Advanced compiler optimizations for supercomputers
Communications of the ACM - Special issue on parallelism
A study of scalar compilation techniques for pipelined supercomputers
ASPLOS II Proceedings of the second international conference on Architectual support for programming languages and operating systems
Automatic decomposition of scientific programs for parallel execution
POPL '87 Proceedings of the 14th ACM SIGACT-SIGPLAN symposium on Principles of programming languages
Detecting conflicts between structure accesses
PLDI '88 Proceedings of the ACM SIGPLAN 1988 conference on Programming Language design and Implementation
Available instruction-level parallelism for superscalar and superpipelined machines
ASPLOS III Proceedings of the third international conference on Architectural support for programming languages and operating systems
Limits on multiple instruction issue
ASPLOS III Proceedings of the third international conference on Architectural support for programming languages and operating systems
Compiling Lisp programs for parallel execution
Lisp and Symbolic Computation
Limits of instruction-level parallelism
ASPLOS IV Proceedings of the fourth international conference on Architectural support for programming languages and operating systems
A brief survey of papers on scheduling for pipelined processors
ACM SIGPLAN Notices
Dependence Analysis for Supercomputing
Dependence Analysis for Supercomputing
Parallelizing Programs with Recursive Data Structures
IEEE Transactions on Parallel and Distributed Systems
Language design and analyzability: a retrospective
Software—Practice & Experience
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In this paper we propose a programming language mechanism and associated compiler techniques which significantly enhance the analyzability of pointer-based data structures frequently used in non-scientific programs. Our approach is based on exploiting two important properties of pointer data structures: structural inductivity and speculative traversability. Structural inductivity facilitates the application of a static interference analysis method for such pointer data structures based on path matrices, and speculative traversability is utilized by a novel loop unrolling technique for while loops that exploit fine-grain parallelism by speculatively traversing such data structures. The effectiveness of this approach is demonstrated by applying it to a collection of loops found in typical non-scientific C programs.