We performed semistructured, open-ended interviews with 11 professional developers of parallel, scientific applications to determine how their programming time is spent and where tools could improve productivity. The subjects were selected from a variety of research laboratories, both industrial and governmental. The major findings were that programmers would prefer a global over a per-processor view of data structures, struggle with load balancing and optimizations, and need interactive tools for observing the behavior of parallel programs. Furthermore, handling and processing massive amounts of data in parallel is emerging as a new challenge
peer-reviewedThe shift towards multicore processing has led to a much wider population of developer...
Parallelization is a technique that boosts the performance of a program beyond optimizations of the ...
Computational scientists face many challenges when developing software that runs on large-scale para...
peer-reviewedIn recent years there has been a shift in microprocessor manufacture from building sing...
In developing High-Performance Computing (HPC) software, time to solution is an important metric. Th...
2Writing parallel programs is difficult. Besides the inherent difficulties associ-ated with writing ...
Performance analysis of parallel programs continues to be challenging for programmers. Programmers h...
The ability to write programs that execute efficiently on modern parallel computers has not been fu...
The computer industry has thrived upon decades of exponential growth in hardware and software capabi...
The computer industry is at a critical stage. Historically, programmers have been relying on faster ...
Parallel programmers do not use software tools, in spite fact that parallel development is a difficu...
We evaluate the claim that a PRAM-like parallel programming model (XMTC) requires less effort than a...
The popularity of parallel systems for building high performance software only continues to rise. Pr...
The availability of modern commodity multicore processors and multiprocessor computer systems has re...
The widespread adoption of Chip Multiprocessors has renewed the emphasis on the use of parallelism t...
peer-reviewedThe shift towards multicore processing has led to a much wider population of developer...
Parallelization is a technique that boosts the performance of a program beyond optimizations of the ...
Computational scientists face many challenges when developing software that runs on large-scale para...
peer-reviewedIn recent years there has been a shift in microprocessor manufacture from building sing...
In developing High-Performance Computing (HPC) software, time to solution is an important metric. Th...
2Writing parallel programs is difficult. Besides the inherent difficulties associ-ated with writing ...
Performance analysis of parallel programs continues to be challenging for programmers. Programmers h...
The ability to write programs that execute efficiently on modern parallel computers has not been fu...
The computer industry has thrived upon decades of exponential growth in hardware and software capabi...
The computer industry is at a critical stage. Historically, programmers have been relying on faster ...
Parallel programmers do not use software tools, in spite fact that parallel development is a difficu...
We evaluate the claim that a PRAM-like parallel programming model (XMTC) requires less effort than a...
The popularity of parallel systems for building high performance software only continues to rise. Pr...
The availability of modern commodity multicore processors and multiprocessor computer systems has re...
The widespread adoption of Chip Multiprocessors has renewed the emphasis on the use of parallelism t...
peer-reviewedThe shift towards multicore processing has led to a much wider population of developer...
Parallelization is a technique that boosts the performance of a program beyond optimizations of the ...
Computational scientists face many challenges when developing software that runs on large-scale para...