high performance computing on graphics processing units: hgpu.org

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Fast, parallel implementation of particle filtering on the GPU architecture

Anna Gelencser-Horvath, Gabor Janos Tornai, Andras Horvath, Gyorgy Cserey,

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Tags: Computer science, CUDA, Filtering, nVidia, nVidia GeForce GTX 550 Ti, Particle filtering

September 28, 2013 by hgpu

From OpenCL to Gates: the FFT

Joao Andrade, Vitor Silva, Gabriel Falcao

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Tags: Algorithms, Computer science, FFT, FPGA, nVidia, nVidia GeForce GTX 680, OpenCL

September 28, 2013 by hgpu

Performance Improvement of Optical Algorithms on Multicore Platforms

Ratnakar Madan

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Tags: Algorithms, Computer science, CUDA, FPGA, nVidia, nVidia GeForce GTX 580, Optics, Thesis

September 28, 2013 by hgpu

Efficient Computation of k-Nearest Neighbour Graphs for Large High-Dimensional Data Sets on GPU Clusters

Ali Dashti, Ivan Komarov, Roshan M. D'Souza

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Tags: Computer science, CUDA, GPU cluster, Nearest neighbour, nVidia, Tesla C2050

September 28, 2013 by hgpu

Clustering on GPU – A Brief Survey

V.Saveetha, S.Sophia, V.Anusha Sowbarnika

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Tags: Algorithms, Clustering, Computer science, CUDA, nVidia, Review

September 27, 2013 by hgpu

CUD@ASP: Experimenting with GPUs in ASP solving

Flavio Vella, Alessandro Dal Palu, Agostino Dovier, Andrea Formisano, Enrico Pontelli

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GT 520, nVidia GeForce GT 640, nVidia GeForce GTX 580

September 27, 2013 by hgpu

GPU-TLS: An Efficient Runtime for Speculative Loop Parallelization on GPUs

Chenggang Zhang, Guodong Han, Cho-Li Wang

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 580, Performance, Tesla M2050

September 27, 2013 by hgpu

Java with Auto-Parallelization on Graphics Coprocessing Architecture

Guodong Han, Chenggang Zhang, King Tin Lam, Cho-Li Wang

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Tags: Algorithms, Computer science, CUDA, Heterogeneous systems, Java, nVidia, Performance, Tesla M2050

September 27, 2013 by hgpu

Multi-Scale, Multi-Level, Heterogeneous Features Extraction and Classification of Volumetric Medical Images

Shuai Li, Qinping Zhao, Shengfa Wang, Aimin Hao, Hong Qin

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Tags: Algorithms, CUDA, Diffusion tensor, Image processing, nVidia, nVidia GeForce GTX 330 M

September 27, 2013 by hgpu

Trellis: Portability Across Architectures with a High-level Framework

Lukasz G. Szafaryn, Todd Gamblin, Bronis R. de Supinski, Kevin Skadron

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, OpenACC, Tesla C2050

September 27, 2013 by hgpu

Large Graphs on multi-GPUs

Enrico Mastrostefano

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Tags: Algorithms, Computer science, CUDA, Graph theory, nVidia, Tesla X2090, Thesis

September 25, 2013 by hgpu

Automatic Software Synthesis from High-Level ForSyDe Models Targeting Massively Parallel Processors

George Ungureanu

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Tags: Algorithms, Computer science, CUDA, Data parallelism, Heterogeneous systems, Image processing, nVidia, Thesis

September 25, 2013 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

Fast, parallel implementation of particle filtering on the GPU architecture

From OpenCL to Gates: the FFT

Performance Improvement of Optical Algorithms on Multicore Platforms

Efficient Computation of k-Nearest Neighbour Graphs for Large High-Dimensional Data Sets on GPU Clusters

Clustering on GPU – A Brief Survey

CUD@ASP: Experimenting with GPUs in ASP solving

GPU-TLS: An Efficient Runtime for Speculative Loop Parallelization on GPUs

Java with Auto-Parallelization on Graphics Coprocessing Architecture

Multi-Scale, Multi-Level, Heterogeneous Features Extraction and Classification of Volumetric Medical Images

Trellis: Portability Across Architectures with a High-level Framework

Large Graphs on multi-GPUs

Automatic Software Synthesis from High-Level ForSyDe Models Targeting Massively Parallel Processors

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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