Scaling ExecuTorch & Disaggregating LLM Serving // TRAIN BRAIN

Scaling ExecuTorch & Disaggregating LLM Serving

At PyTorch Conference North America in San Jose, Arkadip Maitra from the PyTorch engineering team at Red Hat will present two technical poster sessions covering key topics in inference performance and testing infrastructure.
Register for PyTorch Conference America today: https://hubs.la/Q04v4SL60

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Scaling ExecuTorch & Disaggregating LLM Serving

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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

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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

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SGLang: An Efficient Open-Source Framework for Large-Scale LLM Serving - Liangsheng Yin

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