high performance computing on graphics processing units: hgpu.org

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A Comparison of High-Level Design Tools for SoC-FPGA on Disparity Map Calculation Example

Shaodong Qin, Mladen Berekovic

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Tags: ARM, Computer science, FPGA, OpenCL

September 3, 2015 by hgpu

OpenCL 2.0 for FPGAs using OCLAcc

Franz Richter-Gottfried, Alexander Ditter, Dietmar Fey

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Tags: ARM, Computer science, FPGA, OpenCL

September 3, 2015 by hgpu

Fast GPU-based calculations in few-body quantum scattering

V.N. Pomerantsev, V.I. Kukulin, O.A. Rubtsova, S.K. Sakhiev

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Tags: Computational Physics, CUDA, Integral equations, nVidia, nVidia GeForce GTX 670, Physics

September 3, 2015 by hgpu

EMMA: an AMR cosmological simulation code with radiative transfer

Dominique Aubert, Nicolas Deparis, Pierre Ocvirk

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Tags: Astrophysics, Cosmology, CUDA, Instrumentation and Methods for Astrophysics, nVidia, Tesla K20, Tesla M2090

September 3, 2015 by hgpu

A Real-time Coherent Dedispersion Pipeline for the Giant Metrewave Radio Telescope

Kishalay De, Yashwant Gupta

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Tags: Astrophysics, CUDA, Instrumentation and Methods for Astrophysics, nVidia, Tesla C2075

September 3, 2015 by hgpu

Exploiting Hyper-Loop Parallelism in Vectorization to Improve Memory Performance on CUDA GPGPU

Shixiong Xu, David Gregg

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Tags: ARM, Computer science, CUDA, Memory model, nVidia, nVidia GeForce GTX 645, nVidia Jetson TK1

September 3, 2015 by hgpu

Dynamic Memory Allocation for OpenCL

Nadir Gamal Abdelrahim Salih

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Tags: ATI, ATI Radeon HD 7400 M, Computer science, Memory model, OpenCL, Thesis

August 31, 2015 by hgpu

A parallel algorithm for implicit depletant simulations

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

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Source codes

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

August 31, 2015 by hgpu

A GPU-accelerated local search algorithm for the Correlation Clustering problem

Mario Levorato, Lucia Drummond, Yuri Frota, Rosa Figueiredo

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Tags: Algorithms, Clustering, Computer science, CUDA, Metaheuristics, nVidia, Tesla K40

August 31, 2015 by hgpu

High-Speed Object Detection: Design, Study and Implementation of a Detection Framework using Channel Features and Boosting

Tom Runia

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Tags: ATI, ATI Radeon HD 6450, Computer science, Computer vision, Image processing, Machine learning, nVidia, nVidia Jetson TK1, nVidia Tegra, OpenCL, OpenCV, Thesis

August 28, 2015 by hgpu

Boosting Java Performance using GPGPUs

James Clarkson, Christos Kotselidis, Gavin Brown, Mikel Lujan

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Tags: Benchmarking, Computer science, CUDA, Heterogeneous systems, Java, nVidia, Performance, Tesla K20

August 28, 2015 by hgpu

Deep Convolutional Neural Networks for Smile Recognition

Patrick O. Glauner

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Tags: Computer science, CUDA, Deep learning, Neural and Evolutionary Computing, Neural networks, nVidia, Tesla K40, Thesis

August 28, 2015 by hgpu

Tutoring LLM into a Better CUDA Optimizer

Adaptivity in AdaptiveCpp: Optimizing Performance by Leveraging Runtime Information During JIT-Compilation

Kernel Library for LLM Serving

Compiler and Runtime Systems for Generative AI Models

Neptune: Advanced ML Operator Fusion for Locality and Parallelism on GPUs

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high performance computing on graphics processing units: hgpu.org

Programming

A Comparison of High-Level Design Tools for SoC-FPGA on Disparity Map Calculation Example

OpenCL 2.0 for FPGAs using OCLAcc

Fast GPU-based calculations in few-body quantum scattering

EMMA: an AMR cosmological simulation code with radiative transfer

A Real-time Coherent Dedispersion Pipeline for the Giant Metrewave Radio Telescope

Exploiting Hyper-Loop Parallelism in Vectorization to Improve Memory Performance on CUDA GPGPU

Dynamic Memory Allocation for OpenCL

A parallel algorithm for implicit depletant simulations

A GPU-accelerated local search algorithm for the Correlation Clustering problem

High-Speed Object Detection: Design, Study and Implementation of a Detection Framework using Channel Features and Boosting

Boosting Java Performance using GPGPUs

Deep Convolutional Neural Networks for Smile Recognition

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Tutoring LLM into a Better CUDA Optimizer

Adaptivity in AdaptiveCpp: Optimizing Performance by Leveraging Runtime Information During JIT-Compilation

Kernel Library for LLM Serving

Neptune: Advanced ML Operator Fusion for Locality and Parallelism on GPUs

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