high performance computing on graphics processing units: hgpu.org

Programming

The Scalable Heterogeneous Computing (SHOC) benchmark suite

Anthony Danalis,Gabriel Marin,Collin McCurdy,Jeremy S. Meredith,Philip C. Roth,Kyle Spafford,Vinod Tipparaju,Jeffrey S. Vetter

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Source codes

Tags: ATI, ATI Radeon HD 5770, ATI Radeon HD 5870, ATI Stream, Benchmarking, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce 8800 GT, nVidia GeForce 8800 GTS, nVidia GeForce 8800 GTX, nVidia GeForce 9400 M, OpenCL, Package, Performance, Tesla C1060

November 5, 2010 by hgpu

A Performance Comparison of CUDA and OpenCL

Kamran Karimi, Neil G. Dickson, Firas Hamze

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Tags: Computational Physics, Computer science, CUDA, nVidia, nVidia GeForce GTX 260, OpenCL, Package, Performance

November 5, 2010 by hgpu

Optimal loop unrolling for GPGPU programs (thesis)

Giridhar S. Murthy

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Tags: Computer science, CUDA, nVidia, nVidia GeForce 8800 GTX, nVidia GeForce GTX 280, OpenCL, Review, Thesis

November 3, 2010 by hgpu

Optimal loop unrolling for GPGPU programs

Giridhar S. Murthy, Mahesh Ravishankar, Muthu M. Baskaran, P. Sadayappan

Tags: Computer science, CUDA, nVidia, nVidia GeForce 8800 GTX, nVidia GeForce GTX 280, OpenCL, Review

November 3, 2010 by hgpu

GPU packet classification using OpenCL: a consideration of viable classification methods

Alastair Nottingham, Barry Irwin

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Tags: Algorithms, Computer science, nVidia, OpenCL

October 28, 2010 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

Programming

The Scalable Heterogeneous Computing (SHOC) benchmark suite

A Performance Comparison of CUDA and OpenCL

Optimal loop unrolling for GPGPU programs (thesis)

Optimal loop unrolling for GPGPU programs

GPU packet classification using OpenCL: a consideration of viable classification methods

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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