nVidia GeForce GTX 480 | Page 10

hgpu.org » nVidia GeForce GTX 480

Concurrent learning of a Probabilistic Graphical Model on the GPU

M. Matuszak

View

Download (PDF)

Tags: Bayesian, CUDA, nVidia, nVidia GeForce GTX 480, Path problems

March 21, 2014 by hgpu

An optimized algorithm for discrete element system analysis using CUDA

Zhaosong Ma, Chun Feng, Tianping Liu, Shihai Li

View

Download (PDF)

Tags: Algorithms, Computer science, CUDA, Finite element method, nVidia, nVidia GeForce GTX 285, nVidia GeForce GTX 460, nVidia GeForce GTX 480, nVidia GeForce GTX 580, Tesla C2070

March 17, 2014 by hgpu

Simulation and modelling of gravitational microlensing events using graphical processing units

Cho Hong Ling

View

Download (PDF)

Tags: Astrophysics, CUDA, Gravitation, nVidia, nVidia GeForce GTX 470, nVidia GeForce GTX 480, Thesis

March 15, 2014 by hgpu

The Flocking Based and GPU Accelerated Internet Traffic Classification

Zhiguang Xu

View

Download (PDF)

Tags: Computer science, CUDA, Network communications, nVidia, nVidia GeForce GTX 480, Tesla C2070

March 13, 2014 by hgpu

Performance Tradeoff Spectrum of Integer and Floating Point Applications Kernels on Various GPUs

M.G.B. Johnson, D. P. Playne, K.A. Hawick

View

Download (PDF)

Tags: Benchmarking, Computer science, CUDA, nVidia, nVidia GeForce GTX 260, nVidia GeForce GTX 480, nVidia GeForce GTX 580, nVidia GeForce GTX 590, nVidia GeForce GTX 660 M, nVidia GeForce GTX 680, Performance, Tesla M2050, Tesla M2070, Tesla M2075, Tesla M2090

March 6, 2014 by hgpu

QuickProbs – A Fast Multiple Sequence Alignment Algorithm Designed for Graphics Processors

Adam Gudys, Sebastian Deorowicz

View

Download (PDF)

Source codes

Tags: ATI, ATI Radeon HD 7970, Bioinformatics, Biology, nVidia, nVidia GeForce GTX 480, nVidia GeForce GTX 580, nVidia GeForce GTX 680, OpenCL, Package, Sequence alignment

March 4, 2014 by hgpu

Increasing programmability of an embedded domain specific language for GPGPU kernels using static analysis

Niklas Ulvinge

View

Download (PDF)

Tags: Code generation, Computer science, CUDA, nVidia, nVidia GeForce GTX 480, Thesis

March 4, 2014 by hgpu

Performance Optimization of Clustering On GPU

Vijal D. Patel, Sumitra Menaria

View

Download (PDF)

Tags: Algorithms, Clustering, Computer science, CUDA, Hierarchical clustering, nVidia, nVidia GeForce GTX 480, Tesla C2070

March 4, 2014 by hgpu

Efficient pseudo-random number generation for monte-carlo simulations using graphic processors

Siddhant Mohanty, A K Mohanty, F Carminati

View

Download (PDF)

Tags: Algorithms, Computer science, CUDA, Monte Carlo simulation, nVidia, nVidia GeForce GTX 480, OpenCL, Pseudo-random number generators

February 17, 2014 by hgpu

GPGPUs: How to Combine High Computational Power with High Reliability

L. Bautista Gomez, F. Cappello, L. Carro, N. DeBardeleben, B. Fang, S. Gurumurthi, S. Keckler, K. Pattabiraman, P. Rech, M. Sonza Reorda

View

Download (PDF)

Tags: Computer science, CUDA, Fault tolerance, nVidia, nVidia GeForce GTX 480, Tesla C2050

February 15, 2014 by hgpu

GPU-based high-performance computing for radiation therapy

Xun Jia, Peter Ziegenhein, Steve B Jiang

View

Download (PDF)

Tags: CUDA, Medicine, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 295, nVidia GeForce GTX 480, nVidia GeForce GTX 570, nVidia GeForce GTX 580, nVidia GeForce GTX 590, Physics, Radiotherapy, Review, Tesla C1060, Tesla C2050, Tesla C2070

February 9, 2014 by hgpu

State-Based Gauss-Seidel Framework for Real-time 2D Ultrasound Image Sequence Denoising on GPUs

Banpot Dolwithayakul, Chantana Chantrapornchai, Noppadol Chumchob

View

Download (PDF)

Tags: CUDA, Image processing, nVidia, nVidia GeForce GTX 480, OpenMP, Ultrasound

February 8, 2014 by hgpu

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

SimSYCL: A SYCL Implementation Targeting Development, Debugging, Simulation and Conformance

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

gpu_tracker: Python package for tracking and profiling GPU utilization in both desktop and high-performance computing environments

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

94% on CIFAR-10 in 3.29 Seconds on a Single GPU

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

LOOPer: A Learned Automatic Code Optimizer For Polyhedral Compilers

OpenMC Monte Carlo Code

Performance Portable Monte Carlo Particle Transport on Intel, NVIDIA, and AMD GPUs

Polygeist: C/C++ frontend for MLIR

Retargeting and Respecializing GPU Workloads for Performance Portability

Parallel Gaussian process with kernel approximation in CUDA

See all packages

* * *

high performance computing on graphics processing units: hgpu.org

Concurrent learning of a Probabilistic Graphical Model on the GPU

An optimized algorithm for discrete element system analysis using CUDA

Simulation and modelling of gravitational microlensing events using graphical processing units

The Flocking Based and GPU Accelerated Internet Traffic Classification

Performance Tradeoff Spectrum of Integer and Floating Point Applications Kernels on Various GPUs

QuickProbs – A Fast Multiple Sequence Alignment Algorithm Designed for Graphics Processors

Increasing programmability of an embedded domain specific language for GPGPU kernels using static analysis

Performance Optimization of Clustering On GPU

Efficient pseudo-random number generation for monte-carlo simulations using graphic processors

GPGPUs: How to Combine High Computational Power with High Reliability

GPU-based high-performance computing for radiation therapy

State-Based Gauss-Seidel Framework for Real-time 2D Ultrasound Image Sequence Denoising on GPUs

Recent source codes

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

GPU plugin for PySCF

QArray

Celerity: High-level C++ for Accelerator Clusters

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

OpenMC Monte Carlo Code

Polygeist: C/C++ frontend for MLIR

Parallel Gaussian process with kernel approximation in CUDA

Most viewed papers (last 30 days)