high performance computing on graphics processing units: hgpu.org

hgpu.org » nVidia GeForce GTX 280

Multiple String Matching on a GPU using CUDAs

Charalampos S. Kouzinopoulos, Panagiotis D. Michailidis, Konstantinos G. Margaritis

View

Download (PDF)

Tags: Algorithms, Biology, Computer science, CUDA, nVidia, nVidia GeForce GTX 280, String matching

July 10, 2015 by hgpu

GPU concurrency: Weak behaviours and programming assumptions

Jade Alglave, Mark Batty, Alastair F. Donaldson, Ganesh Gopalakrishnan, Jeroen Ketema, Daniel Poetzl, Tyler Sorensen, John Wickerson

View

Download (PDF)

Tags: ATI, ATI Radeon HD 6570, ATI Radeon HD 7970, Computer science, Memory, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 540 M, nVidia GeForce GTX 660, nVidia GeForce GTX 750, nVidia GeForce GTX Titan, OpenCL, Performance, PTX, Tesla C2075

January 21, 2015 by hgpu

Hybrid Multicore Algorithms for Some Semi-Numerical Applications and Graphs

Dip Sankar Banerjee

View

Download (PDF)

Tags: Algorithms, Cell processor, Computer science, CUDA, Distributed computing, List ranking, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 580, OpenCL, Sorting, Thesis

January 19, 2015 by hgpu

Parallel Implementation of the Finite Element Method on Graphics Processors for the Solution of Incompressible Flows

Mahmut Murat Gocmen

View

Download (PDF)

Source codes

Tags: Algorithms, CUBLAS, CUDA, FEM, Finite element method, Fluid dynamics, Lattice Boltzmann model, nVidia, nVidia GeForce GTX 280, Package, Tesla C2075, Thesis

January 16, 2015 by hgpu

Query Optimization in Heterogeneous CPU/GPU Environment for Time Series Databases

Piotr Przymus

View

Download (PDF)

Tags: Algorithms, Compression, Computer science, CUDA, Data mining, Databases, Heterogeneous systems, nVidia, nVidia GeForce GTX 280, Tesla C2070, Tesla M2070, Thesis

October 24, 2014 by hgpu

Optimization Techniques for Mapping Algorithms and Applications onto CUDA GPU Platforms and CPU-GPU Heterogeneous Platforms

Jing Wu

View

Download (PDF)

Tags: Computer science, CUDA, FFT, Heterogeneous systems, Laplace and Poisson equation, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 480, Poisson equation, Tesla C1060, Tesla C2050, Thesis

October 22, 2014 by hgpu

FDTD on Distributed Heterogeneous Multi-GPU Systems

Eirik Myklebost

View

Download (PDF)

Tags: Algorithms, Benchmarking, Cluster computing, CUDA, Electrodynamics, FDTD, Finite-difference time-domain, Heterogeneous systems, MPI, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 470, nVidia GeForce GTX 760, Physics, Tesla K20, Thesis, Ultrasound

October 10, 2014 by hgpu

Fast Estimation of Gaussian Mixture Model Parameters on GPU using CUDA

Lukas Machlica, Jan Vanek, Zbynek Zajıc

View

Download (PDF)

Source codes

Tags: Computer science, CUDA, Machine learning, nVidia, nVidia GeForce GTX 280, Package, Statistics and Probability

October 2, 2014 by Vanekyj

A Comprehensive Survey on Various Evolutionary Algorithms on GPU

Satvir Singh, Jaspreet Kaur, Rashmi Sharan Sinha

View

Download (PDF)

Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 285, nVidia GeForce GTX 480, nVidia GeForce GTX 580, Particle swarm optimization, Tesla C1060, Tesla C2050

August 23, 2014 by hgpu

Design and Evaluation of Scalable Concurrent Queues for Many-Core Architectures

Thomas R. W. Scogland, Wu-chun Feng

View

Download (PDF)

Tags: ATI, ATI Radeon HD 7970, Computer science, Intel Xeon Phi, nVidia, nVidia GeForce GTX 280, OpenCL, Performance, Tesla K20

August 15, 2014 by hgpu

Benchmarking the Memory Hierarchy of Modern GPUs

Xinxin Mei, Kaiyong Zhao, Chengjian Liu, Xiaowen Chu

View

Download (PDF)

Source codes

Tags: Benchmarking, Computer science, CUDA, Memory, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 560 Ti, nVidia GeForce GTX 780, Package, Performance

July 14, 2014 by hgpu

Hybrid Particle Lattice Boltzmann Shallow Water for interactive fluid simulations

Jesus Ojeda, Antonio Susin

View

Download (PDF)

Tags: CUDA, Fluid dynamics, Fluid simulation, Lattice Boltzmann model, nVidia, nVidia GeForce GTX 280

July 11, 2014 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

* * *

high performance computing on graphics processing units: hgpu.org

Multiple String Matching on a GPU using CUDAs

GPU concurrency: Weak behaviours and programming assumptions

Parallel Implementation of the Finite Element Method on Graphics Processors for the Solution of Incompressible Flows

Query Optimization in Heterogeneous CPU/GPU Environment for Time Series Databases

Optimization Techniques for Mapping Algorithms and Applications onto CUDA GPU Platforms and CPU-GPU Heterogeneous Platforms

FDTD on Distributed Heterogeneous Multi-GPU Systems

Fast Estimation of Gaussian Mixture Model Parameters on GPU using CUDA

A Comprehensive Survey on Various Evolutionary Algorithms on GPU

Design and Evaluation of Scalable Concurrent Queues for Many-Core Architectures

Benchmarking the Memory Hierarchy of Modern GPUs

Hybrid Particle Lattice Boltzmann Shallow Water for interactive fluid simulations

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

Most viewed papers (last 30 days)