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, ...

Parallel programming exploits the capabilities of multicore systems by dividing computational tasks into concurrently executed subtasks. This approach is fundamental to maximising performance and ...

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 ...

I just recently finished reading Introduction to Concurrency in Programming Languages, one of the entries in CRC’s incredibly active Computational Science Series (“Incredibly active?” Yes: the series ...

I’m James Reinders. A common question I get asked is “If I’m going to add parallelism to my program, how should I do it? What should I look for?” A seemingly simple question so let’s see if we can ...

I just finished reading the new book by David Kirk and Wen-mei Hwu called Programming Massively Parallel Processors. The generic title notwithstanding, readers should not come to this book expecting ...

Whether modifying an existing application or writing entirely new code, parallel applications can be much more challenging to work with than their sequential counterparts. Without a doubt, 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, ...