high performance computing on graphics processing units: hgpu.org

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Alpaka – An Abstraction Library for Parallel Kernel Acceleration

Erik Zenker, Benjamin Worpitz, Rene Widera, Axel Huebl, Guido Juckeland, Andreas Knupfer, Wolfgang E. Nagel, Michael Bussmann

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Tags: Computer science, CUDA, Mathematical Software, nVidia, OpenMP, Package, performance portability, Portability, Tesla K20, Tesla K80

March 1, 2016 by hgpu

Auto-Vectorizing a Large-scale Production Unstructured-mesh CFD Application

G.R. Mudalige, I.Z. Reguly, M.B. Giles

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Tags: cfd, Code generation, Computer science, CUDA, Fluid dynamics, Fortran, nVidia, Programming techniques, Tesla K80

February 25, 2016 by hgpu

Algorithms and Heuristics for Scalable Betweenness Centrality Computation on Multi-GPU Systems

Flavio Vella, Giancarlo Carbone, Massimo Bernaschi

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Tags: Algorithms, Computer science, CUDA, Data Structures and Algorithms, Graph theory, nVidia, OpenMPI, Tesla K20, Tesla K80

February 3, 2016 by hgpu

Exploring LLVM Infrastructure for Simplified Multi-GPU Programming

Alexander Matz, Mark Hummel, Holger Froning

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Tags: Computer science, CUDA, LLVM, nVidia, OpenCL, Tesla K80

January 22, 2016 by hgpu

GPU Remote Memory Access Programming

Jeremia Bar

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Tags: Computer science, CUDA, GPU cluster, MPI, nVidia, OpenMPI, Tesla K80, Thesis

January 12, 2016 by hgpu

Pulsar Acceleration Searches on the GPU for the Square Kilometre Array

Sofia Dimoudi, Wesley Armour

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Tags: Astrophysics, CUDA, Instrumentation and Methods for Astrophysics, nVidia, nVidia GeForce GTX Titan X, Tesla K80

November 25, 2015 by hgpu

A polyphase filter for many-core architectures

Karel Adamek, Jan Novotny, Wes Armour

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Tags: Algorithms, CUDA, Intel Xeon Phi, nVidia, nVidia GeForce GTX 580, nVidia GeForce GTX 780 Ti, nVidia GeForce GTX 980, nVidia GeForce GTX Titan X, Signal processing, Tesla K40, Tesla K80, Tesla M2090

November 12, 2015 by hgpu

Evaluation of the Intel Xeon Phi and NVIDIA K80 as accelerators for two-dimensional panel codes

Lukas Einkemmer

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Tags: Computer science, CUDA, Differential equations, Intel Xeon Phi, nVidia, Partial differential equations, PDEs, Performance, Tesla K80

November 10, 2015 by hgpu

Accelerating the D3Q19 Lattice Boltzmann Model with OpenACC and MPI

Alessandro Gabbana

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Tags: Fluid dynamics, Heterogeneous systems, Lattice Boltzmann model, MPI, nVidia, OpenACC, Tesla K80, Thesis

October 11, 2015 by hgpu

Adaptive and Transparent Cache Bypassing for GPUs

Ang Li, Gert-Jan van den Braak, Akash Kumar, Henk Corporaal

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Tags: Benchmarking, cache, Computer science, Memory, nVidia, nVidia GeForce GTX 460, nVidia GeForce GTX 570, nVidia GeForce GTX 690, nVidia GeForce GTX 750 Ti, nVidia GeForce GTX 980, Performance, PTX, Tesla K40, Tesla K80

September 24, 2015 by hgpu

Parallel Execution of the ASP Computation – an Investigation on GPUs

Agostino Dovier, Andrea Formisano, Enrico Pontelli, Flavio Vella

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Tags: Artificial intelligence, Computer science, CUDA, nVidia, nVidia GeForce GT 520, nVidia GeForce GT 640, nVidia GeForce GTX Titan X, Search strategies, Tesla C2075, Tesla K20, Tesla K80

September 5, 2015 by hgpu

A parallel algorithm for implicit depletant simulations

Jens Glaser, Andrew S. Karas, Sharon C. Glotzer

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Tags: Condensed matter, CUDA, Molecular dynamics, nVidia, Package, Physics, Soft Condensed Matter, Tesla K20, Tesla K80

August 31, 2015 by hgpu

Over-synchronization in GPU Programs

profile_util: simple C++ library to report memory, timing, thread affinity

Profile Util library: A quick and easy way to get MPI, OpenMP and GPU runtime information

MaC: Mamba CPU performance predictor

MambaCPU: Enhanced Correlation Mining with State Space Models for CPU Performance Prediction

Mixed-precision finite element kernels

Mixed-precision finite element kernels and assembly: Rounding error analysis and hardware acceleration

SHMT: The Simultaneous and Heterogenous Multithreading project

General-Purpose Computing on Tensor Processors

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

EnergyUCB-Bandit

Online Energy Optimization in GPUs: A Multi-Armed Bandit Approach

See all packages

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high performance computing on graphics processing units: hgpu.org

Alpaka – An Abstraction Library for Parallel Kernel Acceleration

Auto-Vectorizing a Large-scale Production Unstructured-mesh CFD Application

Algorithms and Heuristics for Scalable Betweenness Centrality Computation on Multi-GPU Systems

Exploring LLVM Infrastructure for Simplified Multi-GPU Programming

GPU Remote Memory Access Programming

Pulsar Acceleration Searches on the GPU for the Square Kilometre Array

A polyphase filter for many-core architectures

Evaluation of the Intel Xeon Phi and NVIDIA K80 as accelerators for two-dimensional panel codes

Accelerating the D3Q19 Lattice Boltzmann Model with OpenACC and MPI

Adaptive and Transparent Cache Bypassing for GPUs

Parallel Execution of the ASP Computation – an Investigation on GPUs

A parallel algorithm for implicit depletant simulations

Recent source codes

Kokkidio: Kokkos+Eigen - write fast, readable multi-platform code

LLaMA-Inference-Bench

MATAR

Over-synchronization in GPU Programs

profile_util: simple C++ library to report memory, timing, thread affinity

MaC: Mamba CPU performance predictor

Mixed-precision finite element kernels

SHMT: The Simultaneous and Heterogenous Multithreading project

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

EnergyUCB-Bandit

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