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Examines recent advances in design, modeling, and implementation of dataflow and multithreaded computers. The text contains reports concerning many of the world's leading projects engaged in the continuing evolution and application of dataflow concepts. It covers the broad range of dataflow principles in program representation -- from language design to processor architecture -- and compiler optimization techniques. The book includes papers on massively parallel distributed memory and multithreaded architecture design, synchronization and pipelined design, and superpipelined data-driven VLSI processors. Other sections discuss stream data types, the development of well-structured software, and parallelization of dataflow programs It also details and analytical model for the behavior of dataflow graphs, compare a centralized work distribution scheme with a distributed scheme, and present a comprehensive approach to understanding workload management schemes. Altogether, the text introduces the reader to dataflow concepts that show how functional programming ideas can be harnessed to exploit the power of parallel computing.
Inhaltsverzeichnis
Foreword vii
Introduction ix
Processor Design
Design Principle of Massively Parallel Distributed-Memory Multiprocessor Architecture 1
M. Amamiya and T. Kawano StarT the Next Generation: Integrating Global Caches and Dataflow Architecture 19
B.S. Ang, Arvind, and D. Chiou Synchronization and Pipeline Design for a Multithreaded Massively Parallel Computer 55
S. Sakai Superpipelined Dynamic Data-Driven VLSI Processors 75
H. Terada, M. Iwata, S. Miyata, and S. Komori Language and Programming Issues Stream Data Types for Signal Processing 87
J.B. Dennis Multilateral Diagrammatical Specification Environment Based on Data-Driven Paradigm 103
M. Iwata and H. Terada Coarse-Grain Dataflow Programming of Conventional Parallel Computers 113
R. Jagannathan Distributed Data Structure in Thread-Based Programming for a Highly Parallel Dataflow Machine EM-4 131
M. Sato, Y. Kodama, S. Sakai, Y. Yamaguchi, and S. Sekiguchi Programmability and Performance Issues of Multiprocessors on Hard Nonnumeric Problems 143
A. Sohn and J.-L. Gaudiot Compiling Exploiting Iteration-Level Parallelism in Dataflow Programs 167
L. Bic, J.M.A. Roy, and M. Nagel Empirical Study of a Dataflow Language on the CM-5 187
D.E. Culler, S.C. Goldstein, K.E. Schauser, and T. von Eicken Programming the ADAM Architecture with SISAL 211
S. Mitrovic Can Dataflow Machines Be Programmed with an Imperative Language? 229
S.F. Wail and D. Abramson Resource Management and Scheduling The Token Flow Model 267
J. Buck and E.A. Lee Distributed Task Management in SISAL 291
M. Haines and A.P.W. Bohm Load Balancing and Resource Management in the ADAM Machine 307
O.C. Maquelin Workload Management in Massively Parallel Computers: Some Dataflow Experiences 325
D.F. Snelling and J.R. Gurd Studies on Optimal Task Granularity and Random Mapping 349
T. Sterling, J. Kuehn, M. Thistle, and T. Anastasio The Effects of Resource Limitations on Program Parallelism 367
K.B. Theobald, G.R. Gao, and L.J. Hendren Program Characteristics and Performance Studies The Dataflow Parallelism of FFT 393
A.P.W. Bohm and R.E. Hiromoto Locality in the Dataflow Paradigm 405
I. Gottlieb and L. Biran Locality and Latency in Hybrid Dataflow 417
W.A. Najjar, W.M. Miller, and A.P.W. Bohm Implementation of Manipulator Control Computation on Conventional and Dataflow Multiprocessor 435
S. Zeng and G.K. Egan Biography 449
Über den Autor / die Autorin
Guang R. Gao is a computer scientist and a Professor of Electrical and Computer Engineering at the University of Delaware. Gao is a founder and Chief Scientist of ETI. Lubomir Bic is the author of Advanced Topics in Dataflow Computing and Multithreading, published by Wiley.
