high performance computing on graphics processing units: hgpu.org

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hgpu.org » Applications » Computer science

Performance Improvement of Multichannel Audio by Graphics Processing Units

Jose Antonio Belloch Rodriguez

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Tags: Acoustics, Algorithms, Computer science, CUDA, Databases, Filtering, nVidia, nVidia GeForce GTS 360 M, nVidia GeForce GTX 590, nVidia GeForce GTX 690, nVidia Quadro FX 5800, OpenCL, Rendering, Signal processing, Tesla C2070, Tesla K20, Thesis

October 11, 2014 by hgpu

Leo: A Profile-Driven Dynamic Optimization Framework for GPU Applications

Naila Farooqui, Christopher J. Rossbach, Yuan Yu, Karsten Schwan

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Tags: Benchmarking, Computer science, CUDA, nVidia, PTX, Tesla M2075

October 11, 2014 by hgpu

Introducing SLAMBench, a performance and accuracy benchmarking methodology for SLAM

Luigi Nardi, Bruno Bodin, M. Zeeshan Zia, John Mawer, Andy Nisbet, Paul H. J. Kelly, Andrew J. Davison, Mikel Lujan, Michael F. P. O'Boyle, Graham Riley, Nigel Topham, Steve Furber

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Tags: Algorithms, ARM, Benchmarking, Computer science, Computer vision, CUDA, nVidia, nVidia GeForce GTX Titan, OpenCL, Performance

October 10, 2014 by hgpu

Code Refinement of Stencil Codes

Marcel Koster, Roland Leissa, Sebastian Hack

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Tags: Algorithms, Computer science, CUDA, DSL, nVidia, nVidia GeForce GTX 580, nVidia GeForce GTX 680

October 10, 2014 by hgpu

Parallel implementation of linear repetitive processes identification using subspace algorithms

Dominik Kujawa

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 460

October 10, 2014 by hgpu

cuDNN: Efficient Primitives for Deep Learning

Sharan Chetlur, Cliff Woolley, Philippe Vandermersch, Jonathan Cohen, John Tran, Bryan Catanzaro, Evan Shelhamer

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Tags: Computer science, CUDA, Machine learning, Mathematical Software, Neural and Evolutionary Computing, nVidia, nVidia GeForce GTX 980, Tesla K40

October 8, 2014 by hgpu

KBLAS: An Optimized Library for Dense Matrix-Vector Multiplication on GPU Accelerators

Ahmad Abdelfattah, David Keyes, Hatem Ltaief

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Tags: Computer science, CUBLAS, CUDA, Linear Algebra, Mathematical Software, nVidia, Package, Tesla K20

October 8, 2014 by hgpu

A Framework for the Volumetric Integration of Depth Images

Victor Adrian Prisacariu, Olaf Kahler, Ming Ming Cheng, Julien Valentin, Philip H.S. Torr, Ian D. Reid, David W. Murray

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Tags: Computer science, Computer vision, CUDA, nVidia

October 8, 2014 by hgpu

Using Graphics Processing Unit to Accelerate Database Query Execution

Kamil Ksiazek, Piotr Sapiecha

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Tags: Computer science, Databases, nVidia, nVidia GeForce GTS 450, OpenCL

October 6, 2014 by hgpu

Accelerating NTRU Encryption with Graphics Processing Units

Tianyu Bai, Spencer Davis, Juanjuan Li, Ying Gu, Hai Jiang

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 680, Quantum computing, Security

October 6, 2014 by hgpu

Load Balancing in Data Warehouse – Evolution and Perspectives

Michal Gorawski

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Tags: Algorithms, Cloud, Computer science, CUDA, Machine learning, nVidia, nVidia GeForce 9600 GT, nVidia GeForce GTX 260

October 6, 2014 by hgpu

Embedding GPU Computations in Hadoop

Jie Zhu, Hai Jiang, Juanjuan Li, Erikson Hardesty, Kuan-Ching Li, Zhongwen Li

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Tags: Cloud, Computer science, CUDA, Hadoop, Heterogeneous systems, Java, MapReduce, nVidia, nVidia GeForce GTX 480, Task scheduling

October 6, 2014 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

Applications

Performance Improvement of Multichannel Audio by Graphics Processing Units

Leo: A Profile-Driven Dynamic Optimization Framework for GPU Applications

Introducing SLAMBench, a performance and accuracy benchmarking methodology for SLAM

Code Refinement of Stencil Codes

Parallel implementation of linear repetitive processes identification using subspace algorithms

cuDNN: Efficient Primitives for Deep Learning

KBLAS: An Optimized Library for Dense Matrix-Vector Multiplication on GPU Accelerators

A Framework for the Volumetric Integration of Depth Images

Using Graphics Processing Unit to Accelerate Database Query Execution

Accelerating NTRU Encryption with Graphics Processing Units

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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