Results 271 to 280 of about 103,699 (311)
Some of the next articles are maybe not open access.
Dynamic program parallelization
ACM SIGPLAN Lisp Pointers, 1992Static program analysis limits the performance improvements possible from compile-time parallelization. Dynamic program parallelization shifts a portion of the analysis from complie-time to run-time, thereby enabling optimizations whose static detection is overly expensive or impossible. Lambda tagging
Lorenz Huelsbergen, James R. Larus
openaire +1 more source
On reductions of parallel programs
1979By a reduction of a parallel program, as informally introduced by Lipton, the number of possible execution sequences is decreased, which facilitates analysis and verification. This method is extended to simplify verification proofs of parallel programs.
Wolfgang Kowalk, Rüdiger Valk
openaire +1 more source
Verification of parallel programs
International Journal of Computer Mathematics, 1995Ensuring the reliability of computer programs is particularly important, especially for systems with critical applications. The program correctness has to be verified to behave as they were intended to do. For parallel machines, the task is even more difficult because results of executing parallel programs can be very unpredictable as many processes ...
Mohd Yazid Saman, David J. Evans 0001
openaire +1 more source
International Journal of High Speed Computing, 1993
Parallel computer architectures and hardware have evolved impressively in the last few years from the architecture and the hardware point of view. Progress on the software side can be best characterized as moderate. The lack of methodologies and software to support parallel programming is profound even on the most advanced parallel machines.
openaire +1 more source
Parallel computer architectures and hardware have evolved impressively in the last few years from the architecture and the hardware point of view. Progress on the software side can be best characterized as moderate. The lack of methodologies and software to support parallel programming is profound even on the most advanced parallel machines.
openaire +1 more source
Proceedings of the compilation of the co-located workshops on DSM'11, TMC'11, AGERE! 2011, AOOPES'11, NEAT'11, & VMIL'11, 2011
Sequential programs are often difficult to parallelize because of the complexity in their implementation and the uncertainty in their behavior. We will demonstrate behavior-oriented parallelization (BOP), which provides annotations for a user to mark possibly parallel regions (PPR) in code and a safe implementation to execute the annotated tasks in ...
Chen Ding 0001, Zachary Fletcher
openaire +2 more sources
Sequential programs are often difficult to parallelize because of the complexity in their implementation and the uncertainty in their behavior. We will demonstrate behavior-oriented parallelization (BOP), which provides annotations for a user to mark possibly parallel regions (PPR) in code and a safe implementation to execute the annotated tasks in ...
Chen Ding 0001, Zachary Fletcher
openaire +2 more sources
Languages for parallel programming
1991Many different paradigms for parallel programming exist, nearly each of which is employed in dozens of languages. Several researchers have tried to compare these languages and paradigms by examining the expressivity and flexibility of their constructs.
openaire +1 more source
Parallel evolutionary programming
Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753), 2005This work presents a study of parallel evolutionary programming (EP). The paper is divided into two parts. The first part proposes a concept of parallel EP. Four numerical functions are used to compare the performance between the serial algorithm and the parallel algorithm.
Shisanu Tongchim, Xin Yao 0001
openaire +1 more source
Parallelizing constraint programs
Proceedings of the 5th ACM SIGPLAN workshop on Declarative aspects of multicore programming, 2010The availability of commodity multicore and multiprocessor machines and the inherent parallelism in constraint programming search offer significant opportunities for constraint programming. Both constraint-based local search and finite-domain techniques can dramatically benefit from parallelization.
openaire +1 more source
Practical parallel programming
IEEE Concurrency, 1999Part 1 Fundamentals: basic architectural ideas classifying architectures some example applications decomposition techniques terms and measures. Part 3 Data parallelism: basic operations an inside-out syntax other data-parallel operations automatic parallelization controlling and exploiting data placement discussion.
openaire +1 more source
[1989] Proceedings of the Thirteenth Annual International Computer Software & Applications Conference, 2003
Although parallel programs are significantly more complex than sequential programs the same debugging methodology, augmented with the appropriate tools, can be used to debug parallel and sequential programs. Experiments have shown that these tools can reduce the debugging cycle for a parallel program dramatically. Other techniques, such as verification
openaire +1 more source
Although parallel programs are significantly more complex than sequential programs the same debugging methodology, augmented with the appropriate tools, can be used to debug parallel and sequential programs. Experiments have shown that these tools can reduce the debugging cycle for a parallel program dramatically. Other techniques, such as verification
openaire +1 more source