Parallel execution of Lisp programs. Doctoral thesis

Technical Report · Thu Jun 01 04:00:00 EDT 1989

OSTI ID:6764432

Weening, J S

This dissertation considers several issues in the execution of Lisp programs on shared-memory multiprocessors. An overview of constructs for explicit parallelism in Lisp is first presented. The problem of partitioning a program into process and scheduling these processes are then described, and a number of methods for performing these are proposed. These include cutting off process creation based on properties of the computation tree of the program, and basing partitioning decisions on the state of the system at runtime instead of the program. An experimental study of these methods has been performed using a simulator for parallel Lisp. This is followed by a description of the experiments that were performed and an analysis of the results. Two programs are used as illustrations-a Fast Fourier Transform, which has an abundance of parallelism, and the Cocke-Younger-Kasami parsing algorithm, for which good speedup is not as easy to obtain. The difficulty of using cutoff-based partitioning methods, and the differences between varios scheduling methods, are shown. A combination of partitioning and scheduling methods which we call dynamic partitioning is analyzed in more detail. This method is based on examining the machine's runtime state; it requires that the programmer only identify parallelism in the program, without deciding which potential parallelism is actually useful. We conclude that for programs whose computation trees have small height relative to their total size, dynamic partitioning can achieve asymptotically minimal overhead in the cost of process creation.

• Research Organization: Stanford Univ., CA (USA). Dept. of Computer Science
• OSTI ID: 6764432
• Report Number(s): AD-A-219623/6/XAB; STAN-CS--89-1265
• Country of Publication: United States
• Language: English

Related Subjects

99 GENERAL AND MISCELLANEOUS
990200* -- Mathematics & Computers
ARRAY PROCESSORS
COMPUTER CODES
COMPUTERIZED SIMULATION
COST
DATA PROCESSING
DECISION MAKING
DIMENSIONS
FOURIER TRANSFORMATION
HEIGHT
INTEGRAL TRANSFORMATIONS
LISP
MEMORY DEVICES
PARALLEL PROCESSING
PROCESSING
PROGRAMMING
PROGRAMMING LANGUAGES
SIMULATION
TASK SCHEDULING
TRANSFORMATIONS