What You Cannot Profile, You Cannot Optimize: Learning to Read PyTorch Traces // TRAIN BRAIN

What You Cannot Profile, You Cannot Optimize: Learning to Read PyTorch Traces

In his talk at PyTorch Conference North America 2026, Suvaditya Mukherjee from Hugging Face will share practical guidance on how to start using the PyTorch Profiler on your models to extract maximum performance efficiency.
Whether you are aiming to identify performance bottlenecks or optimize model execution, this talk will help you get the most out of your hardware.
Join the open source AI community in San Jose, October 20-21: https://hubs.la/Q04v4SL60

PyTorch

Welcome to the official PyTorch YouTube Channel. Learn about the latest PyTorch tutorials, new, and more. PyTorch is an open source machine learning framework that is used by both researchers and developers to build, train, and deploy ML systems that so...

What You Cannot Profile, You Cannot Optimize: Learning to Read PyTorch Traces

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Why WideEP Inference Needs Data-Parallel-Aware Scheduling - Maroon Ayoub & Tyler Michael Smith

Lightning Talk: How DeepInverse Is Solving Imaging in Science and H... Andrew Wang & Minh Hai Nguyen

Write Once, Run Everywhere with Pytorch Transformers - Pedro Cuenca, Hugging Face

The Science and Practice of Open and Scalable LLM Evaluations - Grzegorz Chlebus, NVIDIA

Lightning Talk: Deep Learning in the Wild: Embedded PyTorch for... Taraqur Rahman & Owen O'Donnell

The Token Slice: Implementing Preemptive Scheduling Via Chunked Decod... Maroon Ayoub & Kellen Swain

Enabling State-of-the-art Asynchronous Execution in Torch.compile With CUDA Streams - Michael Lazos

Lightning Talk: ExecuTorch on Microcontrollers: Deploying PyTorch To... RJ Ascani & Matthias Cremon

Lightning Talk: TerraKit: Standardising AI-Ready Geospatial Data... Rosie Lickorish & Romeo Kienzler

Lightning Talk: Bayesian Neural Networks With Variational Inference in PyTorch - Lars Heyen

Lightning Talk: Why Your Forecasting Transformer Isn’t Working (And How To Fix It... Rosheen Naeem

Build PyTorch to Understand PyTorch - Vijay Janapa Reddi & Andrea Mattia Garavagno

Lightning Talk: Jigsaw: Domain and Tensor Parallelism for High-Resolution Inp... Deifilia Kieckhefen

Optimizing PyTorch on CPU-GPU Coherent Platforms - Matthias Jouanneaux, Nvidia

torch.compile and Diffusers: A Hands-On Guide to Peak Performance - Sayak Paul, Hugging Face

PyTorch Foundation Spotlight: Matt White

PyTorch Foundation Spotlight: Prabha Ganapathy (AWS)

PyTorch Foundation Spotlight: Christian Jacobi

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PyTorch Foundation Spotlight: Niles Burbank, AMD

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PyTorch Foundation Spotlight: Ankita Guha, PyTorch Ambassador

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Behind Every AI SBOM Lies a Minefield: Here's How to Not Step... - Matthew Crawford & Jimmy Ahlberg

SPDX: Tackling System Risk in Modern Supply Chains - Kate Stewart & Gary O'Neall

The OpenMDW License Agreement: Simple, Permissive Terms for AI Model Materials - Steve Winslow

Sponsored Session: Lightning Talk: Accelerating Experimentation... - Niall Lyons & Luca Antiga

Using LlamaIndex to Build an Open-Source NotebookLM Alternative - Tuana Çelik, LlamaIndex

Our Journey With TorchTitan - Linsong Chu & Garrett Goon, IBM Research

Panel Discussion: The Future of Agents and Human-Agent Collaboration

PyTorch-Native Stack for Agents - Allen Wang & Davide Testuggine, Meta

Sponsored Session: Architecting AI: Efficient Models, Everywhere - Sharbani Roy, Arm

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Keynote: Building an Open Agentic Future - Samuel Colvin, Founder, Pydantic

Open Source Model Performance Optimization With SGLang - Yineng Zhang, Together AI

Sponsored Session: Fine Tune Your AI Toolbox with GitHub Copilot, Azure AI Foundry... - Sarah Kaiser

Sponsored Session: Lightning Talk: Build and Deploy AI Flows with an Agent Factory - Arjun Upadhyay

Generating State-of-the-Art GEMMs for Heterogeneous Hardware with... - Michael Lazos & Henry Tsang

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