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The Art of Data Presentation

The Art of Data Presentation. Overview. Types of Variables Guidelines for Preparing Good Charts Common Mistakes in Preparing Charts Pictorial Games Special Charts for Computer Performance Gantt Charts Kiviat Graphs Schumacher Charts Decision Maker’s Games. Types of Variables.

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The Art of Data Presentation

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  1. The Art of Data Presentation

  2. Overview • Types of Variables • Guidelines for Preparing Good Charts • Common Mistakes in Preparing Charts • Pictorial Games • Special Charts for Computer Performance • Gantt Charts • Kiviat Graphs • Schumacher Charts • Decision Maker’s Games

  3. Types of Variables • Type of computer: Super computer, minicomputer, microcomputer • Type of Workload: Scientific, engineering, educational • Number of processors • Response time of system

  4. Guidelines for Preparing Good Charts • Require minimum effort from the readerDirect labeling vs. legend box • Maximize Information: Words in place of symbolsCleary label the axes

  5. Guidelines (cont) • Minimize Ink: No grid lines, more details • Use Commonly accepted practices: origin at (0,0)Independent variable (cause) along x axis, linear scales, increasing scales, equal divisions • Avoid ambiguity: Show coordinate axes, scale divisions, origin. Identify individual curves and bars. • See checklist in Box 10.1

  6. Common Mistakes in Preparing Charts • Presenting too many alternatives on a single chartMax 5 to 7 messages => Max 6 curves in a line charts, no more than 10 bars in a bar chart, max 8 components in a pie chart • Presenting many y variables on a single chart

  7. Common Mistakes in Charts (Cont) • Using symbols in place of text • Placing extraneous information on the chart: grid lines, granularity of the grid lines • Selecting scale ranges improperly: automatic selection by programs may not be appropriate

  8. 8000 8100 8300 8200 Common Mistakes in Charts (Cont) • Using a line chart in place of column chart: line => Continuity MIPS CPU Type

  9. Pictorial Games • Using non-zero origins to emphasize the difference Three quarter high-rule => height/width > 3/4

  10. Pictorial Games (Cont) • Using double-whammy graph for dramatizationUsing related metrics

  11. Pictorial Games (Cont) • Plotting random quantities without showing confidence intervals

  12. Pictorial Games (Cont) • Pictograms scaled by height MinePerformance = 2 YoursPerformance = 1

  13. 0 8 6 4 2 0 8 6 4 2 Pictorial Games (Cont) • Using inappropriate cell size in histograms 12 12 10 10 Frequency Frequency [0,2) [2,4) [4,6) [6,8) [8,10) [10,12) [0,6) [6,12) Response Time Response Time

  14. 0 0 2 4 6 8 Pictorial Games (Cont) • Using broken scales in column charts 12 12 10 11 Resp. Time Resp. Time 10 9 F F A B C D E A B C D E System System

  15. Special Charts for Computer Performance • Gantt charts • Kiviat Graphs • Schumacher's charts

  16. Gantt Charts • Shows relative duration of a number of conditions 60 CPU 20 20 IO Channel 30 10 5 15 Network 0% 20% 40% 60% 80% 100% Utilization

  17. Example: Data for Gantt Chart

  18. Draft of the Gantt Chart

  19. Final Gantt Chart

  20. CPUBusy CPU inSupervisor State CPU OnlyBusy CPU/ChannelOverlap CPU inProblem State Channel onlyBusy CPUWait Any ChannelBusy Kiviat Graphs • Radial chart with even number of metrics • HB and LB metrics alternate • Ideal shape: star

  21. CPUBusy CPU inSupervisor State CPU OnlyBusy CPU inProblem State CPU/ChannelOverlap CPUWait Channel onlyBusy Any ChannelBusy Kiviat Graph for a Balanced System • Problem: Inter-related metrics CPU busy = problem state + Supervisor state CPU wait = 100 – CPU busy Channel only – any channel –CPU/channel overlap CPU only = CPU busy – CPU/channel overlap

  22. Shapes of Kiviat Graphs CPU Keel boat I/O Wedge I/O Arrow

  23. Merrill’s Figure of Merit (FoM) • Performance = {x1, x2, x3, …, x2n}Odd values are HB and even values are LB • x2n+1 is the same as x1 • Average FOM = 50%

  24. Example: FoM • System A:

  25. FoM Example (Cont) • System B:System B has a higher figure of merit and it is better.

  26. Figure of Merit: Known Problems • All axes are considered equal • Extreme values are assumed to be better • Utility is not a linear function of FoM • Two systems with the same FoM are not equally good. • System with slightly lower FoM may be better

  27. Kiviat Graphs For Other Systems • Networks: ApplicationThroughput LinkOverhead Packets With Error LinkUtilization Implicit Acks Duplicate Packets

  28. Schumacher Charts • Performance matrix are plotted in a tabular manner • Values are normalized with respect to long term means and standard deviations • Any observations that are beyond mean  one standard deviation need to be explained • See Figure 10.25 in the book

  29. Performance Analysis Rat Holes Workload Metrics Configuration Details

  30. Reasons for not Accepting an Analysis • This needs more analysis. • You need a better understanding of the workload. • It improves performance only for long IOs/packets/jobs/files, and most of the IOs/packets/jobs/files are short. • It improves performance only for short IOs/packets/jobs/files, but who cares for the performance of short IOs/packets/jobs/files, its the long ones that impact the system. • It needs too much memory/CPU/bandwidth and memory/CPU/bandwidth isn't free. • It only saves us memory/CPU/bandwidth and memory/CPU/bandwidth is cheap. See Box 10.2 on page 162 of the book for a complete list

  31. Summary • Qualitative/quantitative, ordered/unordered, discrete/continuous variables • Good charts should require minimum effort from the reader and provide maximum information with minimum ink • Use no more than 5-6 curves, select ranges properly, Three-quarter high rule • Gantt Charts show utilizations of various components • Kiviat Graphs show HB and LB metrics alternatively on a circular graph • Schumacher Charts show mean and standard deviations • Workload, metrics, configuration, and details can always be challenged. Should be carefully selected.

  32. Ratio Games

  33. Overview • Ratio Game Examples • Using an Appropriate Ratio Metric • Using Relative Performance Enhancement • Ratio Games with Percentages • Ratio Games Guidelines • Numerical Conditions for Ratio Games

  34. Using an Appropriate Ratio Metric Example: • Throughput: A is better • Response Time: A is worse • Power (Ratio): A is better  could be a contradictory conclusion

  35. Using Relative Performance Enhancement • Example: Two floating point accelerators • Problem: Incomparable bases. Need to try both on the same machine

  36. Ratio Games with Percentages • Example: Tests on two systems 1. System B is better on both systems 2. System A is better overall. System A: System B:

  37. Ratio Games Guidelines • If one system is better on all benchmarks, contradicting conclusions can not be drawn by any ratio game technique

  38. Guidelines (cont) • Even if one system is better than the other on all benchmarks, a better relative performance can be shown by selecting appropriate base. • In the previous example, System A is 40% better than System B using raw data, 43% better using system A as a base, and 42% better using System B as a base. • If a system is better on some benchmarks and worse on others, contracting conclusions can be drawn in some cases. Not in all cases. • If the performance metric is an LB metric, it is better to use your system as the base • If the performance metric is an HB metric, it is better to use your opponent as the base • Those benchmarks that perform better on your system should be elongated and those that perform worse should be shortened

  39. Numerical Conditions for Ratio Games • A is better than B iff • Raw Data: • With A as the Base: • A is better than B iff

  40. Numerical Conditions (Cont) 2 B is betterusing all 3 Ratio of B/A response on benchmark j 1 A isbetterusing all 3 Base B Raw Data Base A 0 1 1 1 2 3 Ratio of B/A response on benchmark i

  41. Summary • Ratio games arise from use of incomparable bases • Ratios may be part of the metric • Relative performance enhancements • Percentages are ratios • For HB metrics, it is better to use opponent as the base

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