Topics in Performance Evaluation – Course Plan

Topics in Performance Evaluation

Course Plan

Classes are held on Sundays 10-12 in Shprintzak 213 and Tuesdays 2-4 in Shprintzak 26. The Sunday sessions will be held only on alternate weeks (recall that the course is 3 points) — see below for detailed list. PARTICIPATION IS MANDATORY.

Exercises are to be done in pairs. Note that this means that both members of the pair should work on each one, not that you alternate! Exercises are given each Tuesday and are due the following Monday in the morning.

Textbook chapters are listed in case you need to make up some study materials. Listed references are for added reading if you are interested; they are not required if you come to the lectures.

The following plan is subject to change — each week is final only after it happens...

ClassLecture materialExercises
Introduction:
116/2/14 Motivation and problems
The issues: techniques, metrics, and workloads
Using measurements, simulations, and analysis
Jain chap. 2, 3
ex0: looking at graphs
18/2/14 Visual data representation (slides)
Different types of graphs
Avoiding misleading representation
Jain chap. 10, 11; Tufte, The Visual display of Quantitative Information, 1983; Michael Friendly's Gallery of Data Visualization
ex1: plotting research results
[alternative ex1 for people who joined late]
225/2/14 Introduction to event-driven simulation ex2a: basic event-driven simulation
Queueing analysis:
32/3/14 Queues and queueing networks
Response time, utilization, and system dynamics
The M/M/1 queue
Jain chap. 30, 31
 
4/3/14 Little's law
Operational laws and bottleneck analysis
Open vs. closed systems
Jain chap. 31, 33
ex2b: simulating an M/M/1 queue
411/3/14 Case studies:
Analysis of network router with bounded buffer
Compare two slow processors to one fast one
ex3: analysis of join random queue
518/3/14 Queueing networks
Mean value analysis
Jain chap. 32, 34
ex4: simulating an M/M/k/b queue
ArgoUML project with simulator diagrams from class
Workloads:
623/3/14 Workload analysis and characterization
Summary statistics such as mean and median
Feitelson, Workload modeling for performance evaluation. Performance 2002 tutorials (or the long version)
 
25/3/14 Creating a variate from a distribution
Jain chap. 12, 28; Law/Kelton chap. 6, 8
ex5: generating random variates
730/3/14 Useful distributions
Parameter estimation techniques and goodness of fit
Comparing distributions using quantile-quantile plots
Law/Kelton chap. 8; Jain chap. 29
 
1/4/14 Heavy tails and long tails
Power laws and the Pareto distribution
Mass-count disparity and conditional expectation
Popularity and the Zipf distribution
Crovella, Performance evaluation with heavy tailed distributions. JSSPP 2001
ex6: fitting a distribution with Q-Q plots
829/4/14 Case study: load balancing
Oblivious balancing
Balancing based on workload characteristics
Harchol-Balter and Downey, Exploiting process lifetime distributions for dynamic load balancing. ACM Trans. Comput. Syst. 15(3) pp. 253-285, Aug 1997
ex7: characterizing requests from a web server
911/5/14 Feedback in workloads (slides)
The daily cycle of activity
User-based workload modeling
Shmueli and Feitelson, Using site-level modeling to evaluate the performance of parallel system schedulers. 14th MASCOTS, Sep 2006
project: extracting feedback data
13/5/14 Self similarity
The Hurst parameter
 
Simulation:
1020/5/14 Event-driven vs. time-driven simulation
Simulating the system in its steady state
Jain chap. 24; Law/Kelton chap. 9; Pawlikowski, Steady-state simulation of queueing processes. ACM Comput. Surv. 22(2) pp. 123-170 Jun 1990
ex8: simulation warmup
1125/5/14 Evaluating confidence intervals
Termination conditions and simulation length
Variance reduction
Jain chap. 25, 12; Law/Kelton chap. 11
 
27/5/14 Case study: networking evaluation (slides)
The ns-2 simulator and its use
The PlanetLab infrastructure
Paxson and Floyd, Difficulties in simulating the Internet. IEEE/ACM Trans. Netw. 9(4) pp. 392-403 Aug 2001
ex9: simulating rain to find pi
121/6/14 Experimental design and analysis of variation (slides)
ex10: back to event-based simulations
138/6/14 Case study: parallel job scheduling (slides)
Scheduling on parallel supercomputers
Backfilling
 
10/6/14 (Case study continued)
The effect of inaccurate runtime estimates
ex11: parallel job scheduling and backfilling
The End:
1417/6/14 Summary of exercises and simulations
Complementary approaches: measurement and experimentation
Final quiz (Example quiz and solutions)

 

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