high performance computing on graphics processing units: hgpu.org

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Accelerated MD Program Using CUDA Technology

Hoang Van Hue, Nguyen Thi Thanh Ha, Pham Khac Hung

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Tags: CUDA, Materials Science, Molecular dynamics, nVidia, nVidia GeForce GTS 250, Physics

October 26, 2011 by hgpu

gpustats: GPU Library for Statistical Computing in Python

Andrew Cron, Wes McKinney

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Tags: Algorithms, Bayesian, Code generation, CUDA, Mathematics, nVidia, nVidia GeForce GTS 250, OpenCL, Package, Probability, Python, Statistics

October 13, 2011 by hgpu

Design space exploration towards a realtime and energy-aware GPGPU-based analysis of biosensor data

Constantin Timm, Frank Weichert, Peter Marwedel, Heinrich Muller

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Tags: Computer science, Design space exploration, Energy-efficient computing, Image processing, nVidia, nVidia GeForce 9600 GT, nVidia GeForce GTS 250, nVidia ION, OpenCL, Sensing

September 28, 2011 by hgpu

Utilising OpenCL Framework for Ray-Tracing Acceleration

Pavel Hradsky

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Tags: 3D Graphics and Realism, Computer science, nVidia, nVidia GeForce GTS 250, OpenCL, Raytracing, Thesis

September 24, 2011 by hgpu

Accelerating biomedical signal processing algorithms with parallel programming on graphic processor units

Evdokimos I. Konstantinidis, Christos A. Frantzidis, Lazaros Tzimkas, Costas Pappas, Panagiotis D. Bamidis

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Tags: CUDA, Medicine, nVidia, nVidia GeForce 8600 GT, nVidia GeForce 9600 GT, nVidia GeForce GTS 250, Signal processing

June 6, 2011 by hgpu

Parallel AES algorithm for fast Data Encryption on GPU

Deguang Le, Jinyi Chang, Xingdou Gou, Ankang Zhang, Conglan Lu

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Tags: AES, Computer science, CUDA, nVidia, nVidia GeForce GTS 250, Security

May 4, 2011 by hgpu

CUDA-Based Radiative Transfer Method with Application to the EM Scattering from a Two-Layer Canopy Model

W.-Q. Jiang, M. Zhang, Y. Wang

Tags: CUDA, Electrodynamics, nVidia, nVidia GeForce GTS 250

January 10, 2011 by hgpu

SIML: A Fast SIMD Algorithm for Calculating LINGO Chemical Similarities on GPUs and CPUs

Imran S. Haque, Vijay S. Pande, W. Patrick Walters

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Tags: Chemistry, CUDA, nVidia, nVidia GeForce GTS 250, OpenMP, Package, Tesla T10

November 9, 2010 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

Accelerated MD Program Using CUDA Technology

gpustats: GPU Library for Statistical Computing in Python

Design space exploration towards a realtime and energy-aware GPGPU-based analysis of biosensor data

Utilising OpenCL Framework for Ray-Tracing Acceleration

Accelerating biomedical signal processing algorithms with parallel programming on graphic processor units

Parallel AES algorithm for fast Data Encryption on GPU

CUDA-Based Radiative Transfer Method with Application to the EM Scattering from a Two-Layer Canopy Model

SIML: A Fast SIMD Algorithm for Calculating LINGO Chemical Similarities on GPUs and CPUs

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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