high performance computing on graphics processing units: hgpu.org

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hgpu.org » Applications » Computer science

Efficient Parallel Nonnegative Least Squares on Multicore Architectures

Yuancheng Luo, Ramani Duraiswami

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Tags: Algorithms, Computer science, CUDA, Factorization, Nonnegative matrix factorization, nVidia, Package, Tesla C2050

November 28, 2011 by hgpu

Parallel Pseudo-Random Number Generation

Nimalan Nandapalan, Richard Brent

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Tags: Algorithms, Computer science, CUDA, nVidia, OpenCL, Pseudo-random number generators, Review

November 28, 2011 by hgpu

Assembly of finite element methods on graphics processors

Cris Cecka, Adrian J. Lew, E. Darve

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Tags: Computer science, CUDA, FEM, Finite element method, nVidia, nVidia GeForce 8800 GTX, Tesla C1060

November 27, 2011 by hgpu

Computing room acoustics with CUDA-3D FDTD schemes with boundary losses and viscosity

Craig J. Webb, Stefan Bilbao

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Tags: Acoustics, Computer science, CUDA, FDTD, Finite difference, Finite-difference time-domain, Numerical simulation, nVidia, Tesla C1060, Tesla C2050

November 27, 2011 by hgpu

A GPU-based Simulation for Stochastic Computing

Peng Li, Weijun Xiao, David J. Lilja

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Tags: Algorithms, Computer science, CUDA, Electronic design automation, nVidia, Probability, Stochastic simulation, Tesla C2050

November 27, 2011 by hgpu

Scalable Multi-Cache Simulation Using GPUs

Michael Moeng, Sangyeun Cho, Rami Melhem

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Tags: Analytical model, Computer science, CUDA, FPGA, Memory, nVidia, nVidia GeForce GTS 450

November 27, 2011 by hgpu

Towards paradisEO-MO-GPU: a framework for GPU-based local search metaheuristics

N. Melab, T-V. Luong, K. Boufaras, E-G. Talbi

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Tags: Computer science, CUDA, Metaheuristics, nVidia, nVidia GeForce GTX 480, Package

November 27, 2011 by hgpu

Numerical Precision and Benchmarking Very-High-Order Integration of Particle Dynamics on GPU Accelerators

K.A. Hawick, D.P. Playne, M.G.B. Johnson

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Tags: Algorithms, Benchmarking, Computer science, CUDA, N-body simulation, nVidia, nVidia GeForce GTX 260, nVidia GeForce GTX 295, nVidia GeForce GTX 480, nVidia GeForce GTX 580, Tesla C2070

November 27, 2011 by hgpu

A low-cost 3D human interface device using GPU-based optical flow algorithms

Rafael del Riego, Jose Otero, Jose Ranilla

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Tags: Algorithms, CAD, Computer science, nVidia, nVidia GeForce 9500 GT, nVidia GeForce 9500 M, Optical flow

November 27, 2011 by hgpu

A GPU based Parallel Hierarchical Fuzzy ART Clustering

Sejun Kim

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Tags: Clustering, Computer science, CUDA, Hierarchical clustering, nVidia, nVidia GeForce GTX 480

November 27, 2011 by hgpu

A New Compilation Path: From Python/NumPy to OpenCL

Xunhao Li, Rahul Garg, Jose Nelson Amaral

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Tags: ATI, ATI Radeon HD 5850, Benchmarking, Code generation, Compilers, Computer science, nVidia, nVidia GeForce GTX 260, OpenCL, Python

November 26, 2011 by hgpu

Symbolic Differentiation in GPU Shaders

Brian Guenter, John Rapp, Mark Finch

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Tags: Algorithms, ATI, ATI Radeon HD 5870, Computer science, DirectX, HLSL, Symbolic Computation

November 26, 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

Applications

Efficient Parallel Nonnegative Least Squares on Multicore Architectures

Parallel Pseudo-Random Number Generation

Assembly of finite element methods on graphics processors

Computing room acoustics with CUDA-3D FDTD schemes with boundary losses and viscosity

A GPU-based Simulation for Stochastic Computing

Scalable Multi-Cache Simulation Using GPUs

Towards paradisEO-MO-GPU: a framework for GPU-based local search metaheuristics

Numerical Precision and Benchmarking Very-High-Order Integration of Particle Dynamics on GPU Accelerators

A low-cost 3D human interface device using GPU-based optical flow algorithms

A GPU based Parallel Hierarchical Fuzzy ART Clustering

A New Compilation Path: From Python/NumPy to OpenCL

Symbolic Differentiation in GPU Shaders

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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