DISTRIBUTED, PARALLEL AND CLOUD COMPUTING (2 Units C: LH 15; PH 45)
Course Contents:
Analysis and Design of Parallel and Distributed Algorithms; Languages/Operating Systems for parallel processing; GPGPU computing; Architecture of parallel/distributed systems, Tools for parallel computing, Parallel (distributed) database systems, Networking aspects of parallel/distributed computing, Parallel/distributed scientific computing Applications; High performance computing Applications in molecular sciences; Multimedia applications for parallel/distributed systems; Grid networks, services and applications; Distributed File Systems; Hyper Scale/Hyper Converged Distributed Storage Design, Storage I/O Protocols; Cloud as a Service, Cloud Infrastructure, Management and operations, Performance, Scalability, Reliability, Virtualization, loud Provisioning Orchestration, Architecture support, Development Tools, Platforms and Applications, Legal aspects and Service Level Agreement, Mobile computing advances in the Cloud, Performance optimization
Lab Work: Distributed Computing: Set up a Hadoop cluster and process large datasets. Write a MapReduce program for word count.
Cloud Deployment: Deploy a web application on AWS or Azure .Set up an EC2 instance, install the required stack, and host an app.
- Teacher: LMS Admin