high performance computing on graphics processing units: hgpu.org

Programming

A mapping path for multi-GPGPU accelerated computers from a portable high level programming abstraction

Allen Leung, Nicolas Vasilache, Benoit Meister, Muthu Baskaran, David Wohlford, Cedric Bastoul, Richard Lethin

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Tags: Algorithms, Code generation, Compilers, Computer science, CUBLAS, CUDA, nVidia, nVidia GeForce 9800 GX2, nVidia GeForce GTX 285, Programming Languages

August 24, 2011 by hgpu

Experience of parallelizing cryo-EM 3D reconstruction on a CPU-GPU heterogeneous system

Linchuan Li, Xingjian Li, Guangming Tan, Mingyu Chen, Peiheng Zhang

Tags: Algorithms, Computer science, Cryo-EM, CUDA, Data parallelism, GPU cluster, Heterogeneous systems, MPI, nVidia, Performance, Tesla C2050

August 24, 2011 by hgpu

An open framework for rapid prototyping of signal processing applications

Maxime Pelcat, Jonathan Piat, Matthieu Wipliez, Slaheddine Aridhi, and Jean-Francois Nezan

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Tags: Algorithms, Graph theory, Signal processing

August 24, 2011 by hgpu

Precise dynamic analysis for slack elasticity: adding buffering without adding bugs

Sarvani Vakkalanka, Anh Vo, Ganesh Gopalakrishnan, Robert M. Kirby

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Tags: Algorithms, Computer science, MPI, Network communications

August 24, 2011 by hgpu

Fast parallel surface and solid voxelization on GPUs

Michael Schwarz, Hans-Peter Seidel

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Tags: 3D Graphics and Realism, Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 285, nVidia GeForce GTX 480

August 23, 2011 by hgpu

High performance content-based matching using GPUs

Alessandro Margara, Gianpaolo Cugola

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Tags: Algorithms, Computer science, CUDA, Information Retrieval, nVidia, nVidia GeForce GTX 460, Package, Performance, Programming techniques

August 23, 2011 by hgpu

Auto-tuning 3-D FFT library for CUDA GPUs

Akira Nukada, Satoshi Matsuoka

Tags: Algorithms, Computer science, CUDA, FFT, Mathematical Software, nVidia, Performance

August 22, 2011 by hgpu

Floating-point data compression at 75 Gb/s on a GPU

Molly A. O'Neil, Martin Burtscher

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Tags: Algorithms, Compression, Computer science, CUDA, nVidia, nVidia GeForce FX 5600, Package, Performance, Programming techniques

August 22, 2011 by hgpu

A new method for GPU based irregular reductions and its application to k-means clustering

Balaji Dhanasekaran, Norman Rubin

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Tags: Algorithms, ATI, ATI Radeon HD 5870, Computer science, Data mining, Heterogeneous systems, OpenCL, Performance, Programming techniques

August 21, 2011 by hgpu

Multi- and many-core data mining with adaptive sparse grids

Alexander Heinecke, Dirk Pfluger

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Tags: Algorithms, Computer science, Data mining, Mathematical Software, nVidia, nVidia GeForce GTX 470, OpenCL, Performance, Presentation

August 21, 2011 by hgpu

Breaking the GPU programming barrier with the auto-parallelising SAC compiler

Jing Guo, Jeyarajan Thiyagalingam, Sven-Bodo Scholz

Tags: Algorithms, Compilers, Computer science, CUDA, nVidia, Performance, Programming Languages

August 21, 2011 by hgpu

The openip open source image processing library

Gyorgy Kovacs, Janos Istvan Ivan, Arpad Panyik, Attila Fazekas

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Tags: Algorithms, ATI, Computer vision, Image processing, nVidia, OpenCL, OpenMP, Package

August 21, 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

Programming

A mapping path for multi-GPGPU accelerated computers from a portable high level programming abstraction

Experience of parallelizing cryo-EM 3D reconstruction on a CPU-GPU heterogeneous system

An open framework for rapid prototyping of signal processing applications

Precise dynamic analysis for slack elasticity: adding buffering without adding bugs

Fast parallel surface and solid voxelization on GPUs

High performance content-based matching using GPUs

Auto-tuning 3-D FFT library for CUDA GPUs

Floating-point data compression at 75 Gb/s on a GPU

A new method for GPU based irregular reductions and its application to k-means clustering

Multi- and many-core data mining with adaptive sparse grids

Breaking the GPU programming barrier with the auto-parallelising SAC compiler

The openip open source image processing library

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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