high performance computing on graphics processing units: hgpu.org

hgpu.org » Optimization

Intel’s Array Building Blocks: A retargetable, dynamic compiler and embedded language

Chris J. Newburn, Byoungro So, Zhenying Liu, Michael McCool, Anwar Ghuloum, Stefanus Du Toit, Zhi Gang Wang, Zhao Hui Du, Yongjian Chen, Gansha Wu, Peng Guo, Zhanglin Liu and Dan Zhang

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Tags: Benchmarking, Code generation, Computer science, Heterogeneous systems, Optimization

October 7, 2011 by hgpu

A Framework for Automatic OpenMP Code Generation

A. Raghesh

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Tags: Code generation, Computer science, OpenCL, Optimization, Programming techniques, Thesis

October 7, 2011 by hgpu

Divergence Analysis and Optimizations

Bruno Coutinho, Diogo Sampaio, Fernando Magno Quintao Pereira, Wagner Meira Jr.

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Tags: Algorithms, Benchmarking, Computer science, CUDA, nVidia, nVidia GeForce GTX 260, Optimization, Package, PTX

October 6, 2011 by hgpu

CUDA performance analyzer

Aniruddha Dasgupta

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Tags: Analytical model, Computer science, CUDA, Fast multipole method, nVidia, Optimization, Performance, Tesla C1060, Thesis

October 6, 2011 by hgpu

Profiling Heterogeneous Multi-GPU Systems to Accelerate Cortically Inspired Learning Algorithms

Andrew Nere, Atif Hashmi, Mikko Lipasti

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Tags: Algorithms, Computer science, CUDA, Heterogeneous systems, Image recognition, Neural networks, nVidia, nVidia GeForce 9800 GX2, nVidia GeForce GTX 280, Optimization, Tesla C2050

October 5, 2011 by hgpu

Applying software-managed caching and CPU/GPU task scheduling for accelerating dynamic workloads

Mark Silberstein, Assaf Schuster, John D. Owens

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce 8800 GTX, nVidia GeForce GTX 285, Optimization, Package, Performance, Probability, Task scheduling, Tesla C2050

October 5, 2011 by hgpu

A Framework for Automated Performance Tuning and Code Verification on GPU Computing Platforms

Allison S. Gehrke, Ilkyeun Ra, Daniel A. Connors

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Tags: Code generation, Computer science, Numerical simulation, nVidia, Optimization, Performance, PTX

October 5, 2011 by hgpu

A Massive Data Parallel Computational Framework on Petascale/Exascale Hybrid Computer Systems

Marek Blazewicz, Steven R. Brandt, Peter Diener, David M. Koppelman, Krzysztof Kurowski, Frank Loffler, Erik Schnetter, Jian Tao

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Tags: CUDA, Fluid dynamics, Heterogeneous systems, nVidia, OpenCL, Optimization, Package, Programming techniques, Tesla S1070

October 4, 2011 by hgpu

Architecture-Aware Optimization on a 1600-core Graphics Processor

Mayank Daga, Thomas R.W. Scogland, Wu-chun Feng

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Tags: ATI, ATI Radeon HD 5870, Cluster computing, Computer science, CUDA, Molecular modeling, nVidia, nVidia GeForce GTX 280, OpenCL, Optimization, Tesla C2050

October 4, 2011 by hgpu

Optimization of the Gaussian Mixture Model Evaluation on GPU

Jan Vanek, Jan Trmal, Josef V. Psutka, Josef Psutka

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GT 240, nVidia GeForce GTX 260, OpenCL, Optimization, Speech recognition

October 4, 2011 by hgpu

Implementation of the optimization algorithms on GPGPU architecture and multi-cores

Li Liang

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Tags: Algorithms, Computer science, CUDA, Neural networks, nVidia, OpenCL, Optimization

October 3, 2011 by hgpu

Heterogeneous Computing with OpenCL

Benedict Gaster, David R. Kaeli, Lee Howes, Perhaad Mistry, Dana Schaa

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Tags: Algorithms, Book, Computer science, Heterogeneous systems, OpenCL, Optimization, Tutorial

October 3, 2011 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

Intel’s Array Building Blocks: A retargetable, dynamic compiler and embedded language

A Framework for Automatic OpenMP Code Generation

Divergence Analysis and Optimizations

CUDA performance analyzer

Profiling Heterogeneous Multi-GPU Systems to Accelerate Cortically Inspired Learning Algorithms

Applying software-managed caching and CPU/GPU task scheduling for accelerating dynamic workloads

A Framework for Automated Performance Tuning and Code Verification on GPU Computing Platforms

A Massive Data Parallel Computational Framework on Petascale/Exascale Hybrid Computer Systems

Architecture-Aware Optimization on a 1600-core Graphics Processor

Optimization of the Gaussian Mixture Model Evaluation on GPU

Implementation of the optimization algorithms on GPGPU architecture and multi-cores

Heterogeneous Computing with OpenCL

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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