high performance computing on graphics processing units: hgpu.org

hgpu.org » nVidia GeForce GTX 690

Implementation of Filtering Beamforming Algorithms for Sonar Devices Using GPU

Shahrokh Kamali

View

Download (PDF)

Tags: CUDA, Filtering, nVidia, nVidia GeForce GTX 690, Signal processing, Thesis

July 24, 2013 by hgpu

Using sparse optical flow for multiple Kinect applications

Kai Berger, Yannic Schroeder, Stefan Guthe, Marc Aurel Kastner

View

Download (PDF)

Tags: Computer science, Computer vision, CUDA, nVidia, nVidia GeForce GTX 690, Optical flow

June 4, 2013 by hgpu

SW# – GPU enabled exact alignments on genome scale

Matija Korpar, Mile Sikic

View

Download (PDF)

Source codes

Tags: Bioinformatics, Biology, Computer science, CUDA, nVidia, nVidia GeForce GTX 560, nVidia GeForce GTX 570, nVidia GeForce GTX 690, Package, Sequence alignment, Smith-Waterman algorithm

April 23, 2013 by hgpu

CUDASW++ 3.0: accelerating Smith-Waterman protein database search by coupling CPU and GPU SIMD instructions

Yongchao Liu, Adrianto Wirawan, Bertil Schmidt

View

Download (PDF)

Source codes

Tags: Bioinformatics, Biology, CUDA, nVidia, nVidia GeForce GTX 680, nVidia GeForce GTX 690, Package, PTX, Sequence alignment, Smith-Waterman algorithm

April 10, 2013 by hgpu

Exploring the Feasibility of Fully Homomorphic Encryption

Wei Wang, Yin Hu, Lianmu Chen, Xinming Huang, Berk Sunar

View

Download (PDF)

Tags: Algorithms, Computer science, CUDA, FFT, nVidia, nVidia GeForce GTX 690, Security

January 12, 2013 by hgpu

Molecular dynamics for long-range interacting systems on Graphic Processing Units

Tarcisio M. Rocha Filho

View

Download (PDF)

Tags: Algorithms, Computational Physics, CUDA, Molecular dynamics, nVidia, nVidia GeForce GTX 690, Physics, Statistical Mechanics

December 4, 2012 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

Implementation of Filtering Beamforming Algorithms for Sonar Devices Using GPU

Using sparse optical flow for multiple Kinect applications

SW# – GPU enabled exact alignments on genome scale

CUDASW++ 3.0: accelerating Smith-Waterman protein database search by coupling CPU and GPU SIMD instructions

Exploring the Feasibility of Fully Homomorphic Encryption

Molecular dynamics for long-range interacting systems on Graphic Processing Units

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)