high performance computing on graphics processing units: hgpu.org

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Transform Coding for Hardware-accelerated Volume Rendering

Nathaniel Fout, Kwan-Liu Ma

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Tags: Computer science, nVidia, nVidia GeForce 8800 GTX, Real-time graphics, Rendering

January 11, 2011 by hgpu

Automated image alignment for 2D gel electrophoresis in a high-throughput proteomics pipeline

Andrew W. Dowsey, Michael J. Dunn, Guang-Zhong Z. Yang

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Tags: Bioinformatics, Biology, Cg, Image alignment, nVidia, nVidia GeForce 6800 Ultra, Package

January 11, 2011 by hgpu

Exploring new architectures in accelerating CFD for Air Force applications

Jack Dongarra, Shirley Moore, Gregory Peterson, Stanimire Tomov

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Tags: Algorithms, Fluid dynamics, FPGA, nVidia, nVidia Quadro FX 5600, Tesla T10P

January 11, 2011 by hgpu

SCELib3.0: The new revision of SCELib, the parallel computational library of molecular properties in the Single Center Approach

N. Sanna, I. Baccarelli, G. Morelli

Tags: Biology, Chemistry, CUDA, Molecular modeling, nVidia

January 11, 2011 by hgpu

iNFAnt: NFA pattern matching on GPGPU devices

Niccolo' Cascarano, Pierluigi Rolando, Fulvio Risso, Riccardo Sisto

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Tags: Computer science, CUDA, Networks, nVidia, nVidia GeForce GTX 260, String matching

January 11, 2011 by hgpu

Accelerating linpack with CUDA on heterogenous clusters

Massimiliano Fatica

Tags: Computer science, CUDA, GPU cluster, Linear Algebra, nVidia

January 11, 2011 by hgpu

CUDA-based real time surgery simulation

Youquan Liu, Suvranu De

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Tags: CUDA, Medicine, nVidia, nVidia GeForce 8800 GTX, Surgical simulation

January 11, 2011 by hgpu

Fast binding site mapping using GPUs and CUDA

Bharat Sukhwani, Martin C. Herbordt

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Tags: Bioinformatics, Biology, CUDA, Molecular dynamics, nVidia, Tesla C1060

January 11, 2011 by hgpu

Quality-score guided error correction for short-read sequencing data using CUDA

Haixiang Shi, Bertil Schmidt, Weiguo Liu, Wolfgang Muller-Wittig

Tags: Bioinformatics, Biology, CUDA, Error recovery, Genetics, nVidia

January 11, 2011 by hgpu

High-speed volume ray casting with CUDA

L. Marsalek, A. Hauber, P. Slusallek

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Tags: Computer science, CUDA, nVidia, Poster, Real-time graphics

January 10, 2011 by hgpu

Parallel drainage network computation on CUDA

L. Ortega, A. Rueda

Tags: CUDA, Earth and Space Sciences, Geoscience, nVidia

January 10, 2011 by hgpu

Canny edge detection on NVIDIA CUDA

Yuancheng Luo, Ramani Duraiswami

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Tags: Computer vision, CUDA, Image processing, nVidia, nVidia GeForce 8800 GTX, Package

January 10, 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

Transform Coding for Hardware-accelerated Volume Rendering

Automated image alignment for 2D gel electrophoresis in a high-throughput proteomics pipeline

Exploring new architectures in accelerating CFD for Air Force applications

SCELib3.0: The new revision of SCELib, the parallel computational library of molecular properties in the Single Center Approach

iNFAnt: NFA pattern matching on GPGPU devices

Accelerating linpack with CUDA on heterogenous clusters

CUDA-based real time surgery simulation

Fast binding site mapping using GPUs and CUDA

Quality-score guided error correction for short-read sequencing data using CUDA

High-speed volume ray casting with CUDA

Parallel drainage network computation on CUDA

Canny edge detection on NVIDIA CUDA

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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