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Source channel @githubtrending · Post #14985 · Jul 22

#c_lang#cuda#cuda_driver_api#cuda_kernels#cuda_opengl You can use the CUDA Samples from NVIDIA to learn and test CUDA Toolkit 12.9 features by downloading them from GitHub or as a ZIP file. These samples show how to use CUDA for GPU programming, including utilities, concepts, libraries, and performance optimization. You build them with CMake on Linux, Windows, or Tegra devices, and can run tests automatically with a provided Python script. This helps you understand CUDA programming, debug GPU code, and optimize your applications for better performance on NVIDIA GPUs. It’s a practical way to develop and improve GPU-accelerated software efficiently. https://github.com/NVIDIA/cuda-samples

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DOFH - DevOps from hell

@dofh_ru · Post #3570 · 02/05/2025, 05:54 PM

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Here we go again! SEV-SNP is vulnerable, again. New AMD SEV-SNP vulnerability: https://github.com/google/security-research/security/advisories/GHSA-4xq7-4mgh-gp6w Exploit: https://github.com/google/security-research/tree/master/pocs/cpus/entrysign Reports about two recent vulnerabilities in SEV-SNP memory encryption and isolation mechanism, on CPU pipeline, cache and branch prediction level: https://www.amd.com/en/resources/product-security/bulletin/amd-sb-3019.html https://www.amd.com/en/resources/product-security/bulletin/amd-sb-3010.html AMD reported that previous approaches to Spectre class attacks will work to fix new vulnerabilities: https://www.amd.com/content/dam/amd/en/documents/epyc-technical-docs/tuning-guides/software-techniques-for-managing-speculation.pdf #cVM #TEE #SEV #SNP #SEV_SNP #AMD

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