Lecture 1.pptx - CSE 5103:Computer Engineering Topics...

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CSE 5103:Computer Engineering Topics covered: Course outline, schedule and logistics
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General Information CSE 5103 :Performance Engineering Instructor : Reda Ammar Phone : 6-5285. Email : [email protected] Office : ITEB 254 Lecture time : Tue/Thu 9:30am– 10:00am Office hours : Tue 12:30 – 2:00pm, Thu 10:30am – 12:00pm, or by appointment (I will hang around for a few minutes at the end of each class). Web page : HuskyCT (Lecture notes, homework, and general announcements will be posted )
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Course Goals i. Understand, learn and practice the role of efficient and reliable systems in our day-to-day lives is discussed through the course. ii. Gain an appreciation that performance and reliability attributes are important for many real life systems and their impacts to the society. iii. Evaluate tradeoffs such as fault-tolerant vs. non fault-tolerant systems, performance vs. cost. iv. explore the impact of system architecture and configuration on the performance, reliability, and availability in a project. v. Exposed to the evolving application and use of concepts in probability and statistics to problems ranging from multiprocessor systems to modern technologies including web services, service- oriented architectures, middleware, and social networks.
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Expected Learning Outcomes Specific outcomes of instruction : a) The students will be able to apply the basic concepts of probability theory (both discrete and continuous) to real-world problems, including comparing average values with expected values based on sample size. b) The students will have a fundamental grasp of Markov chains, with applications to computer performance and availability modeling, for estimating performance and availability metrics. c) The students will be apply the concepts of reliability, conditional failure rate, and hazard rate, and analyze multiple component, partially redundant systems/networks for estimating reliability in terms of probability of failure and mean time to failure. d) The students will be able to identify stochastic processes in the real world and define and classify them and obtain various relevant metrics. e) The students will be able to derive estimators and confidence intervals for the parameters of a distribution.
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References 1. Class Notes 2. K. S. Trivedi, Probability and Statistics with Reliability, Queuing and Computer Science Applications, Second Edition, John Wiley.
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Course Topics Introduction and Motivation: Schedule, Logistics, Evaluation , Motivation for performance analysis Ways to study performance, Measurement vs. Simulation vs. Analytical Modeling Hierarchical Performance Model: Introduction to Hierarchical Performance Modeling, Gate level Performance Modeling, Combinational logic network, sequential logic network, assembly language, computational structure model, modeling interrupts, performance of sequential and parallel algorithms (flow analysis, cost equations), modeling threads’ communication.
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