high performance computing on graphics processing units: hgpu.org

hgpu.org » Performance

Load Balancing in a Changing World: Dealing with Heterogeneity and Performance Variability

Michael Boyer, Kevin Skadron, Shuai Che, Nuwan Jayasena

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Tags: ATI, ATI Radeon HD 6550, ATI Radeon HD 6670, Computer science, Heterogeneous systems, OpenCL, Performance, Task scheduling

April 8, 2013 by hgpu

Atomic-free Irregular Computations on GPUs

Rupesh Nasre, Martin Burtscher, Keshav Pingali

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Tags: Algorithms, Computer science, CUDA, Graph theory, nVidia, Package, Performance, Tesla K20

April 7, 2013 by hgpu

A Performance Study of Zero Crossing Rate (ZCR) on Graphics Processors (GPUs) Using CUDA

Nydruva Biligere Priyadarshi

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 480, Performance

April 6, 2013 by hgpu

Improving GPU Performance Prediction with Data Transfer Modeling

Michael Boyer, Jiayuan Meng, Kalyan Kumaran

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Tags: Computer science, CUDA, nVidia, nVidia Quadro FX 5600, Performance

April 6, 2013 by hgpu

Optimising Purely Functional GPU Programs

Trevor L. McDonell, Manuel M. T. Chakravarty, Gabriele Keller, Ben Lippmeier

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Tags: Computer science, CUDA, Haskell, nVidia, Package, Performance, Tesla T10

April 4, 2013 by hgpu

Warp Size Impact in GPUs: Large or Small?

Ahmad Lashgar, Amirali Baniasadi, Ahmad Khonsari

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Tags: Computer science, GPGPU-sim, Memory, Performance

March 29, 2013 by hgpu

How to Benefit from AMD, Intel and Nvidia Accelerator Technologies in Scilab

Thibault Person, Francois Bodin

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Tags: ATI, ATI Radeon HD 7970, Computer science, CUDA, Intel, Intel Phi, nVidia, OpenCL, Package, Performance, Portability, Tesla K20

March 24, 2013 by hgpu

Performance study of filtered back-projection algorithms implemented on GPUs

Bruno Faria

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Tags: Computed tomography, CT, CUDA, Image processing, Medicine, nVidia, nVidia GeForce GTX 580, Performance, Tomography

March 21, 2013 by hgpu

General Purpose Computing on Low-Power Embedded GPUs: Has It Come of Age?

Arian Maghazeh, Unmesh D. Bordoloi, Petru Eles, Zebo Peng

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Tags: ARM, Computer science, nVidia, OpenCL, Performance, Tesla M2050

March 20, 2013 by hgpu

Convergence and Scalarization for Data-Parallel Architectures

Yunsup Lee, Ronny Krashinsky, Vinod Grover, Stephen W. Keckler, Krste Asanovic

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Tags: Algorithms, Code generation, Compilers, Computer science, CUDA, Data parallelism, nVidia, Performance

March 15, 2013 by hgpu

Input-Aware Auto-Tuning for Directive-based GPU Programming

Alberto Magni, Dominik Grewe, Nick Johnson

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Tags: Computer science, nVidia, OpenACC, Performance, Programming techniques, Tesla C2050

March 15, 2013 by hgpu

Just-in-time Acceleration of JavaScript

Uday Pitambare, Arun Chauhan, Saurabh Malviya

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Tags: Computer science, Java, nVidia, Performance, PTX, Tesla C1060

March 12, 2013 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

Load Balancing in a Changing World: Dealing with Heterogeneity and Performance Variability

Atomic-free Irregular Computations on GPUs

A Performance Study of Zero Crossing Rate (ZCR) on Graphics Processors (GPUs) Using CUDA

Improving GPU Performance Prediction with Data Transfer Modeling

Optimising Purely Functional GPU Programs

Warp Size Impact in GPUs: Large or Small?

How to Benefit from AMD, Intel and Nvidia Accelerator Technologies in Scilab

Performance study of filtered back-projection algorithms implemented on GPUs

General Purpose Computing on Low-Power Embedded GPUs: Has It Come of Age?

Convergence and Scalarization for Data-Parallel Architectures

Input-Aware Auto-Tuning for Directive-based GPU Programming

Just-in-time Acceleration of JavaScript

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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