| Course Code |
CSC320 |
| Course Title |
Parallel and distributed Computing |
| Credit Hours |
3+0 |
| Prerequisites by Course(s) and Topics |
Operating Systems |
| Assessment Instruments with Weights (homework, quizzes, midterms, final, programming assignments, lab work, etc.) |
SESSIONAL (Quizzes, Assignments, Presentations) =25 %
Midterm Exam =25 %
Final Exam = 50%
|
| Course Coordinator |
Muhammad Ali Dildar |
| URL (if any) |
NA |
| Current Catalog Description |
NA |
| Textbook (or Laboratory Manual for Laboratory Courses) |
Distributed Systems: Principles and Paradigms, A. S. Tanenbaum and M. V. Steen, Prentice Hall, 2nd Edition, 2007 |
| Reference Material |
Distributed and Cloud Computing: Clusters, Grids, Clouds, and the Future Internet, K Hwang, J Dongarra and GC. C. Fox, Elsevier, 1st Ed. |
| Course Goals |
This course is to provide a combined applied and theoretical background in Parallel and Distributed Computing to improve students’ learning outcomes.; 1. Learn about parallel and distributed computers. 2. Write portable programs for parallel or distributed architectures using Message-Passing Interface (MPI) library. 3. Analytical modeling and performance of parallel programs. 4. Analyze complex problems with shared memory programming with |
| Course Learning Outcomes (CLOs): |
| At the end of the course the students will be able to: | Domain | BT Level* |
|---|
| Learn about parallel and distributed computers. |
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| Write portable programs for parallel or distributed architectures using Message-Passing Interface (MPI) library. |
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| Analytical modelling and performance of parallel programs. |
|
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| Analyze complex problems with shared memory programming with openMP. |
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| * BT= Bloom’s Taxonomy, C=Cognitive domain, P=Psychomotor domain, A= Affective domain |
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| Topics Covered in the Course, with Number of Lectures on Each Topic (assume 15-week instruction and one-hour lectures) |
| Week | Lecture | Topics Covered |
|---|
| Week 1 |
1 |
Asynchronous Communication/Computation |
|
2 |
Synchronous Communication/Computation |
| Week 2 |
3 |
Concurrency Control |
|
4 |
Fault Tolerance |
| Week 3 |
5 |
GPU Architecture |
|
6 |
GPU Programming |
| Week 4 |
7 |
Heterogeneity |
|
8 |
Interconnection Topologies |
| Week 5 |
9 |
Load Balancing |
|
10 |
Memory Consistency Model |
| Week 6 |
11 |
Memory Hierarchies |
|
12 |
Message Passing Interface (MPI) |
| Week 7 |
13 |
MIMD/SIMD |
|
14 |
Multithreaded Programming |
| Week 8 |
1 hours |
Mid Term |
| Week 9 |
15 |
Mid term exams |
|
16 |
Mid term exams |
| Week 10 |
17 |
Parallel Algorithms |
|
18 |
Parallel Architectures |
| Week 11 |
19 |
Parallel Input and Output |
|
20 |
Performance Analysis |
| Week 12 |
21 |
Performance Tuning |
|
22 |
Power Consumption methods and saving techniques in distributed systems |
| Week 13 |
23 |
Programming Models (Data Parallel, Task Parallel) |
|
24 |
Programming Models (Process centric) |
| Week 14 |
25 |
Programming Models (Shared/Distributed memory) |
|
26 |
Scalability and Performance Studies |
| Week 15 |
27 |
Scheduling (Process scheduling schemes in distributed computing) |
|
28 |
Storage Systems for Distributed computing |
| Week 16 |
29 |
Synchronization in communication |
|
30 |
Tools (Cuda, Swift, Globus, Amazon AWS, OpenStack) |
| Week 17 |
2 hours |
Final Term |
|
| Laboratory Projects/Experiments Done in the Course |
Lab is not associated with this course. |
| Programming Assignments Done in the Course |
Implementation of parallel processing concepts using multi-threaded and Message Passing Interface (MPI) based applications. Covering both; shared memory and message passing models. |
