high performance computing on graphics processing units: hgpu.org

Steven G. Parker, James Bigler, Andreas Dietrich, Heiko Friedrich, Jared Hoberock, David Luebke, David McAllister, Morgan McGuire, Keith Morley, Austin Robison, Martin Stich

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Tags: 3D Graphics and Realism, Computer science, nVidia, nVidia GeForce GTX 285, nVidia GeForce GTX 480, nVidia GeForce GTX 485, nVidia Quadro FX 5800, PTX, Raytracing, Software Engineering

September 14, 2011 by hgpu

Nikola: embedding compiled GPU functions in Haskell

Geoffrey Mainland, Greg Morrisett

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Source codes

Tags: Code generation, Computer science, CUDA, nVidia, Package, Programming Languages, Tesla T10

September 14, 2011 by hgpu

A practical approach of curved ray prestack Kirchhoff Time Migration on GPGPU

Xiaohua Shi, Chuang Li, Xu Wang, Kang Li

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Tags: Algorithms, CUDA, Earth and Space Sciences, Floating point error, Geoscience, nVidia, nVidia GeForce 8800 GT, Optimization, Tesla C870

September 14, 2011 by hgpu

Anomalous behaviour detection using spatiotemporal oriented energies, subset inclusion histogram comparison and event-driven processing

Andrei Zaharescu, Richard Wildes

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Tags: Computer science, Computer vision, nVidia, nVidia GeForce GTX 280, OpenCL

September 14, 2011 by hgpu

Seeing through the fog: an algorithm for fast and accurate touch detection in optical tabletop surfaces

Christopher Wolfe, T. C. Nicholas Graham, Joseph A. Pape

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Tags: Algorithms, Computer science, nVidia, nVidia GeForce 9600 GT, OpenGL, Sensing

September 14, 2011 by hgpu

MegaTrain: Full Precision Training of 100B+ Parameter Large Language Models on a Single GPU

Device Virtual Machine (DVM)

DVM: Real-Time Kernel Generation for Dynamic AI Models

Agentic Code Optimization via Compiler-LLM Cooperation

AutoKernel: Autoresearch for GPU kernels. Give it any PyTorch model, go to sleep, wake up to optimized Triton kernels

AutoKernel: Autonomous GPU Kernel Optimization via Iterative Agent-Driven Search

Triton-Sanitizer: A Fast and Device-Agnostic Memory Sanitizer for Triton with Rich Diagnostic Context

LLM.Q: Quantized LLM training in pure CUDA/C++

LLMQ: Efficient Lower-Precision LLM Training for Consumer GPUs

SOL-ExecBench: Speed-of-Light Benchmarking for Real-World GPU Kernels Against Hardware Limits

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high performance computing on graphics processing units: hgpu.org

Processing data streams with hard real-time constraints on heterogeneous systems

Performing with CUDA

Fast Mersenne prime testing on the GPU

Scaling Lattice QCD beyond 100 GPUs

Ambient occlusion volumes

Auto-tuning of fast fourier transform on graphics processors

Shadowfax: scaling in heterogeneous cluster systems via GPGPU assemblies

OptiX: a general purpose ray tracing engine

Nikola: embedding compiled GPU functions in Haskell

A practical approach of curved ray prestack Kirchhoff Time Migration on GPGPU

Anomalous behaviour detection using spatiotemporal oriented energies, subset inclusion histogram comparison and event-driven processing

Seeing through the fog: an algorithm for fast and accurate touch detection in optical tabletop surfaces

Recent source codes

MegaTrain: Full Precision Training of 100B+ Parameter Large Language Models on a Single GPU

Device Virtual Machine (DVM)

Agentic Code Optimization via Compiler-LLM Cooperation

AutoKernel: Autoresearch for GPU kernels. Give it any PyTorch model, go to sleep, wake up to optimized Triton kernels

Triton-Sanitizer: A Fast and Device-Agnostic Memory Sanitizer for Triton with Rich Diagnostic Context

LLM.Q: Quantized LLM training in pure CUDA/C++

SOL-ExecBench: Speed-of-Light Benchmarking for Real-World GPU Kernels Against Hardware Limits

True 4-Bit Quantized CNN Training on CPU

cuFuzz: A GPU-oriented coverage-guided fuzzer for userland CUDA application

KernelSkill: A Multi-Agent Framework for GPU Kernel Optimization

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