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.

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

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

Development tools for parallel computer systems tend to be architecture-specific, difficult to integrate and fairly basic. Parallel application developers often find themselves juggling tools to match ...

Microsoft’s Technical Computing initiative, announced Monday, will feature investments in parallel computing, technical computing in the cloud, and development of powerful technical computing tools ...

Modern computer systems are becoming increasingly parallel, which can make them much more challenging to use efficiently. Intel® Parallel Computing Centers (IPCCs) are being established with leading ...

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 ...

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 ...

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