high performance computing on graphics processing units: hgpu.org

Luigi Nardi, Bruno Bodin, M. Zeeshan Zia, John Mawer, Andy Nisbet, Paul H. J. Kelly, Andrew J. Davison, Mikel Lujan, Michael F. P. O'Boyle, Graham Riley, Nigel Topham, Steve Furber

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Tags: Algorithms, ARM, Benchmarking, Computer science, Computer vision, CUDA, nVidia, nVidia GeForce GTX Titan, OpenCL, Performance

October 10, 2014 by hgpu

Code Refinement of Stencil Codes

Marcel Koster, Roland Leissa, Sebastian Hack

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Tags: Algorithms, Computer science, CUDA, DSL, nVidia, nVidia GeForce GTX 580, nVidia GeForce GTX 680

October 10, 2014 by hgpu

Parallel implementation of linear repetitive processes identification using subspace algorithms

Dominik Kujawa

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 460

October 10, 2014 by hgpu

Accelerating Protein Coordinate Conversion using GPUs

Mahsa Bayati, Jaydeep P. Bardhan, David M. King, Miriam Leeser

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Tags: Algorithms, Bioinformatics, Biology, CUDA, nVidia, Tesla C2075

October 10, 2014 by hgpu

FDTD on Distributed Heterogeneous Multi-GPU Systems

Eirik Myklebost

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Tags: Algorithms, Benchmarking, Cluster computing, CUDA, Electrodynamics, FDTD, Finite-difference time-domain, Heterogeneous systems, MPI, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 470, nVidia GeForce GTX 760, Physics, Tesla K20, Thesis, Ultrasound

October 10, 2014 by hgpu

cuDNN: Efficient Primitives for Deep Learning

Sharan Chetlur, Cliff Woolley, Philippe Vandermersch, Jonathan Cohen, John Tran, Bryan Catanzaro, Evan Shelhamer

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Tags: Computer science, CUDA, Machine learning, Mathematical Software, Neural and Evolutionary Computing, nVidia, nVidia GeForce GTX 980, Tesla K40

October 8, 2014 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

Programming

Towards Efficient Indexing of Spatiotemporal Trajectories on the GPU for Distance Threshold Similarity Searches

Mapping dynamic programming algorithms on graphics processing units

Interactive Simulations with Navier-Stokes Equations on many-core Architectures

Monte Carlo Path Tracing with OpenCL

Performance Improvement of Multichannel Audio by Graphics Processing Units

Leo: A Profile-Driven Dynamic Optimization Framework for GPU Applications

Introducing SLAMBench, a performance and accuracy benchmarking methodology for SLAM

Code Refinement of Stencil Codes

Parallel implementation of linear repetitive processes identification using subspace algorithms

Accelerating Protein Coordinate Conversion using GPUs

FDTD on Distributed Heterogeneous Multi-GPU Systems

cuDNN: Efficient Primitives for Deep Learning

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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