Modern personal computing devices feature multiple cores. This is not only true for desktops, laptops, tablets and smartphones, but also for small embedded devices like the Raspberry Pi. In order to ...

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 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 ...

Many hands make light work, or so they say. So do many cores, many threads and many data points when addressed by a single computing instruction. Parallel programming – writing code that breaks down ...

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 ...

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 ...

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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 ...

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 ...