high performance computing on graphics processing units: hgpu.org

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Hierarchical Exploration of Volumes Using Multilevel Segmentation of the Intensity-Gradient Histograms

Cheuk Yiu Ip

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 260, Visualization

October 20, 2012 by hgpu

Empirical analysis of a parallel data mining algorithm on a graphic processor

Davide Berdin

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Tags: Computer science, CUDA, Data mining, Data parallelism, nVidia, nVidia GeForce GTX 580, Thesis

October 20, 2012 by hgpu

A short guide to CUDA C: For physicists with multi-core graphics cards

David Plotzki

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Tags: Computational Physics, Computer science, CUDA, nVidia, nVidia Quadro NVS 3100 M, Package, Physics, Tesla C1060, Tutorial

October 19, 2012 by hgpu

A Modular Framework for Deformation and Fracture using GPU Shaders

Derek John Morris, Eike Falk Anderson, Christopher Peters

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Tags: 3D Graphics and Realism, ATI, ATI Radeon HD 4870 X2, Computer science, DirectX, HLSL, nVidia, nVidia GeForce GT 230 M

October 19, 2012 by hgpu

A Hybrid CPU/GPU Cluster for Encryption and Decryption of Large Amounts of Data

Ewa Niewiadomska-Szynkiewicz, Michal Marks, Jaroslaw Jantura, Mikolaj Podbielski

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Tags: ATI, ATI FirePro V7800, ATI Radeon HD 6970, Computer science, Distributed computing, GPU cluster, nVidia, OpenCL, Security, Tesla M2050

October 19, 2012 by hgpu

A Novel Learning Algorithm for Bayesian Network and Its Efficient Implementation on GPU

Yu Wang, Weikang Qian, Shuchang Zhang, Bo Yuan

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Tags: Algorithms, Bayesian, Computational Complexity, Computer science, CUDA, nVidia, Tesla M2090

October 19, 2012 by hgpu

Comparative Evaluation of Binary Features

Jared Heinly, Enrique Dunn, Jan-Michael Frahm

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Tags: Computer science, Computer vision, nVidia, nVidia GeForce GTX 285

October 18, 2012 by hgpu

Computing Reachable Sets via Barrier Methods on SIMD Architectures

Lars Grune, Thomas U. Jahn

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Tags: Algorithms, CUDA, Linear Algebra, Mathematics, nVidia, ODEs, Ordinary differential equations

October 18, 2012 by hgpu

Strain Visualization of Ultra Sound Signals Processed by General Purpose Graphic Process Unit

Luis Alvarez

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Tags: CUDA, Image processing, nVidia, nVidia Quadro FX 600, Signal processing, Thesis, Ultrasound, Visualization

October 18, 2012 by hgpu

GPU-based Batched Spatial Query Processing on R-Trees

Simin You, Jianting Zhang

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Tags: Computer science, CUDA, Databases, Graph theory, nVidia, nVidia Quadro FX 6000

October 18, 2012 by hgpu

Platform-independent parallelization of the Lattice Boltzmann method with OpenCL

Carolin Wolf

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Tags: Algorithms, ATI, ATI Mobility Radeon HD 5470, ATI Radeon HD 4870, Fluid dynamics, Lattice Boltzmann model, nVidia, OpenCL, Tesla M1060, Thesis

October 17, 2012 by hgpu

Design and Performance Evaluation of a Software Framework for Multi-Physics Simulations on Heterogeneous Supercomputers

Christian Feichtinger

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Tags: CUDA, Fluid dynamics, GPU cluster, Heterogeneous systems, Lattice Boltzmann model, MPI, Numerical simulation, nVidia, Tesla M2050, Tesla M2070, Thesis

October 17, 2012 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

Hierarchical Exploration of Volumes Using Multilevel Segmentation of the Intensity-Gradient Histograms

Empirical analysis of a parallel data mining algorithm on a graphic processor

A short guide to CUDA C: For physicists with multi-core graphics cards

A Modular Framework for Deformation and Fracture using GPU Shaders

A Hybrid CPU/GPU Cluster for Encryption and Decryption of Large Amounts of Data

A Novel Learning Algorithm for Bayesian Network and Its Efficient Implementation on GPU

Comparative Evaluation of Binary Features

Computing Reachable Sets via Barrier Methods on SIMD Architectures

Strain Visualization of Ultra Sound Signals Processed by General Purpose Graphic Process Unit

GPU-based Batched Spatial Query Processing on R-Trees

Platform-independent parallelization of the Lattice Boltzmann method with OpenCL

Design and Performance Evaluation of a Software Framework for Multi-Physics Simulations on Heterogeneous Supercomputers

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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