Introduction In general, a parallel computer is a computer that has multiple processors connected by a communication network and is capable of using all its processors simultaneously to solve a single problem [34]. Parallel computers have the computational power necessary to solve many of computational science's "grand challenge" problems [27, 34]. However, it can be quite difficult to write programs that perform well on parallel machines. The research proposed here is concerned with performance prediction as a programming and performance debugging tool for parallel computers. 1.1 Parallel Programming Paradigms To solve a problem on a parallel computer, the programmer divides the problem into pieces which are then distribu...
While parallel computing offers an attractive perspective for the future, developing efficient paral...
Performance analysis of parallel programs continues to be challenging for programmers. Programmers h...
A compile-time prediction technique is outlined that yields approximate, yet low-cost, analytical pe...
Introduction In general, a parallel computer is a computer that has multiple processors connected b...
Context. Today’s parallel systems are widely used in different computational tasks. Developing paral...
The performance of a computer system is important. One way of improving performance is to use multip...
As workstation clusters gain popularity as a parallel computing platform,there is an increasing need...
High-performance computing is essential for solving large problems and for reducing the time to solu...
Parallel computing is essential for solving very large scientific and engineering problems. An effec...
Programming parallel computers for performance is a difficult task that requires careful attention t...
Performance is one of the key features of parallel and distributed computing systems. Therefore, in ...
Recent advances in the power of parallel computers have made them attractive for solving large compu...
The simulation of parallel systems is an alternative approach to classical parallel system programmi...
The shift towards multicore processing has led to a much wider population of developers being faced ...
Most performance debugging and tuning of parallel programs is based on the "measure-modify"...
While parallel computing offers an attractive perspective for the future, developing efficient paral...
Performance analysis of parallel programs continues to be challenging for programmers. Programmers h...
A compile-time prediction technique is outlined that yields approximate, yet low-cost, analytical pe...
Introduction In general, a parallel computer is a computer that has multiple processors connected b...
Context. Today’s parallel systems are widely used in different computational tasks. Developing paral...
The performance of a computer system is important. One way of improving performance is to use multip...
As workstation clusters gain popularity as a parallel computing platform,there is an increasing need...
High-performance computing is essential for solving large problems and for reducing the time to solu...
Parallel computing is essential for solving very large scientific and engineering problems. An effec...
Programming parallel computers for performance is a difficult task that requires careful attention t...
Performance is one of the key features of parallel and distributed computing systems. Therefore, in ...
Recent advances in the power of parallel computers have made them attractive for solving large compu...
The simulation of parallel systems is an alternative approach to classical parallel system programmi...
The shift towards multicore processing has led to a much wider population of developers being faced ...
Most performance debugging and tuning of parallel programs is based on the "measure-modify"...
While parallel computing offers an attractive perspective for the future, developing efficient paral...
Performance analysis of parallel programs continues to be challenging for programmers. Programmers h...
A compile-time prediction technique is outlined that yields approximate, yet low-cost, analytical pe...