high performance computing on graphics processing units: hgpu.org

Programming

hgpu.org » Programming

Image Space Gathering

Austin Robison, Peter Shirley

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Tags: 3D Graphics and Realism, Algorithms, Cg, Computer science, nVidia, nVidia Quadro FX 5800, OpenGL

February 12, 2011 by hgpu

Spatial splits in bounding volume hierarchies

Martin Stich, Heiko Friedrich, Andreas Dietrich

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Tags: 3D Graphics and Realism, Computer science, CUDA, nVidia, nVidia GeForce GTX 280, Raytracing

February 12, 2011 by hgpu

Understanding the efficiency of ray traversal on GPUs

Timo Aila, Samuli Laine

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Tags: 3D Graphics and Realism, Computer science, CUDA, Image generation, nVidia, nVidia GeForce GTX 285, Raytracing

February 12, 2011 by hgpu

A meshless hierarchical representation for light transport

Jaakko Lehtinen, Matthias Zwicker, Emmanuel Turquin, Janne Kontkanen, Fredo Durand, Francois Sillion, and Timo Aila

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Tags: Algorithms, Image processing, nVidia, nVidia GeForce 8800 Ultra, Rendering

February 12, 2011 by hgpu

Loop Transformation Recipes for Code Generation and Auto-Tuning

Mary Hall, Jacqueline Chame, Chun Chen, Jaewook Shin, Gabe Rudy, Malik Khan

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Tags: Code generation, Compilers, Computer science, CUDA, nVidia, OpenMP

February 12, 2011 by hgpu

Automated Dynamic Analysis of CUDA Programs

Michael Boyer, Kevin Skadron, Westley Weimer

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Tags: Computer science, CUDA, nVidia, Optimization, Performance

February 12, 2011 by hgpu

Compiling an Array Language to a Graphics Processor

Bradford Larsen

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Tags: Computer science, CUDA, High-level Languages, nVidia, nVidia GeForce 8800 GT, Thesis

February 11, 2011 by hgpu

The fast multipole method on parallel clusters, multicore processors, and graphics processing units

Eric Darve, Cris Cecka, Toru Takahashi

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Tags: Algorithms, CUDA, Fast multipole method, Fluid dynamics, nVidia, Tesla C1060, Tesla S1070

February 11, 2011 by hgpu

Comparing CUDA and OpenGL implementations for a Jacobi iteration

Ronan Amorim, Gundolf Haase, Manfred Liebmann, Rodrigo Weber dos Santos

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Tags: Computer science, CUDA, GLSL, nVidia, nVidia GeForce 8600 GT, nVidia GeForce 8800 GT, nVidia GeForce GTX 280, OpenGL, Performance

February 11, 2011 by hgpu

Comparison of several parallel API for cloth modelling on modern GPUs

Tzvetomir Ivanov Vassilev

Tags: Computer science, CUDA, GLSL, nVidia, OpenCL, OpenGL, Performance

February 11, 2011 by hgpu

Energy-efficient algorithms

Susanne Albers

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Tags: Algorithms, Computer science, Energy-efficient computing, Green, Review

February 11, 2011 by hgpu

GPU-accelerated indirect boundary element method for voxel model analyses with fast multipole method

Shoji Hamada

Tags: CUDA, Electrodynamics, Fast multipole method, Laplace and Poisson equation, nVidia, nVidia GeForce GTX 295, Physics

February 11, 2011 by hgpu

GEAK-agent: LLM-based AI agent, which can write correct and efficient GPU kernels automatically

Geak: Introducing Triton Kernel AI Agent & Evaluation Benchmarks

OpenDwarfs 2025: re-engineered version of the OpenDwarfs benchmark suite, for compatibility with modern platforms

OpenDwarfs 2025: Modernizing the OpenDwarfs Benchmark Suite for Heterogeneous Computing

Specx: Speculative task-based runtime system

Specx: a C++ task-based runtime system for heterogeneous distributed architectures

Mutual-Supervised Learning for Sequential-to-Parallel Code Translation

Hardware Compute Partitioning on NVIDIA GPUs for Composable Systems

KISim: Kubernetes Intelligent Scheduling Simulator

KIS-S: A GPU-Aware Kubernetes Inference Simulator with RL-Based Auto-Scaling

Efficient GPU Implementation of Multi-Precision Integer Division

exa-AMD: Exascale Accelerated Materials Discovery

Accelerated discovery and design of Fe-Co-Zr magnets with tunable magnetic anisotropy through machine learning and parallel computing

ParEval: A Parallel Code Evaluation Benchmark

ParEval-Repo: A Benchmark Suite for Evaluating LLMs with Repository-level HPC Translation Tasks

FlashSparse: Minimizing Computation Redundancy for Fast Sparse Matrix Multiplications on Tensor Cores

Libra: Synergizing CUDA and Tensor Cores for High-Performance Sparse Matrix Multiplication

See all packages

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high performance computing on graphics processing units: hgpu.org

Programming

Image Space Gathering

Spatial splits in bounding volume hierarchies

Understanding the efficiency of ray traversal on GPUs

A meshless hierarchical representation for light transport

Loop Transformation Recipes for Code Generation and Auto-Tuning

Automated Dynamic Analysis of CUDA Programs

Compiling an Array Language to a Graphics Processor

The fast multipole method on parallel clusters, multicore processors, and graphics processing units

Comparing CUDA and OpenGL implementations for a Jacobi iteration

Comparison of several parallel API for cloth modelling on modern GPUs

Energy-efficient algorithms

GPU-accelerated indirect boundary element method for voxel model analyses with fast multipole method

Recent source codes

GEAK-agent: LLM-based AI agent, which can write correct and efficient GPU kernels automatically

OpenDwarfs 2025: re-engineered version of the OpenDwarfs benchmark suite, for compatibility with modern platforms

Specx: Speculative task-based runtime system

Mutual-Supervised Learning for Sequential-to-Parallel Code Translation

Hardware Compute Partitioning on NVIDIA GPUs for Composable Systems

KISim: Kubernetes Intelligent Scheduling Simulator

Efficient GPU Implementation of Multi-Precision Integer Division

exa-AMD: Exascale Accelerated Materials Discovery

ParEval: A Parallel Code Evaluation Benchmark

FlashSparse: Minimizing Computation Redundancy for Fast Sparse Matrix Multiplications on Tensor Cores

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