high performance computing on graphics processing units: hgpu.org

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Efficient Implementation of the eta_T Pairing on GPU

Yosuke Katoh, Yun-Ju Huang, Chen-Mou Cheng, Tsuyoshi Takagi

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Tags: Algorithms, Computer science, nVidia, nVidia GeForce GTX 285, nVidia GeForce GTX 480, Security, Tesla C1060, Tesla C2050

October 30, 2011 by hgpu

High-Level Synthesis for FPGAs: From Prototyping to Deployment

Jason Cong, Bin Liu, Stephen Neuendorffer, Juanjo Noguera, Kees Vissers, Zhiru Zhang

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Tags: Algorithms, Computer science, FPGA

October 30, 2011 by hgpu

Improving Energy Efficiency of GPU based General-Purpose Scientific Computing through Automated Selection of Near Optimal Configurations

Xiaohan Ma, Marion Rincon, Zhigang Deng

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Tags: Algorithms, Benchmarking, Computer science, CUDA, Energy-efficient computing, nVidia, nVidia GeForce 8800 GT

October 30, 2011 by hgpu

CPU and GPU Co-processing for Sound

Aleksander Gjermundsen

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Tags: Algorithms, ATI, ATI Radeon HD 5870, Computer science, Filtering, Linear Algebra, nVidia, nVidia GeForce GTX 280, OpenCL, Package, Signal processing, Tesla C2050, Thesis

October 30, 2011 by hgpu

Using OpenCL for image analysis

Niklas Frisk

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Tags: Algorithms, Benchmarking, Image processing, Java, nVidia, nVidia GeForce 8600 M, OpenCL, Thesis

October 29, 2011 by hgpu

Architectural Exploration and Scheduling Methods for Coarse Grained Reconfigurable Arrays

Giovanni Ansaloni

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Tags: Algorithms, Computer science, Design space exploration, Heterogeneous systems, Thesis

October 28, 2011 by hgpu

Architecture-based Performance Evaluation of Genetic Algorithms on Multi/Many-core Systems

Long Zheng, Yanchao Lu, Mengwei Ding, Yao Shen, Minyi Guo, Song Guo

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Tags: Algorithms, Computer science, CUDA, Genetic programming, nVidia, nVidia GeForce GTX 580, Optimization

October 28, 2011 by hgpu

Matrix inversion speed up with CUDA

Jorge Soriano Pinedo

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Tags: Algorithms, Computer science, CUDA, Image reconstruction, Matrix inversion, Matrix multiplication, nVidia, Tesla C1060, Thesis

October 28, 2011 by hgpu

Dax: Data Analysis at Extreme

Kenneth Moreland, Utkarsh Ayachit, Berk Geveci, Kwan-Liu Ma

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Tags: Algorithms, Computer science, Poster, Visualization

October 28, 2011 by hgpu

Parallel Computing the Longest Common Subsequence (LCS) on GPUs: Efficiency and Language Suitability

Amine Dhraief, Raik Issaoui, Abdelfettah Belghith

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Tags: Algorithms, Bioinformatics, Biology, CUDA, nVidia, nVidia GeForce GT 430, OpenCL, Sequence alignment

October 28, 2011 by hgpu

Efficient Simulation of Ocean and Land Scenes Based on Digital Earth

Sujun Li, Xiaosu Zhan, Yaoli Wang, Feng Ding

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Tags: 3D Graphics and Realism, Algorithms, ATI, ATI Radeon X600, Computer science, DirectX, Rendering, Visualization

October 27, 2011 by hgpu

Sample distribution shadow maps

Andrew Lauritzen, Marco Salvi, Aaron Lefohn

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Tags: 3D Graphics and Realism, Algorithms, ATI, ATI Radeon HD 5870, Computer science, DirectX, Interactive application, Rendering

October 27, 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

Efficient Implementation of the eta_T Pairing on GPU

High-Level Synthesis for FPGAs: From Prototyping to Deployment

Improving Energy Efficiency of GPU based General-Purpose Scientific Computing through Automated Selection of Near Optimal Configurations

CPU and GPU Co-processing for Sound

Using OpenCL for image analysis

Architectural Exploration and Scheduling Methods for Coarse Grained Reconfigurable Arrays

Architecture-based Performance Evaluation of Genetic Algorithms on Multi/Many-core Systems

Matrix inversion speed up with CUDA

Dax: Data Analysis at Extreme

Parallel Computing the Longest Common Subsequence (LCS) on GPUs: Efficiency and Language Suitability

Efficient Simulation of Ocean and Land Scenes Based on Digital Earth

Sample distribution shadow maps

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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