In this 3-parts series of articles, David Pallmann explains how to perform grid computations on the Azure cloud computing platform. In Part 1 he presents a design pattern for using Azure for grid computing, while in Part 2 and 3 he is going to give a concrete code example.
Read: Grid Computing on the Azure Cloud Computing Platform, Part 1
The author starts by showing the difference between grid computing and cloud computing, and continues by presenting the benefits of using a cloud platform for performing grid computations. After introducing Azure, he describes the following design pattern:
The author explains why part of the infrastructure should go in the cloud while an important part should remain in the enterprise. The two major software actors of this pattern are: Grid Manager (Loader, Console, Aggregator) and Grid Worker. The data actors are: Task Queue, Results Queue, Tracking Table, and the Enterprise Data.