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PyTorch/XLA SPMD: Scale Up Model Training and Serving with Automatic Parallelization

Today, we are delighted to announce PyTorch/XLA SPMD: the integration of GSPMD into PyTorch with an easy…

Yeounoh Chung, Jon Bolin, Milad Mohammadi, Jiewen Tan, Jack Cao, Joe Spisak, Alex Spiridonov, Shauheen Zahirazami, Steven Krawczyk, Wonjoo Lee Mohit Khatwani, Wanchao Liang, Vaibhav SinghAugust 31, 2023

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Large Scale Training of Hugging Face Transformers on TPUs With PyTorch/XLA FSDP

AI is transforming many industries through advanced capabilities such as understanding and generating language, answering…

Alex Wertheim, Milad Mohammadi, Jack Cao, Alex Spiridonov, Joe Spisak, Lysandre Debut, Sylvain Gugger, Sourab MangrulkarAugust 24, 2023

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INT8 Quantization for x86 CPU in PyTorch

Overview INT8 quantization is a powerful technique for speeding up deep learning inference on x86…

IntelAugust 7, 2023

Blog

Announcing CPP-based S3 IO DataPipes

Training large deep learning models requires large datasets. Amazon Simple Storage Service (Amazon S3) is a scalable…

John He, Khaled ElGalaind, Roshani Nagmote, Daiming YangJuly 25, 2023

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How to Accelerate PyTorch Geometric on Intel® CPUs

Overview The Intel PyTorch team has been collaborating with the PyTorch Geometric (PyG) community to…

IntelJuly 10, 2023

Community

Unveiling the Power of Semi-Supervised Learning: The Unified Semi-Supervised Learning Benchmark

Machine Learning models thrive on high-quality, fully-annotated data. The traditional supervised learning approach typically requires…

Jindong WangJuly 6, 2023

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Optimizing LibTorch-based inference engine memory usage and thread-pooling

Outline In this blog post we show how to optimize LibTorch-based inference engine to maximize…

Himalay Mohanlal Joriwal, Pierre-Yves Aquilanti, Vivek Govindan, Hamid Shojanazeri, Ankith Gunapal, Tristan RiceJune 29, 2023

Community

Introducing TorchOpt: A High-Performance Differentiable Optimization Library for PyTorch

Explore TorchOpt, a PyTorch-based library that revolutionizes differentiable optimization with its unified programming abstraction, high-performance…

Benjamin LiuJune 29, 2023

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The Path to Achieve Ultra-Low Inference Latency With LLaMA 65B on PyTorch/XLA

Background & State of the Art In the natural language processing (NLP) space, language models…

Milad Mohammadi, Jiewen Tan, Liyang Lu, Siyuan Liu, Yeounoh Chung, Wonjoo Lee, Manfei Bai, Steven Krawczyk, Shauheen Zahirazami, Alex Wertheim, Meghan Cowan, Jack Cao, Joe SpisakJune 28, 2023

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Optimized PyTorch 2.0 Inference with AWS Graviton processors

New generations of CPUs offer significant performance improvement in machine learning (ML) inference due to…

Sunita Nadampalli from AWS & Ankith Gunapal from MetaJune 22, 2023

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🎉 PyTorch Docathon H1 2023 Wrap-up 🎉

Thank you to all who participated in our first ever PyTorch Docathon, the results have…

PyTorch FoundationJune 16, 2023

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Out of the box acceleration and memory savings of 🤗 decoder models with PyTorch 2.0

As part of PyTorch 2.0 release, an accelerated implementation of the attention mechanism as part…

Felix Marty, Younes Belkada, Hamid Shojanazeri, Driss GuessousMay 22, 2023

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Language Identification: Building an End-to-End AI Solution using PyTorch

Language Identification is the process of identifying the primary language from multiple audio input samples.…

IntelMay 12, 2023

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Accelerated Image Segmentation using PyTorch

Using Intel® Extension for PyTorch to Boost Image Processing Performance PyTorch delivers great CPU performance,…

IntelMay 2, 2023

Blog

Introducing Hidet: A Deep Learning Compiler for Efficient Model Serving

Hidet is a powerful deep learning compiler that simplifies the process of implementing high-performing deep learning…

Team HidetApril 27, 2023

Blog

Accelerating Large Language Models with Accelerated Transformers

TL;DR. We show how to use Accelerated PyTorch 2.0 Transformers and the newly introduced torch.compile() method to accelerate…

Lucas Pasqualin, Driss Guessous, Christian Puhrsch, Bertrand Maher, Michael GschwindApril 19, 2023

Blog

Experience the power of PyTorch 2.0 on AMD Solutions

PyTorch 2.0 represents a significant step forward for the PyTorch machine learning framework. The stable…

AMDApril 15, 2023

Blog

Accelerated Generative Diffusion Models with PyTorch 2

TL;DR: PyTorch 2.0 nightly offers out-of-the-box performance improvement for Generative Diffusion models by using the…

Grigory Sizov, Michael Gschwind, Hamid Shojanazeri, Driss Guessous, Daniel Haziza, Christian PuhrschApril 14, 2023

Blog

Straggler Mitigation On PyTorch DDP By Hierarchical SGD

PyTorch DDP has been widely adopted across the industry for distributed training, which by default runs…

Yi Wang (Cruise AI), Rohan Varma (Meta AI)April 7, 2023

Blog

Celebrate PyTorch 2.0 with New Performance Features for AI Developers

Congratulations to the PyTorch Foundation for its release of PyTorch 2.0! In this blog, I discuss…

IntelApril 7, 2023

PyTorch/XLA SPMD: Scale Up Model Training and Serving with Automatic Parallelization

Large Scale Training of Hugging Face Transformers on TPUs With PyTorch/XLA FSDP

INT8 Quantization for x86 CPU in PyTorch

Announcing CPP-based S3 IO DataPipes

How to Accelerate PyTorch Geometric on Intel® CPUs

Unveiling the Power of Semi-Supervised Learning: The Unified Semi-Supervised Learning Benchmark

Optimizing LibTorch-based inference engine memory usage and thread-pooling

Introducing TorchOpt: A High-Performance Differentiable Optimization Library for PyTorch

The Path to Achieve Ultra-Low Inference Latency With LLaMA 65B on PyTorch/XLA

Optimized PyTorch 2.0 Inference with AWS Graviton processors

🎉 PyTorch Docathon H1 2023 Wrap-up 🎉

Out of the box acceleration and memory savings of 🤗 decoder models with PyTorch 2.0

Language Identification: Building an End-to-End AI Solution using PyTorch

Accelerated Image Segmentation using PyTorch

Introducing Hidet: A Deep Learning Compiler for Efficient Model Serving

Accelerating Large Language Models with Accelerated Transformers

Experience the power of PyTorch 2.0 on AMD Solutions

Accelerated Generative Diffusion Models with PyTorch 2

Straggler Mitigation On PyTorch DDP By Hierarchical SGD

Celebrate PyTorch 2.0 with New Performance Features for AI Developers

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