Search Results - parallel computing ((matching algorithm) OR (new algorithm))*
Search alternatives:
- new algorithm »
- matching »
-
1
Multithreaded Scalable Matching Algorithm For Intrusion Detection Systems
Published 2010“…Hence, this thesis defines a new algorithm called the Distributed Packet Header Matching algorithm (DPHM), and a New Network Intrusion Detection Systems (NNIDS) platform using hybrid technology in order to increase the overall performance of SNORT-NIDS.…”
Get full text
Get full text
Thesis -
2
Simulated kalman filter (SKF) based image template matching for distance measurement by using stereo vision system
Published 2018“…By implementing optimization algorithm in image template matching, it is expected that the computation time can be reduced. …”
Get full text
Get full text
Thesis -
3
Effect Of The Addition Of Wastepaper To Concrete Mix
Published 2009“…Hence, this thesis defines a new algorithm called the Distributed Packet Header Matching algorithm (DPHM), and a New Network Intrusion Detection Systems (NNIDS) platform using hybrid technology in order to increase the overall performance of SNORT-NIDS.…”
Get full text
Get full text
Thesis -
4
-
5
Resource Minimization in a Real-time Depth-map Processing System on FPGA
Published 2011“…Depth-map algorithm allows camera system to estimate depth. It is a computational intensive algorithm, but can be implemented with high speed on hardware due to the parallelism property. …”
Get full text
Get full text
Conference or Workshop Item -
6
GPU-based odd and even hybrid string matching algorithm
Published 2016“…String matching is considered as one of the fundamental problems in computer science.Many computer applications provide the string matching utility for their users, and how fast one or more occurrences of a given pattern can be found in a text plays a prominent role in their user satisfaction.Although numerous algorithms and methods are available to solve the string matching problem, the remarkable increase in the amount of data which is produced and stored by modern computational devices demands researchers to find much more efficient ways for dealing with this issue.In this research, the Odd and Even (OE) hybrid string matching algorithm is redesigned to be executed on the Graphics Processing Unit (GPU), which can be utilized to reduce the burden of compute-intensive operations from the Central Processing Unit (CPU).In fact, capabilities of the GPU as a massively parallel processor are employed to enhance the performance of the existing hybrid string matching algorithms.Different types of data are used to evaluate the impact of parallelization and implementation of both algorithms on the GPU. …”
Get full text
Get full text
Get full text
Conference or Workshop Item -
7
An Efficient Parallel Quarter-sweep Point Iterative Algorithm for Solving Poisson Equation on SMP Parallel Computer
Published 2000“…In this paper, the parallel implementation of the new algorithm with the chessboard (CB) strategy on Symmetry Multi Processors (SMP) parallel computer was presented. …”
Get full text
Get full text
Article -
8
Speeding up index construction with GPU for DNA data sequences
Published 2011Get full text
Get full text
Get full text
Conference or Workshop Item -
9
Adaptive resource allocation for reliable performance in heterogeneous distributed systems.
Published 2013Get full text
Book Section -
10
-
11
DC-based PV-powered home energy system
Published 2017“…A controller based on an algorithm of one time maximum power point (MPP) is proposed to mitigate those losses. …”
Get full text
Get full text
Thesis -
12
Parallel block methods for solving higher order ordinary differential equations directly
Published 1999“…A new parallel algorithm for solving systems of ODEs using variable step size and order is also developed. …”
Get full text
Get full text
Thesis -
13
Parallel algorithms for numerical simulations of EHD ion-drag micropump on distributed parallel computing systems
Published 2014“…To implement the parallel algorithms a distributed parallel computing laboratory using easily available low cost computers is setup. …”
Get full text
Get full text
Thesis -
14
-
15
Tile-Level Parallelism For H.264/Avc Codec Using Parallel Domain Decomposition Algorithm On Shared Memory Architecture
Published 2015“…By assuming that parallel architectures are forming the vast majority of computing nodes in digital devises, proposing inherently-parallel algorithms are no more an overstatement. …”
Get full text
Get full text
Thesis -
16
The division free parallel algorithm for finding determinant
Published 2013“…A cross multiplication method for determinant was generalized for any size of square matrices using a new permutation strategy.The permutation is generated based on starter sets.However, via permutation, the time execution of sequential algorithm became longer.Thus, in order to reduce the computation time, a parallel strategy was developed which is suited for master and slave paradigm of the high performance computer.A parallel algorithm is integrated with message passing interface.The numerical results showed that the parallel methods computed the determinants faster than the sequential counterparts particularly when the tasks were equally allocated.…”
Get full text
Get full text
Get full text
Article -
17
-
18
A genetic similarity algorithm for searching the Gene Ontology terms and annotating anonymous protein sequences
Published 2008“…The genetic similarity algorithm combines semantic similarity measure algorithm with parallel genetic algorithm. …”
Get full text
Get full text
Get full text
Article -
19
Parallel batch self-organizing map on graphics processing unit using CUDA
Published 2018“…The most computationally expensive parts of its training algorithm (such as steps to compute distance between each data vector and neuron, and determining the Best Matching Unit based on minimum distance) are identified and mapped on GPU to be processed in parallel. …”
Get full text
Get full text
Article -
20
Parallel batch self-organizing map on graphics processing unit using CUDA
Published 2018“…The most computationally expensive parts of its training algorithm (such as steps to compute distance between each data vector and neuron, and determining the Best Matching Unit based on minimum distance) are identified and mapped on GPU to be processed in parallel. …”
Get full text
Get full text
Article
