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Google's AutoGrad + Tensorflow's XLA Linear Algebra Compiler = JAX
Profiling Pytorch/XLA on TPUs with XProf
JAX/OpenXLA DevLab 2025 Keynote Speech with Robert Hundt
JAX/OpenXLA DevLab 2025 - XLA Architecture
RL at Google Scale, with MaxText 2.0 | JAX/OpenXLA DevLab Fall 2025
Deep Dive: Compiling deep learning models, from XLA to PyTorch 2
Writing Custom TPU Kernels: Can Pallas Beat XLA (Bielik LLM on TPU v5e - RMSNorm)
JAX.einsum Explained By Google Engineer | JAX | XLA | Einstein Summation
2019 EuroLLVM Developers’ Meeting: T. Joerg “Automated GPU Kernel Fusion with XLA”
What is JAX
What Does The XLA Stand For
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Last Updated: September 29, 2026
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Summary
Are you exploring JAX for the first time and feeling overwhelmed by terms "functional purity," "explicit state," and "jit"? Using Triton IR for high-performance fusions in Kevin Gleason and Peter Gavin from an extensive analysis of the emerging software stack that threatens the decades-long dominance of Nvidia's proprietary CUDA ... Unlock the full potential of your PyTorch models running on Distinguished Engineer, Robert Hundt, from Kyle Meggs talks about the latest version of MaxText Fall 2025 Devlab talks playlist: ... Compilation is an excellent technique to accelerate the training and inference of deep learning models, especially if it can be ... JAX is an OpenSource library by llvm.org/devmtg/2019-04/ — Automated GPU Kernel Fusion with JAX is a high performance numerical computing framework that brings together differentiation to Python code (Autograd) and ...