high performance computing on graphics processing units: hgpu.org

hgpu.org » Heterogeneous systems

OpenCL and the 13 Dwarfs: A Work in Progress

W. Feng, H. Lin, T. Scogland, J. Zhang

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Tags: ATI, ATI Radeon HD 5450, Benchmarking, Computer science, Heterogeneous systems, nVidia, nVidia GeForce GT 520, OpenCL, Tesla C2050

May 1, 2012 by hgpu

Lynx: A Dynamic Instrumentation System for Data-Parallel Applications on GPGPU Architectures

Naila Farooqui, Andrew Kerr, Greg Eisenhauer, Karsten Schwan, Sudhakar Yalamanchili

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Source codes

Tags: Code generation, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 480, Optimization, Package, Tesla C2050

April 25, 2012 by hgpu

High-Efficient Parallel CAVLC Encoders on Heterogeneous Multicore Architectures

Huayou Su, Mei Wen, Ju Ren, Nan Wu, Jun Chai, Chunyuan Zhang

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Tags: CUDA, DSP, Heterogeneous systems, Image processing, nVidia, nVidia GeForce GTX 260

April 23, 2012 by hgpu

MetaCL – A Model-Based Approach to Programming Heterogeneous Architectures Using OpenCL

William Spencer Crosswy

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Tags: Algorithms, ATI, ATI Radeon HD 6970, Computer science, Heterogeneous systems, Numerical Analysis, OpenCL, Thesis

April 18, 2012 by hgpu

Heterogeneous Highly Parallel Implementation of Matrix Exponentiation Using GPU

Chittampally Vasanth Raja, Srinivas Balasubramanian, Prakash S. Raghavendra

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Tags: Computer science, Heterogeneous systems, Mathematical Software, Numerical Analysis, nVidia, OpenCL, Tesla C2050

April 16, 2012 by hgpu

A Scalable Framework for Heterogeneous GPU-Based Clusters

Fengguang Song, Jack Dongarra, Stanimire Tomov

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Tags: Algorithms, Computer science, CUDA, Factorization, GPU cluster, Heterogeneous systems, Linear Algebra, MPI, nVidia, Tesla M2070

April 7, 2012 by hgpu

OpenCL framework for a CPU, GPU, and FPGA Platform

Taneem Ahmed

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Tags: ATI, ATI Radeon HD 5450, Computer science, FPGA, Heterogeneous systems, OpenCL, Thesis

April 6, 2012 by hgpu

Enhancing Performance of Simulations using GPGPU

Shadi Alawneh, Dennis Peters

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Tags: Algorithms, Computer science, CUDA, Heterogeneous systems, nVidia

April 5, 2012 by hgpu

Towards Adaptive GPU Resource Management for Embedded Real-Time Systems

Junsung Kim, Raj Rajkumar, Shinpei Kato

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia

April 2, 2012 by hgpu

GPU Programming Strategies and Trends in GPU Computing

Andre R. Brodtkorb, Trond R. Hagen, Martin L. Saetra

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Tags: Computer science, Heterogeneous systems, Optimization, Overview

April 2, 2012 by hgpu

Enabling and Scaling Matrix Computations on Heterogeneous Multi-Core and Multi-GPU Systems

Fengguang Song, Stanimire Tomov, Jack Dongarra

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Tags: Algorithms, Computer science, CUDA, Factorization, Heterogeneous systems, nVidia, Tesla M2070

March 28, 2012 by hgpu

Dynamic Translation of Runtime Environments for Heterogeneous Computing

Rodrigo Dominguez

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Tags: ATI, ATI Radeon HD 5870, Computer science, CUDA, Design space exploration, Heterogeneous systems, nVidia, nVidia GeForce 8800 GTX, OpenCL, Thesis

March 27, 2012 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

OpenCL and the 13 Dwarfs: A Work in Progress

Lynx: A Dynamic Instrumentation System for Data-Parallel Applications on GPGPU Architectures

High-Efficient Parallel CAVLC Encoders on Heterogeneous Multicore Architectures

MetaCL – A Model-Based Approach to Programming Heterogeneous Architectures Using OpenCL

Heterogeneous Highly Parallel Implementation of Matrix Exponentiation Using GPU

A Scalable Framework for Heterogeneous GPU-Based Clusters

OpenCL framework for a CPU, GPU, and FPGA Platform

Enhancing Performance of Simulations using GPGPU

Towards Adaptive GPU Resource Management for Embedded Real-Time Systems

GPU Programming Strategies and Trends in GPU Computing

Enabling and Scaling Matrix Computations on Heterogeneous Multi-Core and Multi-GPU Systems

Dynamic Translation of Runtime Environments for Heterogeneous Computing

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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