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hgpu.org » Heterogeneous systems

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

Performance Assessment of A Multi-block Incompressible Navier-Stokes Solver using Directive-based GPU Programming in a Cluster Environment

Lixiang Luo, Jack R. Edwards, Hong Luo, Frank Mueller

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Tags: CUDA, Fluid dynamics, Heterogeneous systems, nVidia, OpenACC, Tesla K20

February 28, 2014 by hgpu

Heterogenous Acceleration for Linear Algebra in Multi-Coprocessor Environments

Azzam Haidar, Piotr Luszczek, Stanimire Tomov, Jack Dongarra

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Tags: Computer science, Factorization, Heterogeneous systems, Intel Xeon Phi, Linear Algebra

February 28, 2014 by hgpu

An Evaluation of the GAMA/StarPU Frameworks for Heterogeneous Platforms: the Progressive Photon Mapping Algorithm

Miguel Branco Palhas

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Tags: 3D Graphics and Realism, Algorithms, Computer science, CUDA, Heterogeneous systems, Memory model, nVidia, Rendering, Tesla K20, Tesla M2090, Thesis

February 25, 2014 by hgpu

Towards Porting a Real-World Seismological Application to the Intel MIC Architecture

V. Weinberg, M. Allalen, G. Brietzke

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Tags: Earth and Space Sciences, Fortran, Geoscience, Heterogeneous systems, Intel Xeon Phi, MPI, Seismology

February 16, 2014 by hgpu

Designing Bit-Reproducible Portable High-Performance Applications

Andrea Arteaga, Oliver Fuhrer, Torsten Hoefler

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Tags: Algorithms, Computer science, CUDA, Heterogeneous systems, MPI, nVidia, Portability, Tesla K20

February 12, 2014 by hgpu

A scheduling and runtime framework for a cluster of heterogeneous machines with multiple accelerators

Tarun Beri, Sorav Bansal, Subodh Kumar

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Tags: Computer science, CUDA, FFT, GPU cluster, Heterogeneous systems, Matrix multiplication, Memory model, nVidia, Prefetch, Task scheduling, Tesla M2070

February 11, 2014 by hgpu

Exploring Multiple Levels of Performance Modeling for Heterogeneous Systems

Vivek K. Pallipuram

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Tags: Computer science, CUDA, GPU cluster, Heterogeneous systems, nVidia, Performance, Tesla K20, Tesla M2075, Thesis

February 11, 2014 by hgpu

Auto-Generation and Auto-Tuning of 3D Stencil Codes on Homogeneous and Heterogeneous GPU Clusters

Yongpeng Zhang, Frank Mueller

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Tags: Computer science, CUDA, GPU cluster, Heterogeneous systems, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 480, Optimization, Tesla C1060, Tesla C2050

February 5, 2014 by hgpu

Strategies for Maximizing Utilization in multi-CPU & multi-GPU Heterogeneous Architectures

Angeles Navarro, Antonio Vilches, Francisco Corbera, Rafael Asenjo

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Tags: Algorithms, Computer science, CUDA, Heterogeneous systems, nVidia, Performance, Tesla S2050

February 4, 2014 by hgpu

Task migration of DSP application specified with a DFG and implemented with the BSP computing model on a CPU-GPU cluster

Farouk Mansouri, Sylvain Huet, Vincent Fristot, Dominique Houzet

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Tags: Computer science, CUDA, DSP, GPU cluster, Heterogeneous systems, nVidia, nVidia GeForce GTX 285, nVidia Quadro 4000, Signal processing

February 2, 2014 by hgpu

CLUEstering: a high-performance density-based clustering library for scientific computing

PyOMP: OpenMP for Python in Numba

PyOMP: Parallel programming for CPUs and GPUs with OpenMP and Python

GPPerf: Energy-Aware GPU Performance Prediction and Optimization Framework

Understanding GEMM Performance and Energy on NVIDIA Ada Lovelace: A Machine Learning-Based Analytical Approach

HiRep

Scaling SU(2) to 1000 GPUs using HiRep

Gaia AVU-GSR

Performance portability via C++ PSTL, SYCL, OpenMP, and HIP: the Gaia AVU-GSR case study

gpuPairHMM: Ultra-fast GPU-based PairHMM for DNA Variant Calling

gpuPairHMM: High-speed Pair-HMM Forward Algorithm for DNA Variant Calling on GPUs

See all packages

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high performance computing on graphics processing units: hgpu.org

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

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

Performance Assessment of A Multi-block Incompressible Navier-Stokes Solver using Directive-based GPU Programming in a Cluster Environment

Heterogenous Acceleration for Linear Algebra in Multi-Coprocessor Environments

An Evaluation of the GAMA/StarPU Frameworks for Heterogeneous Platforms: the Progressive Photon Mapping Algorithm

Towards Porting a Real-World Seismological Application to the Intel MIC Architecture

Designing Bit-Reproducible Portable High-Performance Applications

A scheduling and runtime framework for a cluster of heterogeneous machines with multiple accelerators

Exploring Multiple Levels of Performance Modeling for Heterogeneous Systems

Auto-Generation and Auto-Tuning of 3D Stencil Codes on Homogeneous and Heterogeneous GPU Clusters

Strategies for Maximizing Utilization in multi-CPU & multi-GPU Heterogeneous Architectures

Task migration of DSP application specified with a DFG and implemented with the BSP computing model on a CPU-GPU cluster

Recent source codes

tdg-benchs: benchmarks used to test the performance of taskgraph

SW#SYCL

LLOR: Automatic Repair of OpenMP Programs

Solomon: Simple Off-LOading Macros Orchestrating multiple Notations

CLUEstering: a high-performance density-based clustering library for scientific computing

PyOMP: OpenMP for Python in Numba

GPPerf: Energy-Aware GPU Performance Prediction and Optimization Framework

HiRep

Gaia AVU-GSR

gpuPairHMM: Ultra-fast GPU-based PairHMM for DNA Variant Calling

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