Variations in hardware and parallel programming models make it increasingly difficult to achieve high performance without disruptive platform-specific changes to application software.

The Parallel Systems Group carries out research to facilitate the use of extreme-scale computers for scientific discovery. We are especially focused on tools research to maximize the …

Research Staff David Boehme : performance analysis tools, performance optimization, parallel and distributed architectures, parallel programming paradigms John Bowen : GPU …

David Richards : co-design of HPC systems, proxy applications, parallel programming models, Monte Carlo transport, cardiac simulation, molecular dynamics Kevin Sala Penades : …

Figure 1: Running scientific applications on heterogeneous HPC systems requires a complex interplay of programming languages, compilers, backend models, and other components. The …

Nov 24, 2015 · I used a Parallel.ForEach to iterate through each DataRow in a datatable and create a unique pdf file for each row in a folder. Even though I'm creating a unique file, I do get …

Nov 4, 2024 · | Johannes Doerfert (presenter) 1:30pm – 5:00pm | Tutorial | PyOMP: Parallel Programming in Python with OpenMP

BLT supports external dependencies for MPI, CUDA, OpenMP, and ROCm approaches to parallel programming. Everything required to use a dependency—includes, libraries, compile flags, link …

Oct 31, 2012 · Yes.Its better. Though inside TPL , its using QueueUserWorkItem and other similar threads. A primary reason for shift is also the lack of platform dependency.Like for windows …

Nov 9, 2023 · | Lance Fletcher, Trevor Steil, Roger Pearce (co-authors) Sophisticated Tools for Performance Analysis and Auto-Tuning of Performance Portable Parallel Programming