Programming nonshared memory systems is more difficult than programming shared memory systems, since there is no support for shared data structures. Current programming languages for distributed memory architectures force the user to decompose all data structures into separate pieces, with each owned by one of the processors in the machine, and with all communication explicitly specified by low-level message-passing primitives. This paper presents a new programming environment for distributed memory architectures, providing a global name space and allowing direct access to remote parts of data values. We describe the analysis and program transformations required to implement this environment, and present the efficiency of the resulting code on the NCUBE/7 and IPSC/2 hypercubes. (kr).

Abstract: "Compiling for distributed memory machines has been a very active research area in recent years. Much of this work has concentrated on programs that use arrays as their primary data structures. To date, little work has been done to address the problem of supporting programs that use dynamic data structures. The techniques developed for supporting SPMD execution of array-based programs rely on the fact that arrays are statically defined and directly addressable. These techniques do not apply to recursive data structures, which are neither statically defined nor directly addressable. In this paper, we describe a three part approach to supporting programs that use dynamic data structures. First, we use a simple mechanism for migrating a thread of control based on the layout of heap-allocated data. Second, we introduce parallelism into the model using a technique based on futures and lazy task creation. Third, we exploit this execution model using compiler analyses and parallelization techniques. We have implemented a prototype system, which we call Olden, that runs on the Intel iPSC/860 and the Thinking Machines CM5. We discuss our implementation and report on experiments with four benchmarks."

Lists citations with abstracts for aerospace related reports obtained from world wide sources and announces documents that have recently been entered into the NASA Scientific and Technical Information Database.

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.

Zusammenfassung: This book offers a comprehensive survey of shared-memory synchronization, with an emphasis on "systems-level" issues. It includes sufficient coverage of architectural details to understand correctness and performance on modern multicore machines, and sufficient coverage of higher-level issues to understand how synchronization is embedded in modern programming languages. The primary intended audience for this book is "systems programmers"--the authors of operating systems, library packages, language run-time systems, concurrent data structures, and server and utility programs. Much of the discussion should also be of interest to application programmers who want to make good use of the synchronization mechanisms available to them, and to computer architects who want to understand the ramifications of their design decisions on systems-level code

Shared memory multiprocessors are becoming the dominant architecture for small-scale parallel computation. This book is the first to provide a coherent review of current research in shared memory multiprocessing in the United States and Japan. It focuses particularly on scalable architecture that will be able to support hundreds of microprocessors as well as on efficient and economical ways of connecting these fast microprocessors. The 20 contributions are divided into sections covering the experience to date with multiprocessors, cache coherency, software systems, and examples of scalable shared memory multiprocessors.