high performance computing on graphics processing units: hgpu.org

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Performance evaluation of GPU memory hierarchy using the FFT

Jacobo Lobeiras, Margarita Amor, Ramon Doallo

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Tags: Benchmarking, Computer science, CUDA, FFT, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 480, Performance, Signal processing

March 30, 2012 by hgpu

A Performance Analysis Framework for Identifying Potential Benefits in GPGPU Applications

Jaewoong Sim, Aniruddha Dasgupta, Hyesoon Kim, and Richard Vuduc

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Tags: Analytical model, CUDA, GPGPU architecture, nVidia, Performance benefit prediction, Performance prediction, Tesla C2050

March 30, 2012 by Moaddeli

Scheduling Tasks over Multicore machines enhanced with Accelerators: a Runtime System’s Perspective

Cedric Augonnet

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Tags: Cell processor, Computer science, CUDA, Databases, nVidia, nVidia Quadro FX 4600, nVidia Quadro FX 5800, Task scheduling, Tesla C2050, Tesla M2070, Tesla S1070, Thesis

March 29, 2012 by hgpu

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

A Massively Parallel Approach for Nonlinear Interdependency Analysis of Multivariate Signals with GPGPU

Dan Chen, Lizhe Wang, Dong Cui, Dongchuan Lu, Xiaoli Li, Samee U. Khan, Joanna Kolodziej

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Tags: CUDA, Medicine, Neuroscience, nVidia, nVidia GeForce GTX 580

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

Accelerating the FDTD Method Using SSE and Graphics Processing Units

Matthew J. Livesey

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Tags: Computer science, CUDA, Data parallelism, FDTD, Finite-difference time-domain, nVidia, Tesla M2050, Tesla T10, Thesis

March 28, 2012 by hgpu

Systematic construction, verification and implementation methodology for LDPC codes

Hui Yu, Jing Cui, Yixiang Wang, Yibin Yang

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Tags: Computer science, CUDA, FPGA, nVidia, nVidia GeForce GTX 260, Parity-check codes, Security

March 28, 2012 by hgpu

Fast, parallel and secure cryptography algorithm using Lorenz’s attractor

Anderson Goncalves Marco, Alexandre Souto Martinez, Odemir Martinez Bruno

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce 8800 GT, nVidia GeForce GTX 285, Security

March 28, 2012 by hgpu

Enabling and Scaling Matrix Computations on Heterogeneous Multi-Core and Multi-GPU Systems

Fengguang Song, Stanimire Tomov, Jack Dongarra

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Tags: Algorithms, Computer science, CUDA, Factorization, Heterogeneous systems, nVidia, Tesla M2070

March 28, 2012 by hgpu

Practical and Theoretical Aspects of a Parallel Twig Join Algorithm for XML Processing using a GPGPU

Lila Shnaiderman, Oded Shmueli

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Tags: Algorithms, Computer science, CUDA, Databases, Join, nVidia, nVidia GeForce GTX 480

March 27, 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

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high performance computing on graphics processing units: hgpu.org

Performance evaluation of GPU memory hierarchy using the FFT

A Performance Analysis Framework for Identifying Potential Benefits in GPGPU Applications

Scheduling Tasks over Multicore machines enhanced with Accelerators: a Runtime System’s Perspective

A computing origami: Optimized code generation for emerging parallel platforms

A Massively Parallel Approach for Nonlinear Interdependency Analysis of Multivariate Signals with GPGPU

Machine Learning for Predictive Auto-Tuning with Boosted Regression Trees

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

Accelerating the FDTD Method Using SSE and Graphics Processing Units

Systematic construction, verification and implementation methodology for LDPC codes

Fast, parallel and secure cryptography algorithm using Lorenz’s attractor

Enabling and Scaling Matrix Computations on Heterogeneous Multi-Core and Multi-GPU Systems

Practical and Theoretical Aspects of a Parallel Twig Join Algorithm for XML Processing using a GPGPU

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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