high performance computing on graphics processing units: hgpu.org

Programming

hgpu.org » Programming

Compression of Deep Convolutional Neural Networks for Fast and Low Power Mobile Applications

Yong-Deok Kim, Eunhyeok Park, Sungjoo Yoo, Taelim Choi, Lu Yang, Dongjun Shin

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Tags: ARM, Bayesian, Caffe, CNN, Computer science, CUDA, Deep learning, Machine learning, Neural networks, nVidia, nVidia GeForce GTX Titan X

November 24, 2015 by hgpu

Comparative Study of Caffe, Neon, Theano, and Torch for Deep Learning

Soheil Bahrampour, Naveen Ramakrishnan, Lukas Schott, Mohak Shah

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Tags: Caffe, Computer science, CUDA, Deep learning, Machine learning, nVidia, nVidia GeForce GTX Titan X

November 24, 2015 by hgpu

Large Scale Artificial Neural Network Training Using Multi-GPUs

Linnan Wang, Wei Wu, Jianxiong Xiao, Yang Yi

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Tags: Algorithms, Computer science, CUDA, Deep learning, Machine learning, Matrix multiplication, Neural and Evolutionary Computing, Neural networks, nVidia, nVidia GeForce GTX Titan X, Tesla K40

November 20, 2015 by hgpu

Supervised Hashing with Deep Neural Networks

Ziming Zhang, Yuting Chen, Venkatesh Saligrama

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Tags: Computer science, CUDA, Deep learning, Hashing, Neural and Evolutionary Computing, Neural networks, nVidia, nVidia GeForce GTX Titan

November 20, 2015 by hgpu

GPU-accelerated adjoint algorithmic differentiation

Felix Gremse, Andreas Hofter, Lukas Razik, Fabian Kiessling, Uwe Naumann

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Tags: Algorithms, Computer science, CUDA, Image reconstruction, nVidia, nVidia GeForce GTX Titan Black, Tomography

November 20, 2015 by hgpu

GPU-Based Inverse Rendering With Multi-Objective Particle Swarm Optimization

Koki Nagano, Thomas Collins, Chi-An Chen, Aiichiro Nakano

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Tags: Algorithms, Computer science, GLSL, Particle swarm optimization, Rendering, Visualization

November 20, 2015 by hgpu

GEMMbench: a framework for reproducible and collaborative benchmarking of matrix multiplication

Anton Lokhmotov

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Tags: ARM, Benchmarking, Computer science, Linear Algebra, Mathematical Software, Matrix multiplication, OpenCL, Package, Performance

November 13, 2015 by hgpu

Accelerating Adaptive IDW Interpolation Algorithm on a Single GPU

Gang Mei, Liangliang Xu, Nengxiong Xu

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Tags: Algorithms, Computer science, CUDA, Geoscience, nVidia, nVidia GeForce GT 730 M

November 13, 2015 by hgpu

Accelerating Recommender Systems using GPUs

Andre Valente Rodrigues, Alipio Jorge, Ines Dutra

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Tags: Computer science, CUDA, Information Retrieval, nVidia, nVidia GeForce GTX 580

November 13, 2015 by hgpu

A polyphase filter for many-core architectures

Karel Adamek, Jan Novotny, Wes Armour

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Tags: Algorithms, CUDA, Intel Xeon Phi, nVidia, nVidia GeForce GTX 580, nVidia GeForce GTX 780 Ti, nVidia GeForce GTX 980, nVidia GeForce GTX Titan X, Signal processing, Tesla K40, Tesla K80, Tesla M2090

November 12, 2015 by hgpu

Comparison of parallel sorting algorithms

Darko Bozidar, Tomaz Dobravec

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 670, Sorting

November 12, 2015 by hgpu

FIESTA 4: optimized Feynman integral calculations with GPU support

Alexander V. Smirnov

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Tags: CUDA, High Energy Physics - Phenomenology, Mathematical Software, nVidia, Package, Physics, Tesla X2070

November 12, 2015 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

Programming

Compression of Deep Convolutional Neural Networks for Fast and Low Power Mobile Applications

Comparative Study of Caffe, Neon, Theano, and Torch for Deep Learning

Large Scale Artificial Neural Network Training Using Multi-GPUs

Supervised Hashing with Deep Neural Networks

GPU-accelerated adjoint algorithmic differentiation

GPU-Based Inverse Rendering With Multi-Objective Particle Swarm Optimization

GEMMbench: a framework for reproducible and collaborative benchmarking of matrix multiplication

Accelerating Adaptive IDW Interpolation Algorithm on a Single GPU

Accelerating Recommender Systems using GPUs

A polyphase filter for many-core architectures

Comparison of parallel sorting algorithms

FIESTA 4: optimized Feynman integral calculations with GPU support

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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