| Pub. Date | : Jul, 2019 |
|---|---|
| Product Name | : The IUP Journal of Computer Sciences |
| Product Type | : Article |
| Product Code | : IJCS41907 |
| Author Name | : Michael Gallagher, Erick Rengifo and Rossen Trendafilov |
| Availability | : YES |
| Subject/Domain | : Management |
| Download Format | : PDF Format |
| No. of Pages | : 16 |
Cloud-based computing has tremendous potential for academia in general and researchers in particular. The ability to store, read and manipulate large dataset is increasingly important to be on the cutting-edge of research. While most researchers have extensive programming skills, they generally are not computer scientists. A number of cloud-based, virtual work spaces have been developed which can bring enormous computing advantages over any desktop or laptop. However, the instructions to get up and running in the cloud are often overwhelming, and require a significant investment of time. There is an initial steep learning curve associated with developing a high performance computing environment that several times becomes an obstacle, preventing many from benefitting the most from using the cloud. This paper seeks to demystify the process and get the reader up and running very quickly. Once this initial process is over and the reader is proficient on these issues, performing computational chores that would take days on a desktop can be done in minutes. We next show the way the readers can implement their research using two well-known computer programs, MATLAB and R. Finally, Part IV concludes with a description on how to use MATLAB in the cloud.
MathWorks has developed a functionality to run computationally intensive jobs in parallel on Elastic Compute Cloud (EC2) directly from the users’ desktop or workstation. As usual with MATLAB, researchers must have a MATLAB license configured as a “Standalone Named User”, with parallel computing toolbox installed. In addition, researchers must have MATLAB Distributed Computing Server (MDCS) license. An MDCS license may take one of two forms, either an “on demand” license, or a “perpetual license”. Large institutions which anticipate significant continual computational usage will opt for a perpetual license, which is priced accordingly.
Cloud computing, Amazon Web Services (AWS), S3, Elastic Compute Cloud (EC2), Virtual computing instance, Linux R, MATLAB