high performance computing on graphics processing units: hgpu.org

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Performance analysis of a hybrid MPI/CUDA implementation of the NASLU benchmark

S.J. Pennycook, S.D. Hammond, S.A. Jarvis, G.R. Mudalige

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Tags: Benchmarking, Computer science, CUDA, MPI, nVidia, nVidia GeForce 8400 GS, nVidia GeForce 9400 GT, Operating systems, Performance, Tesla C1060, Tesla C2050, Tesla T10

November 8, 2011 by hgpu

Global memory access modelling for efficient implementation of the lattice Boltzmann method on graphics processing units

Christian Obrecht, Frederic Kuznik, Bernard Tourancheau, Jean-Jacques Roux

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Tags: Benchmarking, CUDA, Fluid dynamics, Lattice Boltzmann model, nVidia, nVidia GeForce GTX 295

November 6, 2011 by hgpu

Parallelization of maximum likelihood fits with OpenMP and CUDA

Sverre Jarp, Alfio Lazzaro, Julien Leduc, Andrzej Nowak, Felice Pantaleo

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Tags: Algorithms, Benchmarking, CUDA, Numerical Analysis, nVidia, nVidia GeForce GTX 470, OpenMP, Physics

November 4, 2011 by hgpu

Topology Optimization with Unstructured Meshes on Graphics Processing Units (GPUs)

Tomas Zegard Latrach

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Tags: Algorithms, Benchmarking, Computer science, CUDA, nVidia, Optimization, Tesla T10, Thesis

November 3, 2011 by hgpu

Acceleration Methods for Bayesian Network Sampling

Haohai Yu

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Tags: Algorithms, ATI, ATI Radeon HD 5870, Bayesian, Benchmarking, Clustering, Computer science, OpenCL, Probability, Thesis

November 2, 2011 by hgpu

Accelerating Real-time processing of the ATST Adaptive Optics System using Coarse-grained Parallel Hardware Architectures

V. Venugopal, K. Richards, S. Barden, T. Rimmele, S. Gregory, L. Johnson

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Tags: Algorithms, Benchmarking, CUDA, DSP, FPGA, nVidia, Optics, Physics, Tesla C1060, Tesla C2050

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

Development and evaluation of a GPU-optimized N-body term for the simulation of biomolecules

Timo Strunk, Moritz Wolf, Wolfgang Wenzel

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Tags: ATI, ATI Radeon HD 5870, Benchmarking, Biology, Biomolecules, Monte Carlo simulation, N-body simulation, nVidia, nVidia GeForce GTX 285, OpenCL, Optimization

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

An Adaptive Framework for Managing Heterogeneous Many-Core Clusters

Muhammad Mustafa Rafique

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Tags: Benchmarking, Computer science, CUDA, Heterogeneous systems, MapReduce, nVidia, Prefetch, Software Engineering, Tesla C2050, Thesis

October 28, 2011 by hgpu

Extending Scala with General Purpose GPU Programming

Reidar Beck, Helge Willum Larsen, Tommy Jensen

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Source codes

Tags: Benchmarking, Code generation, Compilers, Computer science, Java, nVidia, OpenCL, Package, Tesla C870

October 25, 2011 by hgpu

Democratizing General Purpose GPU Programming through OpenCL and Scala

Raider Beck, Helge Willum Larsen, Tommy Jensen

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Tags: Benchmarking, Code generation, Compilers, Computer science, nVidia, OpenCL, Package, Tesla C870

October 24, 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

Performance analysis of a hybrid MPI/CUDA implementation of the NASLU benchmark

Global memory access modelling for efficient implementation of the lattice Boltzmann method on graphics processing units

Parallelization of maximum likelihood fits with OpenMP and CUDA

Topology Optimization with Unstructured Meshes on Graphics Processing Units (GPUs)

Acceleration Methods for Bayesian Network Sampling

Accelerating Real-time processing of the ATST Adaptive Optics System using Coarse-grained Parallel Hardware Architectures

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

Development and evaluation of a GPU-optimized N-body term for the simulation of biomolecules

Using OpenCL for image analysis

An Adaptive Framework for Managing Heterogeneous Many-Core Clusters

Extending Scala with General Purpose GPU Programming

Democratizing General Purpose GPU Programming through OpenCL and Scala

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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