecross-section of some of the best work in the field ispresented. The volume contains 35 papers, mostly by authorsworking in the U. S. or Canada but also by authors fromAustria, Denmark, Israel, Italy, Japan and the U. K.

This book contains papers selected for presentation at theSixth Annual Workshop on Languages and Compilers forParallel Computing. The workshop washosted by the OregonGraduate Institute of Science and Technology. All the majorresearch efforts in parallel languages and compilers arerepresented in this workshop series. The 36 papers in the volume aregrouped under nine headings:dynamic data structures, parallel languages, HighPerformance Fortran, loop transformation, logic and dataflowlanguage implementations, fine grain parallelism, scalaranalysis, parallelizing compilers, and analysis of parallelprograms. The book represents a valuable snapshot of thestate of research in the field in 1993.

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.

This book presents the refereed proceedings of the Eighth Annual Workshop on Languages and Compilers for Parallel Computing, held in Columbus, Ohio in August 1995.The 38 full revised papers presented were carefully selected for inclusion in the proceedings and reflect the state of the art of research and advanced applications in parallel languages, restructuring compilers, and runtime systems. The papers are organized in sections on fine-grain parallelism, interprocedural analysis, program analysis, Fortran 90 and HPF, loop parallelization for HPF compilers, tools and libraries, loop-level optimization, automatic data distribution, compiler models, irregular computation, object-oriented and functional parallelism.