high performance computing on graphics processing units: hgpu.org

hgpu.org » Heterogeneous systems

On the Characterization of OpenCL Dwarfs on Fixed and Reconfigurable Platforms

Konstantinos Krommydas, Wu-chun Feng, Muhsen Owaida, Christos D. Antonopoulos, Nikolaos Bellas

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Tags: APU, ATI, ATI Radeon HD 7970, Benchmarking, Computer science, FPGA, Heterogeneous systems, Intel Xeon Phi, OpenCL, Package, Performance

June 26, 2014 by hgpu

Runtime Visualization of Application Progress and Monitoring of a GPU-enabled Parallel Environment

Szymon Bultrowicz, Pawel Czarnul, Pawel Rosciszewski

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Tags: Computer science, Heterogeneous systems, OpenCL, Visualization

June 23, 2014 by hgpu

A Portable OpenCL Lattice Boltzmann Code for Multi- and Many-core Processor Architectures

Enrico Calore, Sebastiano Fabio Schifano, Raffaele Tripiccione

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Tags: CUDA, Fluid dynamics, Heterogeneous systems, Intel Xeon Phi, Lattice Boltzmann model, nVidia, OpenCL, Tesla K20

June 17, 2014 by hgpu

HAM – Heterogenous Active Messages for Efficient Offloading on the Intel Xeon Phi

Matthias Noack

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Tags: Computer science, Heterogeneous systems, Intel Xeon Phi, MPI

June 17, 2014 by hgpu

An in-depth performance analysis of irregular workloads on VLIW APU

Matthew Doerksen

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Tags: APU, ATI, ATI Radeon HD 7970, Computer science, Heterogeneous systems, OpenCL, Performance, Thesis

June 16, 2014 by hgpu

Toward OpenCL Automatic Multi-Device Support

Henry Sylvain, Alexandre Denis, Denis Barthou, Marie-Christine Counilh, Raymond Namyst

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Tags: ATI, ATI Radeon HD 7970, Computer science, Heterogeneous systems, nVidia, nVidia Quadro FX 5800, OpenCL, Tesla M2075

June 15, 2014 by hgpu

Dynamic loop vectorization for executing OpenCL kernels on CPUs

Izzat El Hajj

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Tags: Computer science, Heterogeneous systems, OpenCL, Performance, Thesis

June 14, 2014 by hgpu

Unified Development for Mixed Multi-GPU and Multi-Coprocessor Environments using a Lightweight Runtime Environment

Azzam Haidar, Chongxiao Cao, Asim YarKhan, Piotr Luszczek, Stanimire Tomov, Khairul Kabir, Jack Dongarra

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Tags: Algorithms, Computer science, CUDA, Heterogeneous systems, Intel Xeon Phi, Linear Algebra, nVidia, Tesla K20, Tesla M2090

June 14, 2014 by hgpu

Secure Distributed Computing on a Manycore Cloud

Flavio Lombardi

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Tags: Cloud, Computer science, CUDA, Data acquisition, Distributed computing, Heterogeneous systems, nVidia, nVidia GeForce GT 640, Security, Tesla C2050, Thesis

June 13, 2014 by hgpu

Multi-threaded Kernel Offloading to GPGPU Using Hyper-Q on Kepler Architecture

Florian Wende, Thomas Steinke, Frank Cordes

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, Tesla K20, Tesla M2090

June 12, 2014 by hgpu

Native Offload of Haskell Repa Programs to GPGPU

H. Liu, L.E. Day, N. Glew, T.A. Anderson, R. Barik

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Tags: Heterogeneous systems, Intel HD 4600, OpenCL, Parallelization, Programming techniques

June 8, 2014 by hgpu

Mapping parallel programs to heterogeneous multi-core systems

Dominik Grewe

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Tags: Algorithms, ATI, ATI Radeon HD 7990, Computer science, Heterogeneous systems, Machine learning, nVidia, nVidia GeForce GTX 580, OpenCL, Package, Thesis

June 5, 2014 by hgpu

hpcbench: A set of benchmarking utilities for biomolecular simulation tools

Engineering Supercomputing Platforms for Biomolecular Applications

HPCTransCompile: An AI Compiler Generated Dataset for High-Performance CUDA Transpilation and LLM Preliminary Exploration

Efficient Graph Embedding at Scale: Optimizing CPU-GPU-SSD Integration

Can Large Language Models Predict Parallel Code Performance?

See all packages

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high performance computing on graphics processing units: hgpu.org

On the Characterization of OpenCL Dwarfs on Fixed and Reconfigurable Platforms

Runtime Visualization of Application Progress and Monitoring of a GPU-enabled Parallel Environment

A Portable OpenCL Lattice Boltzmann Code for Multi- and Many-core Processor Architectures

HAM – Heterogenous Active Messages for Efficient Offloading on the Intel Xeon Phi

An in-depth performance analysis of irregular workloads on VLIW APU

Toward OpenCL Automatic Multi-Device Support

Dynamic loop vectorization for executing OpenCL kernels on CPUs

Unified Development for Mixed Multi-GPU and Multi-Coprocessor Environments using a Lightweight Runtime Environment

Multi-threaded Kernel Offloading to GPGPU Using Hyper-Q on Kepler Architecture

Native Offload of Haskell Repa Programs to GPGPU

Mapping parallel programs to heterogeneous multi-core systems

Recent source codes

hpcbench: A set of benchmarking utilities for biomolecular simulation tools

HPCTransCompile: An AI Compiler Generated Dataset for High-Performance CUDA Transpilation and LLM Preliminary Exploration

chemtrain: Training Molecular Dynamics Potentials in JAX

microSYCL: SYCL micro-benchmarks repository

XaaS containers

CASS: Cuda-Amd aSSembly

Cluser of smartphones for edge computing application using TensorFlow

SYCL Container

Efficient Graph Embedding at Scale: Optimizing CPU-GPU-SSD Integration

Can Large Language Models Predict Parallel Code Performance?

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