high performance computing on graphics processing units: hgpu.org

hgpu.org » Optimization

Random Walks based Multi-Image Segmentation: Quasiconvexity Results and GPU-based Solutions

Maxwell D. Collins, Jia Xu, Leo Grady, Vikas Singh

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Tags: Algorithms, CUDA, Image processing, Linear Algebra, nVidia, nVidia GeForce GTX 470, Optimization

April 28, 2012 by hgpu

Characterizing and Improving the Use of Demand-Fetched Caches in GPUs

Wenhao Jia, Kelly A. Shaw, Margaret Martonosi

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Tags: Algorithms, Computer science, CUDA, Memory model, nVidia, Optimization, Performance, Tesla C2070

April 28, 2012 by hgpu

Lynx: A Dynamic Instrumentation System for Data-Parallel Applications on GPGPU Architectures

Naila Farooqui, Andrew Kerr, Greg Eisenhauer, Karsten Schwan, Sudhakar Yalamanchili

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Tags: Code generation, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 480, Optimization, Package, Tesla C2050

April 25, 2012 by hgpu

Parboil: A Revised Benchmark Suite for Scientific and Commercial Throughput Computing

John A. Stratton, Christopher Rodrigues, I-Jui Sung, Nady Obeid, Li-Wen Chang, Nasser Anssari, Geng Daniel Liu, Wen-mei W. Hwu

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Tags: Algorithms, Benchmarking, Computer science, CUDA, Molecular simulation, MPI, nVidia, nVidia GeForce GTX 480, Optimization, Package

April 25, 2012 by hgpu

Visualization of Pareto Solutions by Spherical Self-Organizing Map and It’s acceleration on a GPU

Masato Yoshimi, Takuya Kuhara, Kaname Nishimoto, Mitsunori Miki, Tomoyuki Hiroyasu

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Tags: Computer science, CUDA, nVidia, nVidia GeForce 8400 GS, nVidia GeForce GTX 280, Optimization, Self-organizing map, Tesla C1060, Visualization

April 5, 2012 by hgpu

GPU Programming Strategies and Trends in GPU Computing

Andre R. Brodtkorb, Trond R. Hagen, Martin L. Saetra

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Tags: Computer science, Heterogeneous systems, Optimization, Overview

April 2, 2012 by hgpu

Adaptive Input-aware Compilation for Graphics Engines

Mehrzad Samadi, Amir Hormati, Mojtaba Mehrara, Janghaeng Lee, and Scott Mahlke

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Tags: Compiler, CUDA, GPU, nVidia, nVidia GeForce GTX 285, Optimization, Portability, Streaming, Tesla C2050

March 31, 2012 by Moaddeli

A computing origami: Optimized code generation for emerging parallel platforms

Hagiescu Miriste Andrei Mihai

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Tags: Code generation, Computer science, CUDA, FPGA, nVidia, nVidia GeForce 8800 GTX, Optimization, Tesla S1070, Thesis

March 29, 2012 by hgpu

Machine Learning for Predictive Auto-Tuning with Boosted Regression Trees

James Bergstra, Nicolas Pinto, David Cox

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Tags: Computer science, CUDA, Filtering, Machine learning, Matrix multiplication, nVidia, nVidia GeForce GTX 295, nVidia GeForce GTX 480, nVidia GeForce GTX 580, Optimization, Tesla C1060, Tesla C2070

March 29, 2012 by hgpu

Auto-tuning a High-Level Language Targeted to GPU Codes

Scott Grauer-Gray, Lifan Xu, Robert Searles, Sudhee Ayalasomayajula, John Cavazos

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Tags: Computer science, CUDA, nVidia, nVidia GeForce 9800 GT, nVidia GeForce GTX 280, OpenCL, Optimization, Performance, Programming techniques, Stereo vision, Tesla C2050

March 28, 2012 by hgpu

CUDA 2D Stencil Computations for the Jacobi Method

Jose Maria Cecilia, Jose Manuel Garcia, Manuel Ujaldon

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Tags: Algorithms, Computer science, CUDA, Data parallelism, Differential equations, Linear Algebra, nVidia, Optimization, Tesla C1060, Tesla C870

March 16, 2012 by hgpu

On the Use of Small 2D Convolutions on GPUs

Shams A.H. Al Umairy, Alexander S. van Amesfoort, Irwan D. Setija, Martijn C. van Beurden, Henk J. Sips

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Tags: Computer science, CUDA, Electrodynamics, FFT, nVidia, nVidia GeForce 8800 GTX, nVidia GeForce GTX 280, Optimization, Physics, Tesla C1060

March 15, 2012 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

Random Walks based Multi-Image Segmentation: Quasiconvexity Results and GPU-based Solutions

Characterizing and Improving the Use of Demand-Fetched Caches in GPUs

Lynx: A Dynamic Instrumentation System for Data-Parallel Applications on GPGPU Architectures

Parboil: A Revised Benchmark Suite for Scientific and Commercial Throughput Computing

Visualization of Pareto Solutions by Spherical Self-Organizing Map and It’s acceleration on a GPU

GPU Programming Strategies and Trends in GPU Computing

Adaptive Input-aware Compilation for Graphics Engines

A computing origami: Optimized code generation for emerging parallel platforms

Machine Learning for Predictive Auto-Tuning with Boosted Regression Trees

Auto-tuning a High-Level Language Targeted to GPU Codes

CUDA 2D Stencil Computations for the Jacobi Method

On the Use of Small 2D Convolutions on GPUs

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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