Course

Introduction – parallelism and goals, parallel computing models – RAM, PRAM , CTA. Reasoning about Performance – Introduction -Basic Concepts – Performance Loss – Parallel Structure – Measuring Performance. Shared memory architecture.

Parallel Programming: Task and Data Parallelism with examples –Comparison Programming with Threads – POSIX Threads- Thread Creation and Destruction. Mutual Exclusion- Synchronization – Safety and Performance Issues – Reduction – threads Inter process communication – internet protocols – multicast communication – MPI. Remote invocation: Remote procedure call – remote method invocation –

System models : physical models, architecture models, operating system support. Distributed file systems – introduction- time and global states – synchronization of physical clocks – coordination and agreements: Mutual exclusion, election, consensus.

Course Outcomes:

CO1: Understand the basics of parallel computing models.

CO2: Gain knowledge about task and data parallelism.

CO3: Understand the concepts of inter process communication and internet protocols.

CO4: To gain knowledge the system models.

CO-PO Mapping:

Text Books/ ReferencesBooks:

1. George Coulouris , Jean Dollimore , Tim Kindberg , Gordon Blair: Distributed Aystems :

Concepts and Design , Fifth Edition , Addison Wiley, 2012.

2. Calvin Lin ,Larry Snyder : Principles of Parallel Programming, Pearson, 2009
3. Bertil Schmidt, Jorge Gonzalez-Dominguez, Christian Hundt , Moritz Schlarb, Parallel Programming: Concepts and Practice First Edition, Morgan Kaufmann, 2017.

4. Ajay D. Kshemkalyani, Mukesh Singhal , Distributed Computing: Principles, Algorithms, and Systems, Cambridge University Press, First edition, 2008.