high performance computing on graphics processing units: hgpu.org

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hgpu.org » Applications » Computer science

Toolchain for programming, simulating and studying the XMT many-core architecture

Fuat Keceli, Alexandros Tzannes, George C. Caragea, Rajeev Barua, Uzi Vishkin

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Tags: Algorithms, Compilers, Computer science, Hardware Architecture, nVidia, nVidia GeForce GTX 280, Package

December 24, 2011 by hgpu

High Performance and Scalable Radix Sorting: A case study of implementing dynamic parallelism for GPU computing

Duane Merrill, Andrew Grimshaw

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 285, Package, Sorting

December 24, 2011 by hgpu

Efficient Use of In-Game Ray-Tracing Techniques

Thales Luis Rodrigues Sabino, Paulo Andrade, Lucas Grassano Lattari, Esteban Clua, Anselmo Montenegro, Paulo Aristarco Pagliosa

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Tags: 3D Graphics and Realism, Computer science, CUDA, Games, GLSL, Image generation, nVidia, nVidia GeForce 9800 GTX, OpenGL, Raytracing, Rendering

December 24, 2011 by hgpu

Sorting on GPUs for large scale datasets: A thorough comparison

Gabriele Capannini, Fabrizio Silvestri, Ranieri Baraglia

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce 8800 GT, Sorting

December 24, 2011 by hgpu

An Experiment in Parallelizing the Fast Fourier Transform

Timothy W. O'Neil, Ameen B. Mirza, Dale H. Mugler

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Tags: Algorithms, Computer science, CUDA, FFT, MPI, nVidia

December 24, 2011 by hgpu

Using Artificial Intelligence in Computational Games

Carlos A. B. C. W. Madsen, Diana F. Adamatti

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Tags: Artificial intelligence, Computer science, CUDA, Games, nVidia

December 24, 2011 by hgpu

GPU-based parallel computing for the simulation of complex multibody systems with unilateral and bilateral constraints: an overview

Alessandro Tasora, Dan Negrut, Mihai Anitescu

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Tags: Algorithms, Collision detection, Computer science, CUDA, nVidia, Overview, Tesla C1060

December 23, 2011 by hgpu

SIMD Floating Point Extension for Ray Tracing

Yunus Okmen

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia Quadro FX 4000, Raytracing, Thesis

December 23, 2011 by hgpu

Reducing the Size of Nurbs Controls Nets Using Genetic Algorithms and CUDA

Matthew J. O'Neal, Cameron J. Turner

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Tags: Algorithms, Clustering, Computer science, CUDA, nVidia, Programming techniques

December 23, 2011 by hgpu

Survey on Benchmarks for a GPU Based Multi Camera Stereo Matching Algorithm

Klaus Denker, Georg Umlauf

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Tags: Algorithms, Benchmarking, Computer science, Computer vision, GLSL, OpenGL

December 23, 2011 by hgpu

GPU Pathfinding Optimization

Adonis Silva, Fernando Rocha, Artur Santos, Geber Ramalho, Veronica Teichrieb

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Tags: Computer science, CUDA, Games, nVidia, nVidia GeForce GTS 360 M, Optimization, Path problems

December 23, 2011 by hgpu

Using Image Morphing for Memory-Efficient Impostor Rendering on GPU

Kamer Ali Yuksel, Aytul Ercil, Alp Yucebilgin, Selim Balcisoy

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Tags: Computer science, GLSL, nVidia, nVidia GeForce GTX 460, OpenGL, Real-time graphics, Rendering

December 23, 2011 by hgpu

MATLAB Tensor Core models

Accurate Models of NVIDIA Tensor Cores

TritonForge: Transform PyTorch Operations into Optimized GPU Kernels with LLMs

TritonForge: Profiling-Guided Framework for Automated Triton Kernel Optimization

RLTune: Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

tritonBLAS: A Lightweight Triton-based General Matrix Multiplication (GEMM) Library

tritonBLAS: Triton-based Analytical Approach for GEMM Kernel Parameter Selection

hls4ml: Machine learning on FPGAs using HLS

hls4ml: A Flexible, Open-Source Platform for Deep Learning Acceleration on Reconfigurable Hardware

NVIDIA Nemotron Parse 1.1

ThunderKittens: Tile primitives for speedy kernels

ParallelKittens: Systematic and Practical Simplification of Multi-GPU AI Kernels

Iris: AMD RAD's multi-GPU Triton-based framework for seamless multi-GPU programming

Iris: First-Class Multi-GPU Programming Experience in Triton

HipKittens: Fast and Furious AMD Kernels

Fortran xDSL dialects

An MLIR pipeline for offloading Fortran to FPGAs via OpenMP

See all packages

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high performance computing on graphics processing units: hgpu.org

Applications

Toolchain for programming, simulating and studying the XMT many-core architecture

High Performance and Scalable Radix Sorting: A case study of implementing dynamic parallelism for GPU computing

Efficient Use of In-Game Ray-Tracing Techniques

Sorting on GPUs for large scale datasets: A thorough comparison

An Experiment in Parallelizing the Fast Fourier Transform

Using Artificial Intelligence in Computational Games

GPU-based parallel computing for the simulation of complex multibody systems with unilateral and bilateral constraints: an overview

SIMD Floating Point Extension for Ray Tracing

Reducing the Size of Nurbs Controls Nets Using Genetic Algorithms and CUDA

Survey on Benchmarks for a GPU Based Multi Camera Stereo Matching Algorithm

GPU Pathfinding Optimization

Using Image Morphing for Memory-Efficient Impostor Rendering on GPU

Recent source codes

MATLAB Tensor Core models

TritonForge: Transform PyTorch Operations into Optimized GPU Kernels with LLMs

RLTune: Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

tritonBLAS: A Lightweight Triton-based General Matrix Multiplication (GEMM) Library

hls4ml: Machine learning on FPGAs using HLS

NVIDIA Nemotron Parse 1.1

ThunderKittens: Tile primitives for speedy kernels

Iris: AMD RAD's multi-GPU Triton-based framework for seamless multi-GPU programming

HipKittens: Fast and Furious AMD Kernels

Fortran xDSL dialects

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