![]() ![]() You will apply these notions in our labroom with hands-on examples. We will explain basic principles and advanced topics on GPU programming with CUDA. To guide you in this development niche, the Delft Institute for Computational Science and Engineering (DCSE) offers a CUDA course every quarter. Also, CUDA-extended codes keep pace closely with the rapid developments in the underlying technology. A single source code is then able to instruct the CPU and GPU alike. CUDA provides language extensions for C, C++, FORTRAN, and Python as well as knowledge-specific libraries. It is a software-development tool kit for programming on the GPUs maintained by the mainstream manufacturer Nvidia. What is CUDA?ĬUDA stands for Compute Unified Device Architecture. However, realizing efficient parallelism combines three knowledge areas: firstly, on the architecture and compute capabilities of the GPUs then, on special constructs for programming a GPU-equipped computer finally, on the special algorithms for performing logical and mathematical operations in parallel. For affordable budgets anyone can harness supercomputer performance. Nowadays the Graphics Processing Unit (GPU) is a mainstream hardware component in high-performance computing. ![]()
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