Tensors and neural networks in Python with strong hardware acceleration. PyTorch is an open source project at the Linux Foundation. #PyTorchFoundation
Joined September 2016
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Featured on today's agenda: Powering the Enterprise - executive sessions and workshops with @RedHat, @nvidia and @IBM focused on scaling enterprise AI
#PyTorchCon
Live from Jupyter Day - one of the co-located events at PyTorch Conference North America 2026 where data scientists, developers and researchers are coming together to discuss interactive computing and AI-assisted workflows.
#PyTorchCon @ProjectJupyter
If you know PyTorch, you know Trainium. @awscloud is bringing multiple sessions to #PyTorchCon in San Jose. AWS Trainium is an AI chip designed from the ground up for next generation deep learning AI training and inference, and now PyTorch runs natively on AWS Trainium --> zero code changes. Same APIs, same debugging, same ecosystem. Markus Adhiwiyogo of AWS, previews how the Neuron team is showing it all: training, profiling, RL, kernel development, and more. @AmazonScience
Join us at PyTorch Conference North America 2026: hubs.la/Q04v4SL60
Explore the sessions taking place today at LF AI & Data Summit 2026 where attendees are getting together to discuss open source technologies powering every stage of the AI lifecycle.
#PyTorchCon @LFAIDataFdn
#PyTorchCon North America starts TOMORROW! 🎉
Join us in San Jose for two days of open source AI ideas, code, connections, and serious PyTorch power.
Can’t make it in person? Sign up to watch the keynote livestream: bit.ly/4zEOQoq
Still time to register:
bit.ly/4sh3DSw
Day 0 of PyTorch Conference North America 2026: From Academia to Adoption Workshop
8 academic projects. Short lightning talks. Hands-on mentoring - helping researchers build sustainable, community-driven open source software.
#PyTorchCon
PyTorch runs natively on @awscloud Tranium with no code changes. AWS Tranium is @amazon's portfolio of AI chips designed for next-generation deep learning training and inference workloads. You can use it with the tools and workflows you are already familiar with. No new frameworks to learn. No code to change. During PyTorch Conference North America keynote, Robert Hundt, VP Distinguished Engineer, Annapurna Labs, Amazon will share the story and the capabilities AWS provided to meet performance and quality goals. @AmazonScience
#PyTorchCon
PyTorch retweeted
Accelerating open intelligence means an open ecosystem of companies, all investing engineering time upstream to improve critical open source software for inference: @vllm_project
A story in 3 acts, last 3 days: AMD, NVIDIA, Google all contribute significant improvement to @vllm_project, measured with @SemiAnalysis_ standard benchmark on K3. Great work from @inferact team shepherding and leading many of the optimizations!!!
Squeeze extra performance out of GPU kernels that are already autotuned to the limit by diving below the kernel level into compiler controls.
@nvidia CompileIQ and PyTorch Helion have united two distinct optimization layers into a single joint search space. While traditional autotuners search tile shapes, warps, and pipeline stages, ptxas compiler decisions like register allocation and fine-grained scheduling are typically left at default settings.
With CompileIQ’s Advanced Control Files (ACFs) integrated directly into Helion’s autotuner, developers can jointly evaluate kernel configurations and compiler controls, unlocking significant speedups on highly optimized production kernels without requiring deep compiler expertise.
Learn how to extract the last mile of performance: bit.ly/4i8Oxew
PyTorch retweeted
Announcing TorchNeuron: @PyTorch code now runs natively on AWS Trainium chips with a single configuration change. No rewrite needed.
Open sourcing at #PyTorchCon on Oct 20: amzn.to/3U3OnNI
PyTorch retweeted
Will be at @PyTorch conference tomorrow.
looking forward to a great line-up of speakers. 🔥
The next generation of intelligent systems won't be defined by scale.
It will be defined by intelligence that learns from your work. Co-founder @sarahookr on what that takes, live at @PyTorch Conference on October 20.
More hardware choice for PyTorch developers: TorchNeuron registers @awscloud Trainium as a native device, built on the same extension points the community created to make PyTorch hardware-agnostic.
Open sourcing at PyTorch Conference on Oct. 20. bit.ly/4i3P9Ud
Ravi Gupta, Shiksha Patel, and Rishi Madduri (@AMD) will present “Efficient Inference of Masked Diffusion Language Models on AMD XDNA2 NPU” at #PyTorchCon North America 2026.
Their poster presents a power-efficient deployment of LLaDA-8B-Instruct on an AMD NPU. On a Ryzen AI MAX+ 395 APU at sequence length 128, the NPU vendor path ran at 504 ms per forward at 36 W, compared with 843 ms and 110 W for CPU INT4, making it 1.67x faster and 8.9x better on energy.
The poster will also cover the INT4 quantization and graph-partitioning pipeline, the CastAvx fix, and the runtime approach used for single-step prefill on the XDNA2 NPU.
Register for PyTorch Conference North America 2026: hubs.la/Q04v4SL60
Looking for sessions to catch at #PyTorchCon North America 2026? Chris Hoge (@nvidia), co-chair of the PyTorch Ecosystem Working Group, highlights five talks for developers working on open source training and performance.
Hoge will co-present “Ecosystem Working Group: Unlocking Community Impact Through the PyTorch Landscape,” covering what the PyTorch Ecosystem Landscape is, how projects can apply for ecosystem status, and how lifecycle management works for Landscape projects.
He also highlights sessions featuring NVIDIA engineers on hiding expert parallel communication in Mixture-of-Experts training, parameterized dynamic-shaped CUDA graphs, building fused compute-communication kernels with PyTorch Symmetric Memory, and scaling PyTorch data loaders by a factor of 10.
Register for PyTorch Conference North America 2026: hubs.la/Q04v4SL60
How do you deliver full API parity across heterogeneous accelerators with zero additional overhead?
At PyTorch Conference North America 2026, Zesheng Zong (@Huawei), PyTorch Foundation Ambassador and Accelerator Integration Working Group Co-Chair, will share key technical updates on backend integration.
The community is adapting over 600,000 upstream test cases to be generic across all backends, providing a scalable path toward complete API parity. Alongside this effort, Cross-Repository CI Relay connects every PyTorch pull request directly to accelerator repositories, enabling real-time bidirectional testing, early regression detection, and a lower barrier to entry for out-of-tree hardware maintainers.
Join us in San Jose, California next week to see how these foundational updates simplify hardware enablement across the ecosystem: hubs.la/Q04v4SL60
#PyTorchCon @Zesheng_Zong
ExecuTorch is now an official @ZephyrIoT external module, bringing PyTorch model deployment into Zephyr’s firmware build workflow.
Zephyr Project’s walkthrough covers setup and runs quantized MobileNetV2 on an Alif Ensemble E8 DevKit, with the convolutional graph on the Arm Ethos-U55 NPU and input quantization and output dequantization on the Cortex-M55 CPU.
Read more: zephyrproject.org/executorch…
🤠 Hats off to our #PyTorchCon North America diamond sponsors. Connect with the people building the future of machine learning in San Jose, CA on October 20-21. Learn more: bit.ly/3TKs7bi
