The Linux Enterprise Cluster explains how to take a number of inexpensive computers with limited resources, place them on a normal computer network, and install free software so that the computers act together like one powerful server. This makes it possible to build a very inexpensive and reliable ...
How the K-mean Cluster work
Step 1. Begin with a decision the value of k = number of clusters
Step 2. Put any initial partition that classifies the data into k clusters. You may assign the training samples randomly, or systematically as the following:
Take the first k training sample as single-e ...
KMEANS Trains a k means cluster model.CENTRES = KMEANS(CENTRES, DATA, OPTIONS) uses the batch K-means
algorithm to set the centres of a cluster model. The matrix DATA
represents the data which is being clustered, with each row
corresponding to a vector. The sum of squares error function is used.
The ...
pMatlab is a toolsbox from MIT for running matlab in parallel style on a multi-core PC or a cluster environment. These two documents summary the usage of pMatlab and running time measurements on three simple Monte Carlo simulation codes.
MS-Clustering is designed to rapidly cluster large MS/MS datasets. The program merges similar spectra (having similar m/z values ?within a given tolerance), and creates a single consensus spectrum as a representative. The input formats accepted are: dta, mgf, mzXML. The output format is mgf.
前面我们通过Veritas Cluster Server for DB2双机-入门一文已经向大家介绍了DB2双机的基本原理和配置方法，本文将接续上文，继续介绍DB2的高级需求－大规模并行处理（Massively Parallel Processing, MPP）－环境下，用户如何利用VCS配置双机互备环境。 ...
