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Lecture 28: Liger Kernel - Efficient Triton Kernels for LLM Training
Implementing Fused SwiGLU FFN From Scratch in Triton
Lecture 36 : Kernel Fusion, Thread and Block Coarsening (Contd.)
Lecture 28 : Optimizing Reduction Kernels
GPU Kernel Fusion from Scratch for Beginners
Statistical Machine Learning Part 18 - Kernels: definitions and examples
Lecture 37 : Kernel Fusion, Thread and Block Coarsening (Contd.)
Lecture 39 : Kernel Fusion, Thread and Block Coarsening (Contd.)
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Last Updated: October 17, 2026
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In this video, we learn more about writing code for Graphics Processing Units (GPUs). We cover the CUDA programming model, ... Ekaterina Sirazitdinova and Xiaopo Cheng from NVIDIA introduce how to accelerate large language model inference in JAX on ... Created by Vasudev Gupta me18b182. Byron Hsu presents LinkedIn's open-source collection of Triton In this episode, we explore how eliminating redundant read/write cycles to the GPU's global memory can unlock massive ... Part of the Course "Statistical Machine Learning", Summer Term 2020, Ulrike von Luxburg, University of Tübingen. Coarsening Factor, Stride length, Thread Level Coarsening, Block Level Coarsening.