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Source channel @githubtrending · Post #14747 · May 25

#python#deep_learning#intel#machine_learning#neural_network#pytorch#quantization Intel Extension for PyTorch boosts the speed of PyTorch on Intel hardware, including both CPUs and GPUs, by using special features like AVX-512, AMX, and XMX for faster calculations[5][2][4]. It supports many popular large language models (LLMs) such as Llama, Qwen, Phi, and DeepSeek, offering optimizations for different data types and easy GPU acceleration. This means you can run advanced AI models much faster and more efficiently on your Intel computer, with simple setup and support for both ready-made and custom models. https://github.com/intel/intel-extension-for-pytorch

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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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