Through esProc Parallel Computing: Data Redundancy, we know that for cluster computation data files can be stored in separate servers, with data redundancy solution adopted. Thus the parallel program will find the appropriate node for a subtask according to where the needed files are stored. The fact is, during real wo...
2015-10-13 85 0
esProc Parallel Computing: Cluster Computing explains how to use cluster computing to process massive data or handle tasks involving a large amount of computation.
1. The problem with parallel computing
Parallel computing requires that the dfx file to be invoked be stored in all nodes, and that the data files the subta...
2015-10-09 70 0
Parallel computing allows executing a computation on big data by distributing it to nodes. If the data distributed to each node is still in large volume, it can be returned from the node with the remote cursor. We’ll now learn the usage of the remote cursor as well as its features.
1. The usage
The servers the remote c...
2015-09-11 67 0
In esProc Parallel Computing: Multithreading, we learned how to increase efficiency through executing multithreaded computation. But besides using fork in the cellset code to achieve the multithreading type of parallel processing, esProc also builds the approach of parallel processing into some functions. Let’s find ou...
2015-07-31 87 0
Cluster computing can be used in esProc for performing complicated analytic and processing tasks. A cluster system consists of multiple parallel servers running on independent computers in a network. Every single computer in this network can send a parallel computing request to the cluster.
A cluster system enhances co...
2015-07-28 92 0
Parallel computing solves a computational problem by breaking it apart into discrete subtasks and distributing them among multiple servers on which they will be implemented concurrently. Each subtask returns its own computational result to the master task for combination. Through the simultaneous use of multiple comput...
2015-02-17 193 0
Sequential computation was the simplest and most intuitive processing method for handling computational tasks. Contemporary servers and PCs, however, have gained the multi-tasking ability with multi-core CPUs. Under the circumstances, sequential computation cannot make the most use of the computational power the CPU of...
2015-02-16 54 0