high performance computing on graphics processing units: hgpu.org

Applications

hgpu.org » Applications

A journey from single-GPU to optimized multi-GPU SPH with CUDA

E. Rustico, G. Bilotta, G. Gallo, A. Herault, C. Del Negro, R. A. Dalrymple

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Tags: CUDA, Fluid dynamics, nVidia, nVidia GeForce GTX 480, Package

March 31, 2013 by hgpu

A Massively Parallel Associative Memory Based on Sparse Neural Networks

Zhe Yao, Vincent Gripon, Michael G. Rabbat

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Tags: Artificial intelligence, Computer science, CUDA, Neural and Evolutionary Computing, Neural networks, nVidia, Tesla C1060

March 31, 2013 by hgpu

CMCpy: Genetic Code-Message Coevolution Models in Python

Peter J. Becich, Brian P. Stark, Harish S. Bhat, David H. Ardell

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Tags: Bioinformatics, Biology, CUDA, nVidia, nVidia GeForce GTX 460, Package, Python

March 31, 2013 by hgpu

High Performance Computing using GPGPU’s

Omar Usman Khan

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Tags: Electrodynamics, FFT, nVidia, nVidia GeForce GTX 260, OpenCL, Package, Thesis

March 29, 2013 by hgpu

Warp Size Impact in GPUs: Large or Small?

Ahmad Lashgar, Amirali Baniasadi, Ahmad Khonsari

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Tags: Computer science, GPGPU-sim, Memory, Performance

March 29, 2013 by hgpu

Graphics Processing Unit Acceleration of the Explicit Solution of the Time Domain Volume Integral Equation Using OpenACC

Ahmed Al-Jarro, Alain Clo, Hakan Bagci

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Tags: Electrodynamics, Integral equations, Mathematics, OpenACC

March 29, 2013 by hgpu

Parallel Simulation of Population Balance Model-Based Particulate Processes Using Multicore CPUs and GPUs

Anuj V. Prakash, Anwesha Chaudhury, Rohit Ramachandran

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Tags: CAD, Computer science, CUDA, nVidia, nVidia GeForce GTX 280, Pharmaceuticals

March 29, 2013 by hgpu

Accelerating Graph Analysis with Heterogeneous Systems

Ate Penders

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Tags: Algorithms, Computer science, Graph theory, Heterogeneous systems, nVidia, nVidia GeForce GTX 480, OpenCL, Tesla C2050, Thesis

March 29, 2013 by hgpu

Adaptive OpenCL (ACL) Execution in GPU Architectures

Dan Connors, Kyle Dunn, Jeff Wiencrot

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Tags: Algorithms, Computer science, DSP, Heterogeneous systems, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 480, OpenCL

March 26, 2013 by hgpu

Parallel Sorting on the Heterogeneous AMD Fusion Accelerated Processing Unit

Michael Christopher Delorme

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Tags: APU, ATI, ATI Radeon HD 5870, ATI Radeon HD 6530, ATI Radeon HD 6550, Computer science, Heterogeneous systems, nVidia, OpenCL, Sorting, Thesis, Tutorial

March 26, 2013 by hgpu

Accelerated Dictionary Learning with GPU/Multicore CPU and Its Application to Music Classification

Boyang Gao, Emmanuel Dellandrea, Liming Chen

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Tags: Clustering, CUBLAS, CUDA, Linear Algebra, Matrix multiplication, nVidia, nVidia GeForce GTX 285, Signal processing

March 26, 2013 by hgpu

General Purpose Computation on Graphics Processing Units Using OpenCL

Fiaz Gul Khan

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Tags: Computer science, Electrodynamics, FFT, Heterogeneous systems, nVidia, nVidia GeForce GTX 260, nVidia Quadro FX 6000, OpenCL, Sorting, Thesis, Tutorial

March 26, 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

A journey from single-GPU to optimized multi-GPU SPH with CUDA

A Massively Parallel Associative Memory Based on Sparse Neural Networks

CMCpy: Genetic Code-Message Coevolution Models in Python

High Performance Computing using GPGPU’s

Warp Size Impact in GPUs: Large or Small?

Graphics Processing Unit Acceleration of the Explicit Solution of the Time Domain Volume Integral Equation Using OpenACC

Parallel Simulation of Population Balance Model-Based Particulate Processes Using Multicore CPUs and GPUs

Accelerating Graph Analysis with Heterogeneous Systems

Adaptive OpenCL (ACL) Execution in GPU Architectures

Parallel Sorting on the Heterogeneous AMD Fusion Accelerated Processing Unit

Accelerated Dictionary Learning with GPU/Multicore CPU and Its Application to Music Classification

General Purpose Computation on Graphics Processing Units Using OpenCL

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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