high performance computing on graphics processing units: hgpu.org

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A mixed precision semi-Lagrangian algorithm and its performance on accelerators

Lukas Einkemmer

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Tags: Computational Physics, Computer science, CUDA, Intel Xeon Phi, Mathematical Software, Mixed precision, nVidia, OpenMP, Tesla K80

March 25, 2016 by hgpu

Comparison of Technologies for General-Purpose Computing on Graphics Processing Units

Torbjorn Sorman

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Tags: AMD Radeon R7 260X, ATI, Benchmarking, Computer science, DirectCompute, DirectX, nVidia, nVidia GeForce GTX 670, OpenCL, OpenGL, Performance, Thesis

March 22, 2016 by hgpu

Proteus: Efficient Resource Use in Heterogeneous Architectures

Sankaralingam Panneerselvam, Michael M. Swift

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Tags: Computer science, Heterogeneous systems, nVidia, nVidia GeForce GTX 650, nVidia GeForce GTX 670, OpenCL, Task scheduling

March 22, 2016 by hgpu

Recurrent neural networks for language modeling

Emil Sauer Lynge

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Tags: Computer science, CUDA, Deep learning, LSTM, Neural networks, NLP, nVidia, nVidia GeForce GTX Titan X, Package, Python, RNN, Thesis

March 22, 2016 by hgpu

OpenCL Cryptographic Library

Martin Preisler

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Tags: AES, Algorithms, Computer science, Intel HD Graphics 4000, nVidia, nVidia GeForce GT 650 M, nVidia GeForce GTX 460, nVidia GeForce GTX 580, OpenCL, Security, Thesis

March 20, 2016 by hgpu

Automatic Detection and Denoising of Signals in Large Geophysical Datasets

Gabriel O. Trisca

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Tags: Aparapi, Computer science, Machine learning, Neural networks, nVidia, nVidia GeForce GTX Titan, OpenCL, RNN, Seismology, Sensing, Signal denoising, Tesla K20, Thesis

March 20, 2016 by hgpu

Acceleration of ensemble machine learning methods using many-core devices

A. Tamerus, A. Washbrook, D. Wyeth

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Tags: Computer science, CUDA, Machine learning, nVidia, Physics, Tesla K40

March 20, 2016 by hgpu

A Massively Parallel Algorithm for Cell Classification Using CUDA

Samuel Schmidt

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Tags: Bioinformatics, Biology, CUDA, Machine learning, nVidia, nVidia GeForce GTX 770, RNA, Thesis

March 20, 2016 by hgpu

Analyzing and Improving the Performance of Spatial Database Processing

Bogdan Simion

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Tags: Computer science, CUDA, Databases, nVidia, nVidia GeForce GTX 480, nVidia GeForce GTX 580, Thesis

March 20, 2016 by hgpu

DeepX: A Software Accelerator for Low-Power Deep Learning Inference on Mobile Devices

Nicholas D. Lane, Sourav Bhattacharya, Petko Georgiev, Claudio Forlivesi, Lei Jiao, Lorena Qendro, Fahim Kawsar

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Tags: Computer science, CUDA, Deep learning, Heterogeneous systems, nVidia, nVidia Jetson TK1, SoC

March 15, 2016 by hgpu

Towards Automatic Learning of Heuristics for Mechanical Transformations of Procedural Code

Guillermo Vigueras, Manuel Carro, Salvador Tamarit, Julio Marino

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Tags: Computer science, Heterogeneous systems, Machine learning, OpenCL, Programming Languages

March 15, 2016 by hgpu

Melia: A MapReduce Framework on OpenCL-based FPGAs

Zeke Wang, Shuhao Zhang, Bingsheng He, Wei Zhang

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Tags: Computer science, FPGA, MapReduce, OpenCL, Package

March 15, 2016 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

A mixed precision semi-Lagrangian algorithm and its performance on accelerators

Comparison of Technologies for General-Purpose Computing on Graphics Processing Units

Proteus: Efficient Resource Use in Heterogeneous Architectures

Recurrent neural networks for language modeling

OpenCL Cryptographic Library

Automatic Detection and Denoising of Signals in Large Geophysical Datasets

Acceleration of ensemble machine learning methods using many-core devices

A Massively Parallel Algorithm for Cell Classification Using CUDA

Analyzing and Improving the Performance of Spatial Database Processing

DeepX: A Software Accelerator for Low-Power Deep Learning Inference on Mobile Devices

Towards Automatic Learning of Heuristics for Mechanical Transformations of Procedural Code

Melia: A MapReduce Framework on OpenCL-based FPGAs

Recent source codes

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Atlas CLI: Machine Learning (ML) Lifecycle & Transparency Manager

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NCCLX: collective communication framework

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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