Library

MEGDAM Library contains a collection of 102 books encompass the following areas: Natural Language Processing, Cloud Computing, Big Data, Business Intelligence, Visualization Tools, Statistics and Data Modeling, Social, Text Mining, Data Mining, Health Care, Bio Informatics, Knowledge Discovery, Security, Forensics and others. MEGDAM invites students, researchers and collaborators to browse our latest collection. Additionally approximately 250 electronic titles are also available. Pls see attached list of titles. 

Computer Lab

MEGDAM is now providing researchers, collaborators and students with a dedicated computer laboratory with six workstation connected to a dedicated server for intensive computing. All machines have MS Windows 7 installed with Office software. Systems development software as Oracle Netbeans, Microsoft Visual Studio, Expressions, Rapid Miner along with Social networking tools such as NodeXL etc are available on the workstations. Cloud computing software for Big data analytics, data modeling would be made available soon. 
Megdam Computer Lab was established for the sole purpose of assisting researchers are students working in research projects funded by MEGDAM. Establishing a Cloud server for cloud based applications with virtualization technologies from vmware would be made available in near future. We invite researchers and students to utilize our resources for the benefit of advancement of MEGDAM goals. 

MEGDAM Servers

MEGDAM Server provides PSU faculty members with easy access to Data Mining Software Tools and documentation. The server can be accessed within the university campus at 10.0.17.35 
Additionally MEGDAM manages four servers as part of the HPC Computer Lab at CCIS. 

MEGDAM Cluster

MEGDAM Cluster is part of a research project funded by KACST. The Cluster is made of 20 Raspberry Pi computers each having an ARM 7 1GHz quad core processor. All these devices a connected through five Gigabit Ethernet switches and Routers. The router connects the Cluster to PSU Network. The cluster can be accessed at 10.0.17.51.