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 ...

The complexity and detail of mathematical models is rapidly increasing in response to the greater availability of quantitative data generated by experiments. The resulting equations to be solved ...

In case you don’t read the sidebar (you really should, you know), I’ve written a review of Calvin Lin and Larry Snyder’s relatively new book, “Principles of Parallel Programming” (we’ve never met, but ...

One of the best features of using FPGAs for a design is the inherent parallelism. Sure, you can write software to take advantage of multiple CPUs. But with an FPGA you can enjoy massive parallelism ...

We take a look back at the progress made in parallel computing with James Reinders, Parallel Programming Models Architect at Intel, who also shares his thoughts on how developers can get involved ...

The 14th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming (PPoPP 2009) and the 15th International Symposium on High-Performance Computer Architecture (HPCA-15) opened Monday in ...

This course focuses on developing and optimizing applications software on massively parallel graphics processing units (GPUs). Such processing units routinely come with hundreds to thousands of cores ...

NVIDIA’s CUDA is a general purpose parallel computing platform and programming model that accelerates deep learning and other compute-intensive apps by taking advantage of the parallel processing ...

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 ...

Write program to run in parallel? Yes. Did you remember to use a Scalable Memory Allocator? No? Then read on … In my experience, making sure “memory allocation” for a program is ready for parallelism ...