high performance computing on graphics processing units: hgpu.org

Programming

hgpu.org » Programming

A power-aware symbiotic scheduling algorithm for concurrent GPU kernels

Teng Li, Vikram K. Narayana, Tarek El-Ghazawi

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Tags: Algorithms, Computer science, CUDA, nVidia, Performance, Task scheduling, Tesla K20

February 1, 2016 by hgpu

Accelerating the Critical Line Algorithm for Portfolio Optimization Using GPUs

Raja H. Singh, Lee Barford, Frederick Harris Jr.

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Tags: Algorithms, Computer science, CUDA, Finance, nVidia, nVidia GeForce GTX 780

February 1, 2016 by hgpu

Deep learning review and its applications

Andoni Azkarate Saiz

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Tags: Computer science, CUDA, Deep learning, Machine learning, Neural networks, nVidia, nVidia GeForce GTX 660, Review, Thesis

February 1, 2016 by hgpu

R2GUESS: A Graphics Processing Unit-Based R Package for Bayesian Variable Selection Regression of Multivariate Responses

Benoit Liquet, Leonardo Bottolo, Gianluca Campanella, Sylvia Richardson, Marc Chadeau-Hyam

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Tags: Bayesian, Computer science, CUDA, CULA, nVidia, Package

February 1, 2016 by hgpu

A Reproducible Research Methodology for Designing and Conducting Faithful Simulations of Dynamic HPC Applications

Luka Stanisic

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Tags: Computer science, CUDA, Heterogeneous systems, Linear Algebra, nVidia, nVidia Quadro FX 5800, Tesla C2050, Tesla K20, Tesla K40, Tesla M2070, Tesla M2075, Thesis

February 1, 2016 by hgpu

GPU Based Methods for Interactive Information Visualization of Big Data

Peng Mi

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 680, OpenGL, Thesis, Visualization

January 29, 2016 by hgpu

Towards Interactive Visual Exploration of Parallel Programs using a Domain-specific Language

Tobias Klein

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Tags: Computer science, CUDA, DSL, Heterogeneous systems, Image processing, nVidia, nVidia Quadro 6000, OpenCL, Thesis, Visualization

January 29, 2016 by hgpu

GPU-Accelerated Recurrent Neural Networks: OpenCLLink and SymbolicC

Zdenek Buk

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Tags: Computer science, Deep learning, Machine learning, Neural networks, nVidia, OpenCL, Package, RNN

January 29, 2016 by hgpu

High-Performance Tensor Contractions for GPUs

A. Abdelfattah, M. Baboulin, V. Dobrev, J. Dongarra, C. Earl, J. Falcou, A. Haidar, I. Karlin, Tz. Kolev, I. Masliah, S. Tomov

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Tags: Algorithms, Code generation, Computer science, CUDA, FEM, Finite element method, Linear Algebra, Matrix multiplication, nVidia, OpenMP, Tesla K40

January 29, 2016 by hgpu

GeNN: a code generation framework for accelerated brain simulations

Esin Yavuz, James Turner, Thomas Nowotny

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Tags: Biology, Code generation, CUDA, Neural networks, Neuroscience, Numerical simulation, nVidia, nVidia Quadro K 2000 M, Package, Tesla C2070, Tesla K40

January 29, 2016 by hgpu

Compositional Compilation for Sparse, Irregular Data Parallelism

Adam Harries, Michel Steuwer, Murray Cole, Alan Gray, Christophe Dubach

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Tags: Computer science, Data parallelism, nVidia, OpenCL, Sparse matrix, Tesla K40

January 26, 2016 by hgpu

Improving GPU-accelerated Adaptive IDW Interpolation Algorithm Using Fast kNN Search

Gang Mei, Nengxiong Xu, Liangliang Xu

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

January 26, 2016 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

A power-aware symbiotic scheduling algorithm for concurrent GPU kernels

Accelerating the Critical Line Algorithm for Portfolio Optimization Using GPUs

Deep learning review and its applications

R2GUESS: A Graphics Processing Unit-Based R Package for Bayesian Variable Selection Regression of Multivariate Responses

A Reproducible Research Methodology for Designing and Conducting Faithful Simulations of Dynamic HPC Applications

GPU Based Methods for Interactive Information Visualization of Big Data

Towards Interactive Visual Exploration of Parallel Programs using a Domain-specific Language

GPU-Accelerated Recurrent Neural Networks: OpenCLLink and SymbolicC

High-Performance Tensor Contractions for GPUs

GeNN: a code generation framework for accelerated brain simulations

Compositional Compilation for Sparse, Irregular Data Parallelism

Improving GPU-accelerated Adaptive IDW Interpolation Algorithm Using Fast kNN Search

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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