Lecture#11-12.ppt - Performance analysis of computing...

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Performance analysis of computing systems Lecture#11-12 Sanjeev patel Cse&it dept. jiit-128 noida 1
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Outline Objectives ( next ) The Art Common Mistakes Systematic Approach Case Study
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Objectives (1 of 6) Select appropriate evaluation techniques , performance metrics and workloads for a system. Techniques: measurement, simulation, analytic modeling Metrics: criteria to study performance (ex: response time) Workloads: requests by users/applications to the system Example: What performance metrics should you use for the following systems? a) Two disk drives b) Two transactions processing systems c) Two packet retransmission algorithms
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Objectives (2 of 6) Conduct performance measurements correctly Need two tools: load generator and monitor Example: Which workload would be appropriate to measure performance for the following systems? a) Utilization on a LAN b) Response time from a Web server c) Audio quality in a VoIP network
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Objectives (3 of 6) Use proper statistical techniques to compare several alternatives One run of workload often not sufficient Many non-deterministic computer events that effect performance Comparing average of several runs may also not lead to correct results Especially if variance is high Example: Packets lost on a link. Which link is better? File Size Link A Link B 1000 5 10 1200 7 3 1300 3 0 50 0 1
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Objectives (4 of 6) Design measurement and simulation experiments to provide the most information with the least effort. Often many factors that affect performance. Separate out the effects that individually matter. Example: The performance of a system depends upon three factors: A) garbage collection technique: G1, G2 none B) type of workload: editing, compiling, AI C) type of CPU: P2, P4, Sparc How many experiments are needed? How can the performance of each factor be estimated?
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Objectives (5 of 6) Perform simulations correctly Select correct language, seeds for random numbers, length of simulation run, and analysis Before all of that, may need to validate simulator Example: To compare the performance of two cache replacement algorithms: A) how long should the simulation be run? B) what can be done to get the same accuracy with a shorter run?
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Objectives (6 of 6) Use simple queuing models to analyze the performance of systems. Often can model computer systems by service rate and arrival rate of load Multiple servers Multiple queues Example: For a given Web request rate, is it more effective to have 2 single-processor Web servers or 4 single-processor Web servers?
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Outline Objectives (done) The Art ( next ) Common Mistakes Systematic Approach Case Study
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The Art of Performance Evaluation Evaluation cannot be produced mechanically Requires intimate knowledge of system Careful selection of methodology, workload, tools
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  • Spring '18
  • Client-server, common mistakes

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