PERFORMANCE OF PARALLEL AND DISTRIBUTED SYSTEMS
| Title | ΑΠΟΔΟΣΗ ΠΑΡΑΛΛΗΛΩΝ ΚΑΙ ΚΑΤΑΝΕΜΗΜΕΝΩΝ ΣΥΣΤΗΜΑΤΩΝ / PERFORMANCE OF PARALLEL AND DISTRIBUTED SYSTEMS |
| Code | NNA-08-05 |
| Faculty | Sciences |
| School | Informatics |
| Cycle / Level | 1st / Undergraduate |
| Teaching Period | Spring |
| Coordinator | Nikolaos Konofaos |
| Common | No |
| Status | Active |
| Course ID | 600014421 |
Programme of Study: PPS-Tmīma Plīroforikīs (2019-sīmera)
Registered students: 5
| Orientation | Attendance Type | Semester | Year | ECTS |
|---|---|---|---|---|
| GENIKĪ KATEUTHYNSĪ | Elective Courses | 8 | 4 | 5 |
| Academic Year | 2018 – 2019 |
| Class Period | Spring |
| Faculty Instructors |
|
| Weekly Hours | 4 |
| Class ID | 600121351
|
Course Type 2016-2020
- Scientific Area
Course Type 2011-2015
Specific Foundation / Core
Mode of Delivery
- Face to face
Digital Course Content
- e-Study Guide https://qa.auth.gr/en/class/1/600121351
- eLearning (Moodle): https://elearning.auth.gr/
Language of Instruction
- Greek (Instruction, Examination)
Prerequisites
General Prerequisites
Basic knowledge in computer systems, probabilities and statistics, and programming. English language skills for text reading.
Learning Outcomes
Thorough grasp of computer systems performance evaluation concepts. Acquaintance with measurement techniques and tools and queuing network models analysis. Building the necessary background for performance evaluation via the analysis of queueing network models of computer systems.
Thorough grasp of parallel and distributed processing concepts. Acquaintance with different
types of multiprocessing that are related with multiprocessor systems with different characteristics.
Building the necessary background for the development of parallel and distributed
applications.
Practice in solving exercises based on taught theory.
General Competences
- Apply knowledge in practice
- Retrieve, analyse and synthesise data and information, with the use of necessary technologies
- Adapt to new situations
- Make decisions
- Work autonomously
- Work in teams
- Be critical and self-critical
- Advance free, creative and causative thinking
Course Content (Syllabus)
Measurement techniques and tools. Workload selection. Workload characterization. Capacity planning. Benchmarking. Monitoring. Data presentation. Experimental design and data analysis. Queueing models. Types of stochastic processes. Markov Chains. M/M/1 queue. M/M/m queue. Queues with finite buffers. Queueing networks. Analysis of queueing networks. Queueing network models of computer systems. Performance metrics. Operational laws. Mean-Value Analysis (MVA) . Approximate MVA. Web performance.
Introduction to Parallel and Distributed Processing. General description of parallel and distributed processing systems. Performance evaluation, Amdahl’s Law. Cluster Computing -
Grid Computing – Cloud Computing. Use of MPI for distributed processing. Parallel and distributed processing applications. Algorithms for task assignment -Job Scheduling.
Keywords
Performance, Computer Systems, Parallel, Distributed, Processing
Educational Material Types
- Slide presentations
- Book
Use of Information and Communication Technologies
Use of ICT
- Use of ICT in Course Teaching
- Use of ICT in Communication with Students
Description
Use of computer for teaching. Use of eLearning for communication.
Course Organization
| Activities | Workload | ECTS | Individual | Teamwork | Erasmus |
|---|---|---|---|---|---|
| Lectures | 52 | ✓ | |||
| Reading Assigment | 57 | ||||
| Project | 30 | ✓ | ✓ | ||
| Exams | 3 | ||||
| Other / Others | 8 | ✓ | ✓ | ||
| Total | 150 |
Student Assessment
Description
Written exams 80%, project 20% (will be counted only provided that the written exam is graded with at least 4.5).
Student Assessment methods
- Written Exam with Short Answer Questions (Summative)
- Written Exam with Extended Answer Questions (Summative)
- Written Assignment (Summative)
- Written Exam with Problem Solving (Summative)
Bibliography
Course Bibliography (Eudoxus)
Ηλεκτρ. Βιβλίο Εύδοξος: Ανάλυση Επίδοσης Υπολογιστικών Συστημάτων, Σταφυλοπάτης Ανδρέας Γεώργιος, Σιόλας Γεώργιος https://repository.kallipos.gr/bitstream/11419/6055/1/master-KOY.pdf
Γ. Πάντζιου, Β. Μάμαλης, και Α. Τομαράς, "Εισαγωγή στον Παράλληλο Υπολογισμό", Εκδόσεις Νέων Τεχνολογιών, Αθήνα 2013.
Additional bibliography for study
• Ελένη Καρατζά, "Απόδοση Υπολογιστικών Συστημάτων", Σημειώσεις/Διαφάνειες, https://elearning.auth.gr/auth/saml/login.php. β. Επιπρόσθετη βιβλιογραφία • E.D. Lazowska, J. Zahorjan, G. S. Graham, K.C. Sevcik, "Quantitative System Performance: Computer System Analysis Using Queueing Network Models", Prentice- Hall, Inc., 1984 (e-book). • Raj Jain, "The art of Computer Systems Performance Analysis", J. Wiley and Sons, 1991. • Daniel A. Menasce, Virgilio A. F. Almeida, "Capacity planning for web performance", Prentice Hall, 1998. • D. A. Menasce, V. A. F. Almeida, L. W. Dowdy, "Capacity Planning and Performance modelling, From Mainframes to Client Servers", Prentice Hall, 1994. • D. A. Menasce, V. A. F. Almeida, L. W. Dowdy, "Performance by Design: Computer Capacity Planning By Example", Prentice Hall PTR, 2004. • D.J. Lilja, "Measuring Computer Performance: A Practitioner's Guide", Cambridge University Press, 2000. • G. Bolch, S. Greiner, H. De Meer, K.S. Trivedi, "Queueing Networks and Markov Chains: Modeling and Performance Evaluation with Computer Science Applications", Wiley-Interscience, 2006.
• Γ. Κ. Παπακωνσταντίνου, Θ. Α. Θεοχάρης, Π. Δ. Τσανάκας, "Συστήματα Παράλληλης Επεξεργασίας", Συμμετρία, Αθήνα 1994. • Rajkumar Buyya, "High Performance Cluster Computing: Programming and Applications", Vol.II, Prentice Hall, 1999. • B. Wilkinson, and M. Allen, "Parallel Programming, Techniques and Applications Using Networked Workstations and Parallel Computers", Prentice Hall, 1999. • A. Grama, A. Gupta, G. Karypis, and V. Kumar, "Introduction to Parallel Computing", Second Edition, Person, Addison Wesley, 2003. • F. Cottet et. als., "Scheduling in Real-Time Systems", Wiley, 2002. • H. Jordan and G. Alaghband, "Fundamentals of Parallel Processing", Prentice Hall, 2003. • Ian Foster, "Designing and Building Parallel Programs", Addison-Wesley 1994 - (ebook). • Norm Matloff, "Programming on Parallel Machines, GPU, Multicore, Clusters and More" - (e-book). Επιπρόσθετα ερευνητικά άρθρα.
Last Update
14-08-2019
