high performance computing on graphics processing units: hgpu.org

hgpu.org » Heterogeneous systems

Performance Portability of a GPU Enabled Factorization with the DAGuE Framework

George Bosilca, Aurelien Bouteiller, Thomas Herault, Pierre Lemarinier, Narapat Ohm Saengpatsa, Stanimire Tomov, Jack J. Dongarra

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Tags: Computer science, Factorization, GPU cluster, Heterogeneous systems, Linear Algebra, nVidia, Performance, Tesla C1060, Tesla C2050, Tesla S1070

November 3, 2011 by hgpu

A shared file system abstraction for heterogeneous architectures

Mark Silberstein, Idit Keidar

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Tags: Computer science, Heterogeneous systems, Operating systems

November 2, 2011 by hgpu

Quantum chemical many-body theory on heterogeneous nodes

A. Eugene DePrince, Jeff R. Hammond

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Tags: Algorithms, Computational chemistry, CUBLAS, CUDA, Heterogeneous systems, nVidia, Presentation, Tesla C1060, Tesla C2050

November 1, 2011 by hgpu

An Implementation of Differential Evolution for Independent Tasks Scheduling on GPU

Pavel Kromer, Jan Platos, Vaclav Snasel, Ajith Abraham

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Tags: Algorithms, Artificial intelligence, Computer science, CUDA, Differential evolution, Heterogeneous systems, nVidia, Optimization, Task scheduling, Tesla C2050

November 1, 2011 by hgpu

A Real-Time Computer Vision Library for Heterogeneous Processing Environments

Tony J. Liu

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Source codes

Tags: Computer science, Computer vision, DSP, FPGA, Heterogeneous systems, Package, Thesis

November 1, 2011 by hgpu

Workload Balancing on Heterogeneous Systems: A Case Study of Sparse Grid Interpolation

Alin Murarasu, Josef Weidendorfer, Arndt Bode

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Tags: Compression, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 480, Task scheduling, Tesla C2050

October 31, 2011 by hgpu

Automatic CUDA Code Synthesis Framework for Multicore CPU and GPU architectures

Hanwoong Jung, Youngmin Yi, Soonhoi Ha

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Tags: Code generation, Computer science, CUDA, Data parallelism, Heterogeneous systems, nVidia, Tesla M2050

October 30, 2011 by hgpu

Leveraging Binary Translation for Heterogeneous Profiling

Dan Upton, Kim Hazelwood

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Tags: ATI, ATI Radeon HD 5870, Computer science, Heterogeneous systems, nVidia, OpenCL, Performance, Tesla C2050

October 30, 2011 by hgpu

GPU Computations in Heterogeneous Grid Environments

Marcus Hinders

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Tags: ATI, ATI Radeon HD 5870, Biology, Computational biology, Computer science, Grid, Heterogeneous systems, nVidia, nVidia GeForce 8600 GT, nVidia GeForce GTX 280, OpenCL, Thesis

October 30, 2011 by hgpu

Dynamic Scheduling of Parallel Code for Heterogeneous Systems

Jeff Brantley, Chris Gregg

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Tags: ATI, ATI Radeon HD 4350, Computer science, Heterogeneous systems, OpenCL, Performance

October 30, 2011 by hgpu

Jit4OpenCL: a compiler from Python to OpenCL

Xunhao Li

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

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 Portability of a GPU Enabled Factorization with the DAGuE Framework

A shared file system abstraction for heterogeneous architectures

Quantum chemical many-body theory on heterogeneous nodes

An Implementation of Differential Evolution for Independent Tasks Scheduling on GPU

A Real-Time Computer Vision Library for Heterogeneous Processing Environments

Workload Balancing on Heterogeneous Systems: A Case Study of Sparse Grid Interpolation

Automatic CUDA Code Synthesis Framework for Multicore CPU and GPU architectures

Leveraging Binary Translation for Heterogeneous Profiling

GPU Computations in Heterogeneous Grid Environments

Dynamic Scheduling of Parallel Code for Heterogeneous Systems

Jit4OpenCL: a compiler from Python to OpenCL

An Adaptive Framework for Managing Heterogeneous Many-Core Clusters

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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