Heterogeneous Computing detailed syllabus for Information Technology (IT) for 2019 regulation curriculum has been taken from the Anna Universities official website and presented for the IT students. For course code, course name, number of credits for a course and other scheme related information, do visit full semester subjects post given below.
For Information Technology 5th Sem scheme and its subjects, do visit IT 5th Sem 2019 regulation scheme. For Professional Elective-I scheme and its subjects refer to IT Professional Elective-I syllabus scheme. The detailed syllabus of heterogeneous computing is as follows.
Course Objective:
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Unit I
Parallel Computing Basics
Importance of Parallelism – Processes, Tasks and Threads – Modifications to von-Neumann model – ILP – TLP – Parallel Hardware – Flynns Classification – Shared Memory and Distributed Memory Architectures – Cache Coherence – Parallel Software – Performance -Speedup and Scalability – Massive Parallelism – GPUs – GPGPUs.
Suggested Activities:
- Identify parallelism in day-to-day activities.
- Study the configuration of the multi-core processors and GPUs used in laptops, PCs and smart phones.
- Review the configuration of top 500 super computers over the last 10 years.
- Problems on cache coherence in class.
- Flipped classroom on GPGPUs.
Suggested Evaluation Methods:
- Pair-wise/group discussion on the studies conducted.
- Assignment on various topics of the unit.
- Quiz on speedup and scalability calculation.
- Quiz on GPGPUs.
Unit II
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Unit III
Programming Gpus
GPU Architectures – Data Parallelism – CUDA Basics – CUDA Program Structure -Threads, Blocks, Grids – Memory Handling.
Suggested Activities:
- Write simple CUDA programs to understand threads, blocks and grids.
- Experiment with different sizes for threads, blocks and grids.
- Write CUDA programs for memory-intensive programs and experiment with different memory options.
- Mini project: Devise a solution for the problem identified in the earlier unit using CPU and GPU.
Suggested Evaluation Methods:
- Demonstration of the CUDA programs.
- Plot graphs of execution time versus various parameters.
- Mini project: Check design of the solution.
Unit IV
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Unit V
Other Gpu Programming Platforms
Introduction to OpenCL – OpenACC – C++AMP – Thrust – Programming Heterogeneous Clusters – CUDA and MPI.
Suggested Activities:
- Write and execute simple OpenCL programs.
- Study the OpenACC programming model and identify the reduction in programming complexity.
- Identify and compare the different available parallel programming accelerator tools.
- Mini project: Compare OpenMP and CUDA versions of code.
Suggested Evaluation Methods:
- Demonstration of programs.
- Demonstration of use of tools.
- Mini project: Check performance analysis graph.
Course Outcome:
For the complete syllabus, results, class timetable, and many other features kindly download the iStudy App
It is a lightweight, easy to use, no images, and no pdfs platform to make students’s lives easier..
Text Books:
- Peter Pacheco, “Introduction to Parallel Programming”, Morgan Kauffman, 2011.
- David B. Kirk, Wen-mei W. Hwu, “Programming Massively Parallel Processors”, Third Edition, Morgan Kauffman, 2016.
References:
- Shane Cook, “CUDA Programming – A Developers Guide To Parallel Computing with GPUs”, Morgan Kauffman, 2013.
- B.R. Gaster, L. Howes, D.R. Kaeli, P. Mistry, D. Schaa, ” Heterogeneous Computing with OpenCL 2.0″, Morgan Kauffman, 2015.
For detailed syllabus of all the other subjects of Information Technology 5th Sem, visit IT 5th Sem subject syllabuses for 2019 regulation.
For all Information Technology results, visit Anna University IT all semester results direct link.