high performance computing on graphics processing units: hgpu.org

hgpu.org » Heterogeneous systems

Modeling and Simulation of a Dynamic Task-Based Runtime System for Heterogeneous Multi-Core Architectures

Luka Stanisic, Samuel Thibault, Arnaud Legrand, Brice Videau, Jean-Francois Mehaut

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Tags: Computer science, CUDA, Heterogeneous systems, Linear Algebra, nVidia, nVidia Quadro FX 5800, Performance, Task scheduling, Tesla C2050, Tesla K20, Tesla M2075

April 9, 2014 by hgpu

Task-based FMM for heterogeneous architectures

Emmanuel Agullo, Berenger Bramas, Olivier Coulaud, Eric Darve, Matthias Messner, Toru Takahashi

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Tags: Computer science, CUDA, Fast multipole method, Heterogeneous systems, Numerical simulation, nVidia, Tesla M2070, Tesla M2090

April 9, 2014 by hgpu

Code Generation for Embedded Heterogeneous Architectures on Android

R. Membarth, O. Reiche, F. Hannig, J. Teich

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Tags: Code generation, Heterogeneous systems, Image processing

April 1, 2014 by hgpu

BigKernel — High Performance CPU-GPU Communication Pipelining for Big Data-style Applications

R. Mokhtari, M. Stumm

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Tags: CUDA, Heterogeneous systems, Memory, nVidia, nVidia GeForce GTX 680

March 25, 2014 by hgpu

Demonstrating Self-Learning Algorithm Adaptivity in a Hardware-Oblivious Database Engine

M. Heimel, F. Haase, M. Meinke, S. Breß, M. Saecker, V. Markl

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Tags: Databases, Heterogeneous systems, OpenCL, Performance

March 24, 2014 by hgpu

Prototyping methodology of image processing applications on heterogeneous parallel systems

Jinglin Zhang

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Tags: Algorithms, CUDA, Heterogeneous systems, Image processing, nVidia, nVidia GeForce 7800 GT, nVidia GeForce 8800 GTX, nVidia GeForce GT 540 M, OpenCL, Thesis

March 17, 2014 by hgpu

OpenCL-Accelerated Simplified General Perturbations 4 Algorithm

Juan Andres Fraire, Pablo Ferreyra, Carlos Marques

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Tags: ATI, ATI Radeon HD 5870, Earth and Space Sciences, Heterogeneous systems, nVidia, nVidia GeForce 9500 GT, OpenCL, Security

March 10, 2014 by hgpu

A Framework for Developing Real-Time OLAP algorithm using Multi-core processing and GPU: Heterogeneous Computing

H.I. Alzeini, Sh.A. Hameed, M.H. Habaebi

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Tags: Algorithms, Computer science, Heterogeneous systems

March 9, 2014 by hgpu

Designing Efficient MPI and UPC Runtime for Multicore Clusters with InfiniBand, Accelerators and Co-Processors

Miao Luo

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Tags: Algorithms, Computer science, CUDA, Heterogeneous systems, MPI, nVidia, Tesla C2050

March 9, 2014 by hgpu

Dynamic Workload Division in GPU-CPU Heterogeneous Systems

Wei Chen

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Tags: Algorithms, Computer science, CUDA, Heterogeneous systems, nVidia, Tesla C2070, Thesis

March 7, 2014 by hgpu

On-Demand Source Code Generation & Scheduling Optimised Parallel Applications on Heterogeneous Platforms

K.A. Hawick, D.P.Playne

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Tags: Code generation, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 260, nVidia GeForce GTX 580, nVidia GeForce GTX 680, Software Engineering

March 4, 2014 by hgpu

Multi-scale problems, high performance computing and hybrid numerical methods

Guillaume Balarac, Georges-Henri Cottet, Jean-Mathieu Etancelin, Jean-Baptiste Lagaert, Franck Perignon, Christophe Picard

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Tags: Heterogeneous systems, Mathematics, nVidia, OpenCL, Tesla K20

March 3, 2014 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

Modeling and Simulation of a Dynamic Task-Based Runtime System for Heterogeneous Multi-Core Architectures

Task-based FMM for heterogeneous architectures

Code Generation for Embedded Heterogeneous Architectures on Android

BigKernel — High Performance CPU-GPU Communication Pipelining for Big Data-style Applications

Demonstrating Self-Learning Algorithm Adaptivity in a Hardware-Oblivious Database Engine

Prototyping methodology of image processing applications on heterogeneous parallel systems

OpenCL-Accelerated Simplified General Perturbations 4 Algorithm

A Framework for Developing Real-Time OLAP algorithm using Multi-core processing and GPU: Heterogeneous Computing

Designing Efficient MPI and UPC Runtime for Multicore Clusters with InfiniBand, Accelerators and Co-Processors

Dynamic Workload Division in GPU-CPU Heterogeneous Systems

On-Demand Source Code Generation & Scheduling Optimised Parallel Applications on Heterogeneous Platforms

Multi-scale problems, high performance computing and hybrid numerical methods

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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