PCAST helps to quickly isolate divergence between CPU and GPU results so you can isolate bugs or verify your results are OK even if they aren’t identical.
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Detecting Divergence Using PCAST to Compare GPU to CPU Results

Parallel Compiler Assisted Software Testing (PCAST) is a feature available in the NVIDIA HPC Fortran, C++, and C compilers. PCAST has two use cases. 14 MIN READ
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Accelerating Fortran DO CONCURRENT with GPUs and the NVIDIA HPC SDK

Fortran developers have long been able to accelerate their programs using CUDA Fortran or OpenACC. Now with the latest 20.11 release of the NVIDIA HPC SDK… 13 MIN READ
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Bringing Tensor Cores to Standard Fortran

Tuned math libraries are an easy and dependable way to extract the ultimate performance from your HPC system. However, for long-lived applications or those that… 10 MIN READ
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Developer Blog: Bringing Tensor Cores to Standard Fortran

In this post, learn how you can seamlessly accelerate many standard Fortran array intrinsics and language constructs on GPUs. < 1
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Tensor Core Programming Using CUDA Fortran

The CUDA Fortran compiler from PGI now supports programming Tensor Cores with NVIDIA’s Volta V100 and Turing GPUs. This enables scientific programmers using… 12 MIN READ
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Using OpenACC to Port Solar Storm Modeling Code to GPUs

Solar storms consist of massive explosions on the Sun that can release the energy of over 2 billion megatons of TNT in the form of solar flares and Coronal Mass… 39 MIN READ