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GPU Based Acceleration of Telegraph Equation

Vaclav Simek, Michal Kraus, Kunovsky Jiri, Jiri Petrek

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Tags: Algorithms, Computer science, CUDA, nVidia

October 27, 2010 by hgpu

Importance of Explicit Vectorization for CPU and GPU Software Performance

Neil G. Dickson, Kamran Karimi, Firas Hamze

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Tags: Computer science, CUDA, Monte Carlo simulation, nVidia, nVidia GeForce GTX 285, Physics

October 27, 2010 by hgpu

On the limits of GPU acceleration

Richard Vuduc, Aparna Chandramowlishwaran, Jee Choi, Murat Guney, Aashay Shringarpure

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Tags: Computer science, nVidia, nVidia GeForce GTX 285, Performance, Tesla C1060, Tesla S1070

October 27, 2010 by hgpu

GPU sample sort

Nikolaj Leischner, Vitaly Osipov, Peter Sanders

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Tags: Computer science, CUDA, Data Structures and Algorithms, nVidia, nVidia GeForce GTX 285, Sorting, Tesla C1060

October 27, 2010 by hgpu

Accelerating video decoding using GPU

Guobin Shen,Lihua Zhu,Shipeng Li,Heung-Yeung Shum,Ya-Qin Zhang

Tags: Computer science, nVidia, Video decoding

October 27, 2010 by hgpu

nVidia GeForce GTX 480

Tags: nVidia, nVidia GeForce 4xx

October 17, 2010 by hgpu

ATTUNE: Agentic Throughput Tuning for LLM Training

HPCAgent-Bench: A Framework for Sound Benchmarking of Code-Optimizing Agents, Harnesses, and Skills

Brian2 Atlas

A Unified Intermediate Representation and Execution Architecture for Heterogeneous and Distributed Neural Simulation

AgentGarten: Code Worlds for Evolving Agents

KernelLens: Automated Triton-to-C++ Compiler for Enterprise Inference Runtimes

KernelLens: Deploying Triton Kernels to C++ Inference Engines

KernelZero: Co-Evolving Proposer and Coder for Continuously Improved GPU Kernel Generation

Introduction to Computer Vision

ACT: Accelerator Compiler Toolkit

Automatically Generating ML Compiler Backends from Tensor Accelerator ISA Descriptions

pytest-gpu-proof: A Simple Pytest Extension for Local GPU Code Testing

pytest-gpu-proof: Enabling Cloud-CPU Continuous Integration for GPU Code with Local GPU Attestation

Accelerating the Mitigation of LLM Inference Nondeterminism Across GPU Architectures

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high performance computing on graphics processing units: hgpu.org

GPU Based Acceleration of Telegraph Equation

Importance of Explicit Vectorization for CPU and GPU Software Performance

On the limits of GPU acceleration

GPU sample sort

Accelerating video decoding using GPU

nVidia GeForce GTX 480

Recent source codes

ATTUNE: Agentic Throughput Tuning for LLM Training

HPCAgent-Bench: A Framework for Sound Benchmarking of Code-Optimizing Agents, Harnesses, and Skills

Brian2 Atlas

AgentGarten: Code Worlds for Evolving Agents

KernelLens: Automated Triton-to-C++ Compiler for Enterprise Inference Runtimes

KernelZero: Co-Evolving Proposer and Coder for Continuously Improved GPU Kernel Generation

Introduction to Computer Vision

ACT: Accelerator Compiler Toolkit

pytest-gpu-proof: A Simple Pytest Extension for Local GPU Code Testing

Accelerating the Mitigation of LLM Inference Nondeterminism Across GPU Architectures

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