Introduction to parallel computing for scientists and engineers. Shared memory parallel architectures and programming, distributed memory, message-passing data-parallel architectures, and programming.

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 ...

This week is the eighth annual International Workshop on OpenCL, SYCL, Vulkan, and SPIR-V, and the event is available online for the very first time in its history thanks to the coronavirus pandemic.

(CS 213 or (CE 205 & 211)) or MS CS/CE or PhDs CS/CE or permission of Instructor. CS 358 serves as an introduction to the field of parallel computing. Topics include common parallel architectures ...

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 ...

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 ...

The difference between distributed computing and concurrent programming is a common area of confusion as there is a significant amount of overlap between the two when you set out to accomplish ...

There is always the promise of using more computing power for a single task. Your computer has multiple CPUs now, surely. Your video card has even more. Your computer is probably networked to a slew ...

CUDA is a parallel computing programming model for Nvidia GPUs. With the proliferation over the past decade of GPU usage for speeding up applications across HPC, AI and beyond, the ready availability ...

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 ...

Back in 1965, Intel cofounder Gordon Moore predicted that the semiconductor industry could double the number of transistors on a chip every 12 months (he later amended it to 24 months) for about the ...