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 ...

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 ...

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.

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 ...

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 ...

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 ...

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 ...

NVIDIA CUDA Tile introduces 'tile-based parallel programming' and it's being described as a major update to the CUDA platform, which powers a lot of AI.

Take advantage of lock-free, thread-safe implementations in C# to maximize the throughput of your .NET or .NET Core applications. Parallelism is the ability to have parallel execution of tasks on ...