high performance computing on graphics processing units: hgpu.org

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GPU: Power vs Performance

Siddhartha Sankar Mondal

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Tags: Benchmarking, Computer science, CUDA, Energy-efficient computing, nVidia, nVidia GeForce GTX 580, Thesis

January 5, 2015 by hgpu

Real-Time Incompressible Fluid Simulation on the GPU

Xiao Nie, Leiting Chen, Tao Xiang

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Tags: 3D Graphics and Realism, CUDA, Fluid dynamics, Fluid simulation, nVidia, nVidia GeForce GTX 480, nVidia GeForce GTX 780, Real-time graphics, Sorting

January 2, 2015 by hgpu

Customization of OpenCL Applications for Efficient Task Mapping under Heterogeneous Platform Constraints

Edoardo Paone, Francesco Robino, Gianluca Palermo, Vittorio Zaccaria, Ingo Sander, Cristina Silvano

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Tags: Computer science, Heterogeneous systems, nVidia, nVidia Quadro NVS 300, OpenCL, Performance

January 2, 2015 by hgpu

Performance comparison of Lattice Boltzmann fluid flow simulation using OpenCL and CUDA frameworks

Jelena Tekic, Predrag Tekic, Milos Rackovic

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Tags: Benchmarking, CUDA, Fluid dynamics, Heterogeneous systems, Java, Lattice Boltzmann model, nVidia, nVidia GeForce GT 220, OpenCL

January 2, 2015 by hgpu

GPU-based acceleration of free energy calculations in solid state physics

Michal Januszewski, Andrzej Ptok, Dawid Crivelli, Bartlomiej Gardas

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Tags: Algorithms, Computational Physics, CUDA, Fortran, nVidia, Physics, Tesla K40

January 2, 2015 by hgpu

Disjunctive Normal Networks

Mehdi Sajjadi, Mojtaba Seyedhosseini, Tolga Tasdizen

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Tags: Computer science, Computer vision, CUDA, Machine learning, Neural and Evolutionary Computing, Neural networks, nVidia

January 2, 2015 by hgpu

Characterization of OpenCL on a Scalable FPGA Architecture

Shanyuan Gao, Jeremy Chritz

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Tags: AES, Computer science, FPGA, OpenCL

December 30, 2014 by hgpu

Extending OmpSs to support CUDA and OpenCL in C, C++ and Fortran Applications

Florentino Sainz, Sergi Mateo, Vicenc Beltran, Jose L. Bosque, Xavier Martorell, Eduard Ayguade

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Tags: Computer science, CUDA, Fortran, nVidia, OpenCL, Tesla M2050

December 30, 2014 by hgpu

A Tool for Automatic Suggestions for Irregular GPU Kernel Optimization

Saeed Taheri

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

December 30, 2014 by hgpu

Spectral classification using convolutional neural networks

Pavel Hala

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Tags: Astrophysics, Computer science, CUDA, Instrumentation and Methods for Astrophysics, Machine learning, Neural and Evolutionary Computing, nVidia, Thesis

December 30, 2014 by hgpu

How to Correctly Deal With Pseudorandom Numbers in Manycore Environments – Application to GPU programming with Shoverand

Jonathan Passerat-Palmbach (ISIMA, UBP, LIMOS), David Hill (LIMOS, UBP, ISIMA)

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Source codes

Tags: Computer science, CUDA, nVidia, Package, Pseudo-random number generators, Stochastic simulation

December 30, 2014 by hgpu

To Use or Not to Use: Graphics Processing Units for Pattern Matching Algorithms

Vajira Thambawita, Roshan Ragel, Dhammika Elkaduwe

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Tags: Algorithms, Benchmarking, Computer science, CUDA, nVidia, nVidia GeForce GT 740 M, Performance, String matching

December 30, 2014 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

See all packages

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high performance computing on graphics processing units: hgpu.org

Programming

GPU: Power vs Performance

Real-Time Incompressible Fluid Simulation on the GPU

Customization of OpenCL Applications for Efficient Task Mapping under Heterogeneous Platform Constraints

Performance comparison of Lattice Boltzmann fluid flow simulation using OpenCL and CUDA frameworks

GPU-based acceleration of free energy calculations in solid state physics

Disjunctive Normal Networks

Characterization of OpenCL on a Scalable FPGA Architecture

Extending OmpSs to support CUDA and OpenCL in C, C++ and Fortran Applications

A Tool for Automatic Suggestions for Irregular GPU Kernel Optimization

Spectral classification using convolutional neural networks

How to Correctly Deal With Pseudorandom Numbers in Manycore Environments – Application to GPU programming with Shoverand

To Use or Not to Use: Graphics Processing Units for Pattern Matching Algorithms

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Tutoring LLM into a Better CUDA Optimizer

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

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