| Course Name | Parallel and Distributed Computing |
| Course Code | 15CSE360 |
| Program | B. Tech. in Computer Science and Engineering |
| Year Taught | 2019 |
Introduction: The Reality of High Performance Computing – Modern Algorithms – Compilers – Scientific Algorithms – History – State-of-Art and Perspective – Things that are not Traditional Supercomputers. Parallel Computing – PDC models working mechanism – scalability of PDC architectures – applications, performance metrics and Amdahl’s Law.
Models and Algorithms – PRAM algorithms, Process-level parallelism, data-level parallelism, Problem partitioning, divide-and-conquer, Distributed algorithms – Algorithm design techniques – filters, client / server, heartbeat, probe / echo, token passing, replicated servers Communication – Interconnection network design, Topological and parametric models of interconnection networks; routing mechanisms; flow control mechanisms, communication protocols, Communication primitives – Point-to-point communication primitives; group communication patterns; broadcast in distributed systems, CSP, MPI; Synchronization – Locks, monitors, barriers; deadlock; hardware primitives and implementation issues; clock synchronization, distributed mutual exclusion; distribute deadlock detection.
Computation: Threads – Creation, coordination, termination; futures. Shared Memory – Models of memory consistency; implementation of consistency protocols; transactions: serializability, concurrency – control, commit protocols; Linda. Scheduling and Load Balancing: Load distribution algorithms; task migration; coscheduling; affinity scheduling; self-scheduling in loops.
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