In high performance computing, machine learning, and a growing set of other application areas, accelerated, heterogeneous systems are becoming the norm. With that state come several parallel ...

In kicking off the panel, Gropp noted that in the last several years, taking an evolutionary approach to programming highly parallel machines has been successful. Just making incremental changes, ...

As modern .NET applications grow increasingly reliant on concurrency to deliver responsive, scalable experiences, mastering asynchronous and parallel programming has become essential for every serious ...

High Performance Computing (HPC) and parallel programming techniques underpin many of today’s most demanding computational tasks, from complex scientific simulations to data-intensive analytics. This ...

A hands-on introduction to parallel programming and optimizations for 1000+ core GPU processors, their architecture, the CUDA programming model, and performance analysis. Students implement various ...

In this paper, the authors present a survey of the different parallel programming models and tools available today with special consideration to their suitability for high performance computing. Thus, ...

In the task-parallel model represented by OpenMP, the user specifies the distribution of iterations among processors and then the data travels to the computations. In data-parallel programming, the ...

In this slidecast, Torsten Hoefler from ETH Zurich presents: Data-Centric Parallel Programming. The ubiquity of accelerators in high-performance computing has driven programming complexity beyond the ...

One of the things to avoid when it comes to parallelism is working with raw threads. Abstraction offers a way around the issue, by avoiding the need to deal with low-level details of parallel systems, ...