high performance computing on graphics processing units: hgpu.org

Programming

hgpu.org » Programming » CUDA

Four styles of parallel and net programming

Zhiwei Xu, Yongqiang He, Wei Lin, Li Zha

Tags: Computer science, CUDA, MapReduce, nVidia, Programming techniques

January 8, 2011 by hgpu

GPUMCD: a new GPU-oriented Monte Carlo dose calculation platform

Sami Hissoiny, Hugo Bouchard, Benoit Ozell, Philippe Despres

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Tags: CUDA, Medical Physics, Medicine, Monte Carlo simulation, nVidia, nVidia GeForce GTX 480, Radiotherapy

January 8, 2011 by hgpu

Parallel algorithms to a parallel hardware: Designing vision algorithms for a GPU

Jun-Sik Kim, Myung Hwangbo, Takeo Kanade

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Tags: Computer science, Computer vision, CUDA, nVidia, nVidia GeForce 8800 GTX, Optical flow

January 8, 2011 by hgpu

A Unified Runtime System for Heterogeneous Multi-core Architectures

Cedric Augonnet, Raymond Namyst

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Tags: Computer science, CUDA, Heterogeneous systems, Memory, nVidia, nVidia Quadro FX 4600

January 7, 2011 by hgpu

JCUDA: A Programmer-Friendly Interface for Accelerating Java Programs with CUDA

Yonghong Yan, Max Grossman, Vivek Sarkar

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Tags: Computer science, CUDA, Java, nVidia, Package, Tesla C1060

January 7, 2011 by hgpu

Power Consumption of GPUs from a Software Perspective

Sylvain Collange, David Defour, Arnaud Tisserand

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Tags: Computer science, CUDA, Energy-efficient computing, nVidia, nVidia GeForce 9800 GX2, Tesla C870, Tesla D870, Tesla T10P

January 7, 2011 by hgpu

Fast BVH Construction on GPUs

C. Lauterbach, M. Garland, S. Sengupta, D. Luebke, D. Manocha

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Tags: Collision detection, Computer science, CUDA, nVidia, nVidia GeForce GTX 280, Raytracing

January 7, 2011 by hgpu

Accelerating phase unwrapping and affine transformations for optical quadrature microscopy using CUDA

Perhaad Mistry, Sherman Braganza, David Kaeli, Miriam Leeser

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Tags: Biology, CUDA, Genetics, Image processing, nVidia, nVidia GeForce 8800 GTX

January 6, 2011 by hgpu

Synthetic Aperture Radar Processing with GPGPU

Maurizio di Bisceglie, Michele Di Santo, Carmela Galdi, Riccardo Lanari, Nadia Ranaldo

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Tags: CUDA, nVidia, Signal processing, Tesla C1060

January 6, 2011 by hgpu

An asymmetric distributed shared memory model for heterogeneous parallel systems

Isaac Gelado, John E. Stone, Javier Cabezas, Sanjay Patel, Nacho Navarro, Wen-mei W. Hwu

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Tags: Computer science, CUDA, Memory, Memory model, nVidia, nVidia GeForce GTX 280

January 6, 2011 by hgpu

Efficient gather and scatter operations on graphics processors

Bingsheng He, Naga K. Govindaraju, Qiong Luo, Burton Smith

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce 8800, Search, Sorting, Sparse matrix

January 6, 2011 by hgpu

q-state Potts model metastability study using optimized GPU-based Monte Carlo algorithms

Ezequiel E. Ferrero, Juan Pablo De Francesco, Nicolas Wolovick, Sergio A. Cannas

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Tags: Computational Physics, CUDA, Monte Carlo simulation, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 470, nVidia GeForce GTX 480, Package, Physics, Statistical Mechanics

January 6, 2011 by hgpu

Agentic Code Optimization via Compiler-LLM Cooperation

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

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

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

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

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high performance computing on graphics processing units: hgpu.org

Programming

Four styles of parallel and net programming

GPUMCD: a new GPU-oriented Monte Carlo dose calculation platform

Parallel algorithms to a parallel hardware: Designing vision algorithms for a GPU

A Unified Runtime System for Heterogeneous Multi-core Architectures

JCUDA: A Programmer-Friendly Interface for Accelerating Java Programs with CUDA

Power Consumption of GPUs from a Software Perspective

Fast BVH Construction on GPUs

Accelerating phase unwrapping and affine transformations for optical quadrature microscopy using CUDA

Synthetic Aperture Radar Processing with GPGPU

An asymmetric distributed shared memory model for heterogeneous parallel systems

Efficient gather and scatter operations on graphics processors

q-state Potts model metastability study using optimized GPU-based Monte Carlo algorithms

Recent source codes

Agentic Code Optimization via Compiler-LLM Cooperation

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

Device Virtual Machine (DVM)

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

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

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

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

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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