high performance computing on graphics processing units: hgpu.org

Applications

hgpu.org » Applications

A GPU accelerated algorithm for 3D Delaunay triangulation

Thanh-Tung Cao, Ashwin Nanjappa, Mingcen Gao, Tiow-Seng Tan

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Tags: Algorithms, Computational Geometry, Computer science, CUDA, nVidia, nVidia GeForce GTX 580, Package

January 30, 2014 by hgpu

A Detailed GPU Cache Model Based on Reuse Distance Theory

Cedric Nugteren, Gert-Jan van den Braak, Henk Corporaal, Henri Bal

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Tags: Computer science, CUDA, GPGPU-sim, Hardware Architecture, nVidia, nVidia GeForce GTX 470, Package

January 29, 2014 by hgpu

Autotuning Programs with Algorithmic Choice

Jason Ansel

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Tags: Algorithms, ATI, ATI Radeon HD 6630 M, Computer science, nVidia, OpenCL, Package, Performance, Tesla C2070, Thesis

January 28, 2014 by hgpu

Optimizing Stencil Computations for NVIDIA Kepler GPUs

Naoya Maruyama, Takayuki Aoki

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Tags: Computer science, CUDA, Numerical Analysis, nVidia, Package, Tesla K20, Tesla M2075

January 26, 2014 by hgpu

clpeak – peak performance of your opencl device

Krishnaraj Bhat

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Tags: ATI, Benchmarking, Computer science, nVidia, OpenCL, Package, Performance

January 23, 2014 by hgpu

A comparison between parallelization approaches in molecular dynamics simulations on GPUs

Lorenzo Rovigatti, Petr Sulc, Istvan Z. Reguly, Flavio Romano

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Tags: Computational Physics, CUDA, Molecular dynamics, nVidia, Package, Physics, Soft Condensed Matter, Tesla C2070, Tesla K10, Tesla K20

January 23, 2014 by hgpu

GPU Accelerated Vessel Segmentation Using Laplacian Eigenmaps

Lin Cheng, Hyunsu Cho, Peter A. Yoon

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Tags: CUDA, Image processing, nVidia, Package, Tesla K20

January 17, 2014 by hgpu

VertexAPI2 – A Vertex-Program API for Large Graph Computations on the GPU

Erich Elsen, Vishal Vaidyanathan

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Tags: Algorithms, Computer science, CUDA, Graph theory, nVidia, nVidia GeForce GTX 670, Package

January 16, 2014 by hgpu

Adaptation of an acoustic propagation model to the parallel architecture of a graphics processor

Emanuel Ey

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Tags: Acoustics, Algorithms, Earth and Space Sciences, nVidia, nVidia GeForce GTX 580, OpenCL, Package, Raytracing, Thesis

January 14, 2014 by hgpu

Towards Portable Performance for Explicit Hydrodynamics Codes

A. C. Mallinson, D. A. Beckingsale, W. P. Gaudin, J. A. Herdman, S. A. Jarvis

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Tags: APU, ATI, ATI FirePro V7800, Computer science, Fluid dynamics, MPI, nVidia, OpenCL, Package, Performance, Tesla K20

January 14, 2014 by hgpu

k+-buffer: Fragment Synchronized k-buffer

Andreas A. Vasilakis, Ioannis Fudos

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Tags: Algorithms, Computer science, nVidia, nVidia GeForce GTX 480, OpenGL, Package, Real-time graphics, Rendering, Visualization

January 14, 2014 by hgpu

A Framework for Productive, Efficient and Portable Parallel Computing

Ekaterina I. Gonina

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Tags: Algorithms, Code generation, Computer science, CUDA, MapReduce, nVidia, nVidia GeForce GTX 480, Package, Python, Thesis

January 12, 2014 by hgpu

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

True 4-Bit Quantized CNN Training on CPU

True 4-Bit Quantized Convolutional Neural Network Training on CPU: Achieving Full-Precision Parity

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

Hunting CUDA Bugs at Scale with cuFuzz

KernelSkill: A Multi-Agent Framework for GPU Kernel Optimization

MSKernelBench & CUDAMaster

Making LLMs Optimize Multi-Scenario CUDA Kernels Like Experts

EvoScientist: Harness Vibe Research with Self-evolving AI Scientists

EvoScientist: Towards Multi-Agent Evolving AI Scientists for End-to-End Scientific Discovery

RepoLaunch: Automating Build and Test Pipeline of Code Repositories on ANY Language and ANY Platform

RepoLaunch: Automating Build & Test Pipeline of Code Repositories on ANY Language and ANY Platform

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high performance computing on graphics processing units: hgpu.org

Applications

A GPU accelerated algorithm for 3D Delaunay triangulation

A Detailed GPU Cache Model Based on Reuse Distance Theory

Autotuning Programs with Algorithmic Choice

Optimizing Stencil Computations for NVIDIA Kepler GPUs

clpeak – peak performance of your opencl device

A comparison between parallelization approaches in molecular dynamics simulations on GPUs

GPU Accelerated Vessel Segmentation Using Laplacian Eigenmaps

VertexAPI2 – A Vertex-Program API for Large Graph Computations on the GPU

Adaptation of an acoustic propagation model to the parallel architecture of a graphics processor

Towards Portable Performance for Explicit Hydrodynamics Codes

k+-buffer: Fragment Synchronized k-buffer

A Framework for Productive, Efficient and Portable Parallel Computing

Recent source codes

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

MSKernelBench & CUDAMaster

EvoScientist: Harness Vibe Research with Self-evolving AI Scientists

RepoLaunch: Automating Build and Test Pipeline of Code Repositories on ANY Language and ANY Platform

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