. The second idea is to compute the sum of products for multiple length arithmetic operation using inline assembler. The experimental results show that our GPU implementation on NVIDIA GeForce GTX TITAN attains a speed-up factor of 53.2 for 1024-bit RSA encryption and 56.4 for 2048-bit RSA encryption over

Abstract This paper presents efficient implementa-tion of RLS-based adaptive filters with a large number of taps on nVIDIA GeForce graphics processing unit (GPU) and CUDA software development environment. Modification of the order and the combination of calcu-lations reduces the number of accesses

Abstract. NVIDIA have released a new platform (CUDA) for general purpose computing on their graphical processing units (GPU). This pa-per evaluates use of this platform for statistical machine learning appli-cations. The transfer rates to and from the GPU are measured, as is the performance

In this paper we describe the design, programming interface, and implementation of a very efficient user-programmable vertex engine. The vertex engine of NVIDIA’s GeForce3 GPU evolved from a highly tuned fixed-function pipeline requiring considerable knowledge to program. Programs operate only on a

This paper presents implementations of an FIR adaptive fil-ter with a large number of taps on nVIDIA GeForce graph-ics processing unit (GPU) and CUDA software development environment. In order to overcome a long access latency for slow off-chip memory access, reduction of memory ac-cesses by re

Kepler is the newest GPU architecture from NVIDIA, and the GTX 680 is the first commercially available graphics card based on that architecture. Matrix multi-plication is a canonical computational kernel, and often the main target of initial optimization efforts for a new chip. This article

this document is to enable OpenGL developers to implement this technique with NVIDIA OpenGL extensions and GeForce3 hardware. Since shadow mapping is integral to the technique a very basic introduction is provided, but the interested reader is encouraged to explore the referenced material for more

This document is protected by copyright and contains information proprietary to NVIDIA Corporation. This document is an abridged collection of OpenGL extension specifications limited to those extensions for new OpenGL functionality introduced by the GeForce 8 Series (G8x) architecture. See

-of-square-differences (SSD) dissimilarity measure between correlation windows. To achieve good results close to depth discontinuities as well as on low texture areas a multiresolution approach is used. The approach efficiently combines SSD measurements for windows of different sizes. Our implementation running on an NVIDIA

programmable GPU (e.g. NVIDIA’s GeForce FX 5900) and applied to databases consisting of up to a million records. We have compared their performance with an optimized implementation of CPU-based algorithms. Our experiments indicate that the graphics processor available on commodity computer systems