October 24, 2024
ExecuTorch Beta: On-Device AI and LLMs, Stability, and Acceleration with Partners
ExecuTorch has achieved Beta status with the release of v0.4, providing stable APIs and runtime, as well as extensive kernel coverage. ExecuTorch is the recommended on-device inference engine for Llama 3.2 1B/3B models, offering enhanced performance and memory efficiency for both original and quantized models. There has been a significant increase in adoption and ecosystem growth for ExecuTorch, and the focus is now on improving reliability, performance, and coverage for non-CPU backen...
October 23, 2024
TorchRec and FBGEMM 1.0 Stable Release
We are happy to announce the stable release, 1.0, for TorchRec and FBGEMM. TorchRec is the PyTorch native recommendation systems library, powered by FBGEMM’s (Facebook GEneral Matrix Multiplication) efficient, low-level kernels.
October 17, 2024
PyTorch 2.5 Release Blog
We are excited to announce the release of PyTorch® 2.5 (release note)! This release features a new cuDNN backend for SDPA, enabling speedups by default for users of SDPA on H100s or newer GPUs. As well, regional compilation of torch.compile offers a way to reduce the cold start up time for torch.compile by allowing users to compile a repeated nn.Module (e.g. a transformer layer in LLM) without recompilations. Finally, TorchInductor CPP backend offers solid performance speedup with numerous en...
October 15, 2024
The Path to Achieve PyTorch Performance Boost on Windows CPU
The challenge of PyTorch’s lower CPU performance on Windows compared to Linux has been a significant issue. There are multiple factors leading to this performance disparity. Through our investigation, we’ve identified several reasons for poor CPU performance on Windows, two primary issues have been pinpointed: the inefficiency of the Windows default malloc memory allocator and the absence of SIMD for vectorization optimizations on the Windows platform. In this article, we show how PyTorch CPU...
October 08, 2024
PyTorch Foundation Technical Advisory Council Elects New Leadership
We are pleased to announce the first-ever Chair and Vice Chair of the PyTorch Foundation’s Technical Advisory Council (TAC): Luca Antiga as the Chair and Jiong Gong as Vice Chair. Both leaders bring extensive experience and deep commitment to the PyTorch community, and they are set to guide the TAC in its mission to foster an open, diverse, and innovative PyTorch technical community. Meet the New Leadership Luca Antiga is the CTO at Lightning AI since 2022. He is an early contributor to P...
October 02, 2024
PyTorch Conference 2024 Recap: On Fire 🔥
The 2024 PyTorch Conference in San Francisco gathered nearly 1,500 AI researchers, developers, and enthusiasts. Over two days, the event featured engaging discussions, insightful keynotes, and hands-on sessions focused on artificial intelligence (AI) and advancements in PyTorch, the leading open-source machine learning framework. Attendees delved into the future of generative AI, Large Language Models (LLMs), and the crucial role open-source technology plays in driving AI innovation. Here’s...
September 26, 2024
PyTorch Native Architecture Optimization: torchao
We’re happy to officially launch torchao, a PyTorch native library that makes models faster and smaller by leveraging low bit dtypes, quantization and sparsity. torchao is an accessible toolkit of techniques written (mostly) in easy to read PyTorch code spanning both inference and training. This blog will help you pick which techniques matter for your workloads. We benchmarked our techniques on popular GenAI models like LLama 3 and Diffusion models and saw minimal drops in accuracy. Unless o...
