high performance computing on graphics processing units: hgpu.org

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Exploiting Coarse-grained Parallelism in B+ Tree Searches on an APU

Mayank Daga, Mark Nutter

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Tags: APU, ATI, ATI Radeon HD 7660, ATI Radeon HD 7970, Computer science, Databases, Heterogeneous systems, OpenCL

November 18, 2012 by hgpu

Parallel implementations of the MinMin heterogeneous computing scheduler in GPU

Mauro Canabe, Sergio Nesmachnow

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, Task scheduling, Tesla C1060

November 16, 2012 by hgpu

Accelerating Fully Homomorphic Encryption Using GPU

Wei Wang, Yin Hu, Lianmu Chen, Xinming Huang, Berk Sunar

Tags: Algorithms, Computer science, CUDA, FFT, nVidia, Security, Tesla C2050

November 16, 2012 by hgpu

Computer Vision and Image Segmentation Implemented on GPU Using Compute Unified Device Architecture as Applied on Quality Inspection of Pre-etched Printed Circuit Board

Philip Virgil Astillo, Van Patiluna

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Tags: Computer science, Computer vision, CUDA, Image processing, nVidia

November 16, 2012 by hgpu

Device specialization in heterogeneous multi-GPU environments

Gabriele Cocco, Antonio Cisternino

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Tags: AMD Fusion, ATI, ATI IL, ATI Radeon HD 5870, Computer science, GPU cluster, Heterogeneous systems, Task scheduling

November 15, 2012 by hgpu

Resolving the conflict between generality and plausibility in verified computation

Srinath Setty, Benjamin Braun, Victor Vu, Andrew J. Blumberg, Bryan Parno, Michael Walfish

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Tags: Computer science, CUDA, nVidia, Security, Tesla M2070

November 15, 2012 by hgpu

Accelerating the Gillespie Exact Stochastic Simulation Algorithm Using Hybrid Parallel Execution on Graphics Processing Units

Ivan Komarov, Roshan M. D'Souza

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Tags: Computer science, Differential equations, nVidia, nVidia GeForce GTX 480, Stochastic simulation

November 15, 2012 by hgpu

Load Balanced Parallel GPU Out-of-Core for Continuous LOD Model Visualization

Chao Peng, Peng Mi, Yong Cao

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 580, OpenGL, Rendering, Visualization

November 14, 2012 by hgpu

Performance modeling of atomic additions on GPU scratchpad memory

Juan Gomez-Luna, Jose Maria Gonzalez-Linares, Jose Ignacio Benavides, Nicolas Guil

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Tags: Clustering, Computer science, CUDA, nVidia, nVidia GeForce GTX 580, Optimization

November 14, 2012 by hgpu

A simple method to accelerate fringe analysis algorithms based on graphics processing unit and MATLAB

Wenjing Gao, Qian Kemao

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Tags: Algorithms, Computer science, CUDA, FFT, nVidia, nVidia GeForce GTX 285

November 14, 2012 by hgpu

Correctly rounding elementary functions on GPU

Pierre Fortin, Mourad Gouicem, Stef Graillat

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Tags: Algorithms, Computer science, CUDA, Elementary functions, nVidia, Tesla C2070

November 14, 2012 by hgpu

Efficient similarity search on multimedia databases

Mariela Lopresti, Natalia Miranda, Fabiana Piccoli, Nora Reyes

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Tags: Computer science, CUDA, Data mining, Databases, nVidia, nVidia GeForce GTX 330 M, nVidia GeForce GTX 470, nVidia GeForce GTX 550 Ti

November 14, 2012 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

Exploiting Coarse-grained Parallelism in B+ Tree Searches on an APU

Parallel implementations of the MinMin heterogeneous computing scheduler in GPU

Accelerating Fully Homomorphic Encryption Using GPU

Computer Vision and Image Segmentation Implemented on GPU Using Compute Unified Device Architecture as Applied on Quality Inspection of Pre-etched Printed Circuit Board

Device specialization in heterogeneous multi-GPU environments

Resolving the conflict between generality and plausibility in verified computation

Accelerating the Gillespie Exact Stochastic Simulation Algorithm Using Hybrid Parallel Execution on Graphics Processing Units

Load Balanced Parallel GPU Out-of-Core for Continuous LOD Model Visualization

Performance modeling of atomic additions on GPU scratchpad memory

A simple method to accelerate fringe analysis algorithms based on graphics processing unit and MATLAB

Correctly rounding elementary functions on GPU

Efficient similarity search on multimedia databases

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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