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Home / Syllabus / B.E. (Artificial Intelligence and Data Science) / TY BE AI and DS / Semester 6 / High Performance Computing

B.E. (Artificial Intelligence and Data Science) High Performance Computing Syllabus - Mumbai University 2026

This is the TY BE AI and DS syllabus under CBCS REV-2019 'C' Scheme, in force from the academic year 2022-23. The University has published no NEP 2020 syllabus for Semesters V to VIII of any engineering branch, so this is the scheme you are examined on — exam form 1T01815 and 1T01816. The first and second years of the degree are on NEP 2020.

High Performance Computing.pdf
Semester 6 · TY BE AI and DS · 3 credits · CBCS REV-2019 'C' Scheme

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Syllabus for High Performance Computing

Semester 6 · TY BE AI and DS · 3 credits · CBCS REV-2019 'C' Scheme

Module 0: Prerequisite 02 hours

  • Computer Organization, C Programming, Data structures and Algorithm Analysis.

Module I: Introduction 05 hours

  • Introduction to Parallel Computing: Motivating Parallelism, Scope of Parallel Computing, Levels of parallelism (instruction, transaction, task, thread, memory, function), Models (SIMD, MIMD, SIMT, SPMD, Dataflow Models, Demand-driven Computation). Self-learning Topics: Parallel Architectures: Interconnection network, Processor Array, Multiprocessor.

Module II: Parallel Programming Platforms 04 hours

  • Parallel Programming Platforms: Implicit Parallelism: Dichotomy of Parallel Computing Platforms, Physical Organization of Parallel Platforms, Communication Costs in Parallel Machines. Self-learning Topics: Trends in Microprocessor & Architectures, Limitations of Memory System Performance.

Module III: Parallel Algorithm And Concurrency 09 hours

  • Principles of Parallel Algorithm Design: Preliminaries, Decomposition Techniques, Characteristics of Tasks and Interactions, Mapping Techniques for Load Balancing, Basic Communication operations: Broadcast and Reduction Communication types. Self-learning Topics: Parallel Algorithm Models

Module IV: Performance Measures for HPC 05 hours

  • Performance Measures : Speedup, execution time, efficiency, cost, scalability, Effect of granularity on performance, Scalability of Parallel Systems, Amdahl‘s Law, Gustavson‘s Law. Self-learning Topics: Performance Bottlenecks.

Module V: Programming Paradigms for HPC 09 hours

  • Programming Using the Message-Passing Paradigm : Principles of Message Passing Programming, The Building Blocks: Send and Receive Operations, MPI: the Message Passing Interface, Topology and Embedding. Parallel Algorithms and Applications : One-Dimensional Matrix-Vector Multiplication, Graph Algorithms, Sample Sort, Two-Dimensional MatrixVector Multiplication. Self-learning Topics: Introduction to OpenMP.

Module VI: General Purpose Graphics Processing Unit(GPGPU) Architecture and Programming 05 hours

  • OpenCL Device Architectures, Introduction to OpenCL Programming. Self-learning Topics: Introduction to CUDA architecture, and Introduction to CUDA Programming.

Text Books

  • 1 AnanthGrama, Anshul Gupta, George Karypis, Vipin Kumar , ―Introduction to Parallel Computing‖, Pearson Education, Second Edition, 2007.
  • 2 Kai Hwang, Naresh Jotwani, ―Advanced Computer Architecture: Parallelism, Scalability, Programmability‖, McGraw Hill, Second Edition, 2010.
  • 3 Edward Kandrot and Jason Sanders, ―CUDA by Example – An Introduction to General Purpose GPU Programming‖, Addison-Wesley Professional ©, 2010.
  • 4 Georg Hager, Gerhard Wellein, ―Introduction to High Performance Computing for Scientists and Engineers", Chapman & Hall / CRC Computational Science series, 2011.
  • 5 Benedict Gaster, Lee Howes, David Kaeli, Perhaad Mistry, Dana Schaa , ―Heterogeneous Computing with OpenCL‖ , 2nd Edition, Elsevier, 2012.

Reference Books

  • 1 Michael J. Quinn, ―Parallel Programming in C with MPI and OpenMP‖, McGraw-Hill International Editions, Computer Science Series, 2008.
  • 2 Kai Hwang, Zhiwei Xu, ―Scalable Parallel Computing: Technology, Architecture, Programming‖, McGraw Hill, 1998.
  • 3 Laurence T. Yang, MinyiGuo, ―High- Performance Computing: Paradigm and Infrastructure‖ Wiley, 2006.
  • 4 Fayez Gebali, ―Algorithms and Parallel Computing‖, John Wiley & Sons, Inc., 2011.

Online References

  • 1 https://onlinecourses.nptel.ac.in/noc21_cs46/preview
  • 2 https://onlinecourses.nptel.ac.in/noc22_cs21/preview

Reproduced from the University of Mumbai syllabus for B.E. (Artificial Intelligence and Data Science), item 6.42 (R), under CBCS REV-2019 'C' Scheme, in force from the academic year 2022-23. Wording, module numbering and hours are as printed in that syllabus.

The complete syllabus

This subject is cut from the University circular for its year. Open a document here if you want the whole thing rather than a single subject.

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