high performance computing on graphics processing units: hgpu.org

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cellGPU: massively parallel simulations of dynamic vertex models

Daniel M. Sussman

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Tags: Biological Physics, CUDA, nVidia, Package, Physics, Tesla K40

February 14, 2017 by hgpu

Accelerating Binarized Neural Networks: Comparison of FPGA, CPU, GPU, and ASIC

Eriko Nurvitadhi, David Sheffield, Jaewoong Sim, Asit Mishra, Ganesh Venkatesh, Debbie Marr

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Tags: Algorithms, ASIC, Computer science, CUDA, Deep learning, FPGA, Neural networks, nVidia, nVidia GeForce GTX Titan X, nVidia Tegra TX1, Performance

February 14, 2017 by hgpu

Development of JavaScript-based deep learning platform and application to distributed training

Masatoshi Hidaka, Ken Miura, Tatsuya Harada

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Tags: Computer science, Deep learning, Java, Neural networks, nVidia, OpenCL, Package, Tesla K80, WebCL

February 10, 2017 by hgpu

gearshifft – The FFT Benchmark Suite for Heterogeneous Platforms

Peter Steinbach, Matthias Werner

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Tags: Algorithms, Benchmarking, Computer science, FFT, Heterogeneous systems, nVidia, nVidia GeForce GTX 1080, OpenCL, Package, Tesla K20, Tesla K80, Tesla P100

February 10, 2017 by hgpu

Acceleration of low-latency gravitational wave searches using Maxwell-microarchitecture GPUs

Xiangyu Guo, Qi Chu, Shin Kee Chung, Zhihui Du, Linqing Wen

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Tags: Astrophysics, CUDA, Filtering, Gravitation, Gravitational waves, nVidia, nVidia GeForce GTX 980

February 10, 2017 by hgpu

Backpropagation Training for Fisher Vectors within Neural Networks

Patrick Wieschollek, Fabian Groh, Hendrik P.A. Lensch

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Tags: Computer science, Computer vision, CUDA, Neural networks, nVidia, nVidia GeForce GTX Titan X

February 10, 2017 by hgpu

Recurrent Neural Networks for anomaly detection in the Post-Mortem time series of LHC superconducting magnets

Maciej Wielgosz, Andrzej Skoczen, Matej Mertik

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Tags: CUDA, Deep learning, Instrumentation and Detectors, Keras, LSTM, Machine learning, Neural networks, nVidia, Physics, RNN, Tesla K80, Theano

February 7, 2017 by hgpu

Machines and Algorithms

Peter A Boyle

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Tags: Algorithms, Computational Physics, CUDA, HEP, High Energy Physics - Lattice, Intel Xeon Phi, nVidia, Physics, QCD, Review

February 7, 2017 by hgpu

Introduction to the Special Issue on Digital Signal Processing in Radio Astronomy

Danny C. Price, Jonathon Kocz, Matthew Bailes, Lincoln J. Greenhill

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Tags: Astrophysics, CUDA, DSP, FPGA, nVidia, Overview, Signal processing

February 7, 2017 by hgpu

A Dynamic Programming Model To Solve Optimisation Problems Using GPUs

Jonathan Francis O'Connell

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 960, nVidia GeForce GTX Titan, Optimisation, Thesis

February 7, 2017 by hgpu

Advanced Concurrency Control Algorithm Design and GPU System Support for High Performance In-Memory Data Management

Yuan Yuan

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Tags: Algorithms, ATI, ATI Radeon HD 7970, Computer science, CUDA, Databases, nVidia, nVidia GeForce GTX 480, nVidia GeForce GTX 580, nVidia GeForce GTX 680, OpenCL, Thesis

February 7, 2017 by hgpu

Critical Comparison of the Classification Ability of Deep Convolutional Neural Network Frameworks with Support Vector Machine Techniques in the Image Classification Process

Robert T. Kelly

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Tags: Computer science, Deep learning, Image processing, Machine learning, Neural networks, nVidia, nVidia GeForce GTX 970, Theano, Thesis, Torch

February 5, 2017 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

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high performance computing on graphics processing units: hgpu.org

cellGPU: massively parallel simulations of dynamic vertex models

Accelerating Binarized Neural Networks: Comparison of FPGA, CPU, GPU, and ASIC

Development of JavaScript-based deep learning platform and application to distributed training

gearshifft – The FFT Benchmark Suite for Heterogeneous Platforms

Acceleration of low-latency gravitational wave searches using Maxwell-microarchitecture GPUs

Backpropagation Training for Fisher Vectors within Neural Networks

Recurrent Neural Networks for anomaly detection in the Post-Mortem time series of LHC superconducting magnets

Machines and Algorithms

Introduction to the Special Issue on Digital Signal Processing in Radio Astronomy

A Dynamic Programming Model To Solve Optimisation Problems Using GPUs

Advanced Concurrency Control Algorithm Design and GPU System Support for High Performance In-Memory Data Management

Critical Comparison of the Classification Ability of Deep Convolutional Neural Network Frameworks with Support Vector Machine Techniques in the Image Classification Process

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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