high performance computing on graphics processing units: hgpu.org

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High Performance Adaptive Image Processing on Multi-scale Hybrid Architectures

Fangbin Liu

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Tags: Algorithms, CUDA, Distributed computing, Heterogeneous systems, Image processing, Matrix multiplication, nVidia, nVidia GeForce GTX 295, Thesis

November 10, 2015 by hgpu

Free Launch: Optimizing GPU Dynamic Kernel Launches through Thread Reuse

Guoyang Chen, Xipeng Shen

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Tags: Compilers, Computer science, CUDA, nVidia, Tesla K20, Tesla K40

November 8, 2015 by hgpu

Data Stream Classification using Random Feature Functions and Novel Method Combinations

Diego Marron, Jesse Read, Albert Bifet, Nacho Navarro

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Tags: Computer science, CUDA, Deep learning, Nearest neighbour, Neural networks, nVidia, Tesla K40

November 8, 2015 by hgpu

Deep Learning for Computer Vision: A comparison between Convolutional Neural Networks and Hierarchical Temporal Memories on object recognition tasks

Vincenzo Lomonaco

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Tags: Artificial intelligence, Computer science, Computer vision, CUDA, Deep learning, Machine learning, Neural networks, nVidia, Pattern recognition, Tesla C2075, Thesis

November 8, 2015 by hgpu

Performance of GTX Titan X GPUs and Code Optimization

Hwancheol Jeong, Sangbaek Lee, Weonjong Lee, Jeonghwan Pak, Jangho Kim, Juhyun Chung

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX Titan X, Performance

November 4, 2015 by hgpu

Exact diagonalization of quantum lattice models on coprocessors

Topi Siro, Ari Harju

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Tags: Condensed matter, CUDA, Intel Xeon Phi, Mathematical Software, nVidia, OpenMP, Physics, Tesla K40

November 4, 2015 by hgpu

Heterogeneous CPU/(GP) GPU Memory Hierarchy Analysis and Optimization

Josue Vladimir Quiroga Esparza

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Tags: Computer science, CUDA, Heterogeneous systems, Memory, nVidia, Thesis

November 4, 2015 by hgpu

On the programmability of multi-GPU computing systems

Javier Cabezas Rodriguez

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Tags: Computer science, CUDA, MPI, nVidia, Performance, Tesla C1060, Tesla K20, Tesla K40, Thesis

November 3, 2015 by hgpu

Exploring Optimisations for the Local Assembly phase of Finite Element Methods on GPUs

Hector Dearman

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Tags: Benchmarking, Computer science, CUDA, Differential equations, FEM, Finite element method, nVidia, nVidia GRID K520, OpenCL, Partial differential equations, PDEs, Thesis

November 3, 2015 by hgpu

A Framework for Transparent Execution of Massively-Parallel Applications on CUDA and OpenCL

Jorn Teuber, Rene Weller, Gabriel Zachmann

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 680, OpenCL

November 3, 2015 by hgpu

Software Defined Radio over CUDA

Marco Ribero

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Tags: CUDA, nVidia, nVidia GeForce GT 540 M, Signal processing, Thesis

November 3, 2015 by hgpu

Estimation of numerical reproducibility on CPU and GPU

Fabienne Jezequel, Jean-Luc Lamotte, Issam Said

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Tags: APU, ATI, ATI Radeon HD 7970, Computer science, CUDA, nVidia, OpenCL, Tesla C2050, Tesla K20

October 31, 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

See all packages

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high performance computing on graphics processing units: hgpu.org

High Performance Adaptive Image Processing on Multi-scale Hybrid Architectures

Free Launch: Optimizing GPU Dynamic Kernel Launches through Thread Reuse

Data Stream Classification using Random Feature Functions and Novel Method Combinations

Deep Learning for Computer Vision: A comparison between Convolutional Neural Networks and Hierarchical Temporal Memories on object recognition tasks

Performance of GTX Titan X GPUs and Code Optimization

Exact diagonalization of quantum lattice models on coprocessors

Heterogeneous CPU/(GP) GPU Memory Hierarchy Analysis and Optimization

On the programmability of multi-GPU computing systems

Exploring Optimisations for the Local Assembly phase of Finite Element Methods on GPUs

A Framework for Transparent Execution of Massively-Parallel Applications on CUDA and OpenCL

Software Defined Radio over CUDA

Estimation of numerical reproducibility on CPU and GPU

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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