high performance computing on graphics processing units: hgpu.org

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hgpu.org » Applications » Computer science

Sequential Consistency for Heterogeneous-Race-Free: Programmer-centric Memory Models for Heterogeneous Platforms

Derek R. Hower, Bradford M. Beckmann, Benedict R. Gaster, Blake A. Hechtman, Mark D. Hill, Steven K. Reinhardt, David A. Wood

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Tags: Computer science, CUDA, Heterogeneous systems, Memory model, nVidia, OpenCL, Performance

May 23, 2013 by hgpu

Surface Reconstruction from Scattered Point via RBF Interpolation on GPU

Salvatore Cuomo, Ardelio Gallettiy, Giulio Giuntay, Alfredo Staracey

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Tags: Computer science, CUDA, Numerical Analysis, nVidia, Tesla C1060

May 23, 2013 by hgpu

Evaluating the Performance of Legacy Applications on Emerging Parallel Architectures

Simon John Pennycook

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Tags: Algorithms, ATI, ATI FirePro V7800, Benchmarking, Computer science, CUDA, MPI, nVidia, nVidia GeForce 8400 GS, nVidia GeForce 9800 GT, nVidia GeForce GTX 680, OpenCL, Performance, Tesla C1060, Tesla C2050, Thesis

May 21, 2013 by hgpu

An Investigation of the Performance Portability of OpenCL

S.J. Pennycook, S.D. Hammond, S.A. Wright, J.A. Herdman, I. Miller, S.A. Jarvis

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Tags: ATI, ATI FirePro V7800, Benchmarking, Computer science, CUDA, Fortran, MPI, nVidia, OpenCL, Package, Performance, Tesla C1060, Tesla C2050

May 21, 2013 by hgpu

3DES ECB Optimized for Massively Parallel CUDA GPU Architecture

Lukasz Swierczewski

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTS 250, Security, Tesla C2050

May 21, 2013 by hgpu

CLgrep: A Parallel String Matching Tool

Peng Wu

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Tags: Algorithms, Computer science, Heterogeneous systems, nVidia, nVidia GeForce GTX 280, OpenCL, Package, String matching, Thesis

May 20, 2013 by hgpu

Parallel 5 point SOR for solving the Convection Diffusion equation using graphics processing units

Yiannis Cotronis, Elias Konstantinidis, Maria A. Louka, Nikolaos M. Missirlis

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Tags: Computer science, CUDA, Diffusion equation, nVidia, nVidia GeForce GTX 480, Tesla C2050

May 20, 2013 by hgpu

Collision detection on the GPU

Antti Valli

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Tags: Algorithms, Collision detection, Computer science, nVidia, nVidia GeForce GTX 285, OpenCL, Thesis

May 20, 2013 by hgpu

CUDA Accelerated Robot Localization and Mapping

Haiyang Zhang, Fred Martin

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 660

May 20, 2013 by hgpu

Solving Linear Equations with Conjugate Gradient Method on OpenCL Platforms

Caner Sayin

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Tags: Computer science, Heterogeneous systems, Linear Algebra, nVidia, OpenCL, Sparse matrix, Tesla C2050, Tesla C2070, Thesis

May 20, 2013 by hgpu

Generating 3D Topologies with Multiple Constraints on the GPU

Krishnan Suresh

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 480, Topology optimization problem

May 19, 2013 by hgpu

Exploiting Uniform Vector Instructions for GPGPU Performance, Energy Efficiency, and Opportunistic Reliability Enhancement

Ping Xiang, Yi Yang, Mike Mantor, Norm Rubin, Lisa R. Hsu, Huiyang Zhou

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Tags: Computer science, GPGPU-sim, nVidia, nVidia GeForce GTX 285, nVidia GeForce GTX 480, Performance

May 19, 2013 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

Sequential Consistency for Heterogeneous-Race-Free: Programmer-centric Memory Models for Heterogeneous Platforms

Surface Reconstruction from Scattered Point via RBF Interpolation on GPU

Evaluating the Performance of Legacy Applications on Emerging Parallel Architectures

An Investigation of the Performance Portability of OpenCL

3DES ECB Optimized for Massively Parallel CUDA GPU Architecture

CLgrep: A Parallel String Matching Tool

Parallel 5 point SOR for solving the Convection Diffusion equation using graphics processing units

Collision detection on the GPU

CUDA Accelerated Robot Localization and Mapping

Solving Linear Equations with Conjugate Gradient Method on OpenCL Platforms

Generating 3D Topologies with Multiple Constraints on the GPU

Exploiting Uniform Vector Instructions for GPGPU Performance, Energy Efficiency, and Opportunistic Reliability Enhancement

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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