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Comparison based sorting for systems with multiple GPUs

Ivan Tanasic, Lluis Vilanova, Marc Jorda, Javier Cabezas, Isaac Gelado, Nacho Navarro, Wen-mei Hwu

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Tags: Algorithms, Computer science, CUDA, nVidia, Performance, Sorting, Tesla C2070

April 18, 2013 by hgpu

MrBayes tgMC3: A Tight GPU Implementation of MrBayes

Cheng Ling, Tsuyoshi Hamada, Jianing Bai, Xianbin Li, Douglas Chesters, Weimin Zheng, Weifeng Shi

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Tags: Algorithms, Bayesian, Computer science, CUDA, nVidia, nVidia GeForce GTX 480, Package

April 18, 2013 by hgpu

Supporting Iteration in a Heterogeneous Data Flow Engine

Jon Currey, Simon Baker, Christopher J. Rossbach

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Tags: Algorithms, Computer science, Computer vision, DirectCompute, Heterogeneous systems, MapReduce, nVidia, nVidia GeForce GTX 580, Optical flow

April 18, 2013 by hgpu

Massively Parallel Suffix Array Queries and On-Demand Phrase Extraction for Statistical Machine Translation Using GPUs

Hua He, Jimmy Lin, Adam Lopez

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

April 18, 2013 by hgpu

Computing Privacy-Preserving Edit Distance and Smith-Waterman Problems on the GPU Architecture

Shi Pu, Jyh-Charn Liu

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 680, Security, Smith-Waterman algorithm

April 18, 2013 by hgpu

GPU Accelerated Face Detection (thesis)

Jussi Makela

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Tags: Algorithms, Computer science, Computer vision, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 480, OpenCL, Thesis

April 17, 2013 by hgpu

Parallel GPU Architecture Simulation Framework Exploiting Work Allocation Unit Parallelism

Sangpil Lee, Won Woo Ro

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

April 17, 2013 by hgpu

LU Factorization with Partial Pivoting for a Multi-CPU, Multi-GPU Shared Memory System

Jakub Kurzak, P. Luszczek, Mathieu Faverge, Jack J. Dongarra

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Tags: Computer science, CUDA, Factorization, nVidia, Task scheduling, Tesla S2050

April 17, 2013 by hgpu

A Framework for Profiling and Performance Monitoring of Heterogeneous Applications

Perhaad Mistry, Yash Ukidave, Dana Schaa, David Kaeli

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Tags: ATI, ATI Radeon HD 5870, ATI Radeon HD 6550, Computer science, Computer vision, Heterogeneous systems, OpenCL, Performance, Signal processing

April 17, 2013 by hgpu

Communication-Minimizing 2D Convolution in GPU Registers

Forrest N. Iandola, David Sheffield, Michael Anderson, Phitchaya Mangpo Phothilimthana, Kurt Keutzer

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Tags: Algorithms, Computer vision, CUDA, Image processing, nVidia, nVidia GeForce GTX 680, Prefetch, Tesla C2050

April 17, 2013 by hgpu

Zero-copy I/O processing for low-latency GPU computing

Shinpei Kato, Jason Aumiller, Scott Brandt

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Tags: Algorithms, Benchmarking, CUDA, Data parallelism, nVidia, Plasma physics

April 16, 2013 by hgpu

Fast simulation of nonlinear radio frequency ultrasound images in inhomogeneous nonlinear media: CREANUIS

Francois Varray, Matthieu Toulemonde, Olivier Basset, Christian Cachard

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Tags: Acoustics, Ultrasound

April 16, 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

Comparison based sorting for systems with multiple GPUs

MrBayes tgMC3: A Tight GPU Implementation of MrBayes

Supporting Iteration in a Heterogeneous Data Flow Engine

Massively Parallel Suffix Array Queries and On-Demand Phrase Extraction for Statistical Machine Translation Using GPUs

Computing Privacy-Preserving Edit Distance and Smith-Waterman Problems on the GPU Architecture

GPU Accelerated Face Detection (thesis)

Parallel GPU Architecture Simulation Framework Exploiting Work Allocation Unit Parallelism

LU Factorization with Partial Pivoting for a Multi-CPU, Multi-GPU Shared Memory System

A Framework for Profiling and Performance Monitoring of Heterogeneous Applications

Communication-Minimizing 2D Convolution in GPU Registers

Zero-copy I/O processing for low-latency GPU computing

Fast simulation of nonlinear radio frequency ultrasound images in inhomogeneous nonlinear media: CREANUIS

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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