Course Details
Subject {L-T-P / C} : CS6504 : Performance Analysis of Computing Systems { 3-0-0 / 3}
Subject Nature : Theory
Coordinator : Dr. Sanjeev Patel
Syllabus
Introduction to Probability Models and Simulation: Probability space, Random variables, Discrete and Continuous distribution: uniform, geometric, exponential, normal distribution etc, System Modeling, Measurement techniques, Experimental design, workload design, Simulations, Data Analysis and Visualization Basics of Modeling: Performance metrics: Bandwidth utilization, throughput, delays, error rate, network reliability etc. Poisson process, Bernoulli splitting, PASTA, and Markov chain theory Queuing Theory: Arrival and service processes, Server disciplines, Queuing networks: Open vs closed networks, M/M/1, M/M/1/K, M/M/m, M/M/m/m. M/G/1 full analysis Simulation and Analysis of Computing Systems: time averages versus ensemble averages, Asymptotic bounds and limit theorems, confidence intervals, generating random variables for simulation, Inspection Paradox, Empirical Workload Measurements: heavy-tailed property, Pareto distributions, self-similarity, heavy-tailed distributions Applications of Computing Systems: analyze the scheduling algorithms and different computing system based on real-life application.
Course Objectives
- Explain the significance of performance to assess the operational and functional lifetime of computing systems
Course Outcomes
After successful completion of the course, students would be able to: <br />-Explain the significance of performance to assess the operational and functional lifetime of computing systems <br />-Define performance goals for models, methods and algorithms in computational systems <br />-Identify system-specific metrics to evaluate the workload performance of the processor, database, network and server <br />-Implement suitable performance analysis techniques involving modelling, simulation and measurement, owing to specific criteria, involving - execution time, level of accuracy, etc. <br />-Employ probability theory and computational statistics to analyze system performance <br />-Apply random variables to model the outcome of random experiments using discrete and continuous probability distributions
Essential Reading
- Sheldon M. Ross, Introduction to Probability Models, Academic Press , 7th Edition
- R. Jain, The Art of Computer Systems Performance Analysis: Techniques for Experimental Design, Measurement, Simulation and Modeling, John Wiley & Sons,
Supplementary Reading
- Kishor S. Trivedi, Probability and Statistics with Reliability, Queueing, and Computer Science Applications,, Wiley , 2nd edition, 2008.
- Sanjay K. Bose, An Introduction to Queuing System, Springer
Journal and Conferences
- IEEE Journal
- IEEE Conferences