Infleqtion, a world leader in neutral atom quantum computing, used the NVIDIA CUDA-Q platform to first simulate, and then orchestrate the first-ever demonstration of a material science experiment on logical qubits, on their Sqale physical quantum processing unit (QPU). Qubits, the basic units of information in quantum computing, are prone to errors, and far too unreliable to make meaningful��
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NVIDIA offers a large suite of tools for graphics debugging, including NVIDIA Nsight System for CPU debugging, and Nsight Graphics for GPU debugging. Nsight Aftermath is useful for analyzing crash dumps. Thanks to Patrick Neill, Jeffrey Kiel, Justin Kim, Andrew Allan, and Louis Bavoil for their help with this post.
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A total of 23 of the most often requested Vulkan extensions developed by NVIDIA and other Khronos members are now incorporated into the brand new Vulkan 1.3 core specification. NVIDIA is ready with day one drivers for developers to immediately try out this significant new version of the industry��s only modern, cross-platform GPU API on their own systems. Some of the most significant new core��
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One of the most important aspects in professional software development is to detect errors as early as possible. Of course, the best case would be if we couldn��t even write erroneous code. The next best thing is errors that the compiler can detect. The worst cases are runtime errors. The hardest ones are hidden in code that only runs under certain circumstances. Murphy��s law says that��
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In this third post of the CUDA C/C++ series, we discuss various characteristics of the wide range of CUDA-capable GPUs, how to query device properties from within a CUDA C/C++ program, and how to handle errors. In our last post, about performance metrics, we discussed how to compute the theoretical peak bandwidth of a GPU. This calculation used the GPU��s memory clock rate and bus interface��
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In this third post of the CUDA Fortran series we discuss various characteristics of the wide range of CUDA-capable GPUs, how to query device properties from within a CUDA Fortran program, and how to handle errors. In our last post, about performance metrics, we discussed how to compute the theoretical peak bandwidth of a GPU. This calculation used the GPU��s memory clock rate and bus interface��
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