Q I N G A O 1, X U H U I Z H A N G 1, P E I - L U E N P A T R I C K R A U 11   INSTITUTE OF HUMAN FACTORS & ERGONOMICS, DE...
CONTENT• Motivation• Approach to Performance Visualization• Review of Performance Visualization Techniques for  Large-Scal...
MOTIVATION                                                                  Exascale computers: 1000 times                ...
PERFORMANCE VISUALIZATION    Program                              Visualization                              Visual    beh...
APPROACH TO PERFORMANCE         VISUALIZATION                        Enabling access to performance data to beInstrumentat...
APPROACH TO PERFORMANCE           VISUALIZATION• Instrumentation  • What to be instrumented?       Fidelity               ...
APPROACH TO PERFORMANCE          VISUALIZATION• Measurement • Tracing   • More detailed execution information   • Necessar...
APPROACH TO PERFORMANCE          VISUALIZATION• Data analysis  • Microscopic and macroscopic metrics  • Method    • Data r...
APPROACH TO PERFORMANCE             VISUALIZATION• Visualization  • Basic visual components involved in information visual...
CLASSIFICATION OF PERFORMANCE  VISUALIZATION TECHNIQUES Category             Performance Visualization               Examp...
SIMPLE VISUAL STRUCTURES• Statistical charts  • Provide an overview of    important performance    metrics  • Enable quick...
SIMPLE VISUAL STRUCTURES• Time-line views  • Showing the evolution of performance statistics over time                    ...
SIMPLE VISUAL STRUCTURES• Time-line views  • Describing run-time behaviors and communication paths                        ...
SIMPLE VISUAL STRUCTURES• Time-line views  • • Facilitating source code level analysis    AerialVision: PC-Histogram      ...
SIMPLE VISUAL STRUCTURES• Information typography                                           Proposed hierarchical views of ...
SIMPLE VISUAL STRUCTURES• Information landscape         a.        Triva: information landscape based on   b.   Triva: info...
SIMPLE VISUAL STRUCTURES• Trees and networks        a.    Paradyn: Performance Consultant,         b.   Cone Trees: 3D vis...
COMPOSED STRUCTURE• Single-axis composition  • Multiple graphs sharing    single axis• Double-axis composition  • Multiple...
INTERACTIVE STRUCTURES• Direct interaction through the  visualization  •   Magifying lens  •   Panning, selecting, re-posi...
ATTENTION-REACTIVE VISUAL                     STRUCTURES  • Limited usage in performance visualization systems            ...
SUMMARY & OUTLOOK• Summary issues that need to be addressed  throughout the process of performance visualization• Review p...
THANKS, AND QUESTIONS?Performance Visualization for Large-scale Computing Systems: A Literature Review   22
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[HCII2011] Performance Visualization for Large Scale Computing System - A Literature Review

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[HCII2011] Performance Visualization for Large Scale Computing System - A Literature Review

  1. 1. Q I N G A O 1, X U H U I Z H A N G 1, P E I - L U E N P A T R I C K R A U 11 INSTITUTE OF HUMAN FACTORS & ERGONOMICS, DEPT. OF INDUSTRIAL ENGINEERING, TSINGHUA UNIVERSITY, BEIJING, 100084, CHINA A N T H O N Y A . M A C I E J E W S K I 2, H O W A R D J A Y S I E G E L 2,3 2E L E C T R I C A L A N D C O M P U T E R E N G I N E E R I N G D E P A R T M E N T , 3C O M P U T E R S C I E N C E D E P A R T M E N T COLORADO STATE UNIVERSITY, FORT COLLINS, CO 80523 -1373 USA PERFORMANCE VISUALIZATION FOR LARGE-SCALE COMPUTING SYSTEMS A Literature Review HCI International 2011 9-14 July, Orlando, USA
  2. 2. CONTENT• Motivation• Approach to Performance Visualization• Review of Performance Visualization Techniques for Large-Scale Systems• Future Work Performance Visualization for Large-scale Computing Systems: A Literature Review 2
  3. 3. MOTIVATION Exascale computers: 1000 times faster than the currentNeed for extreme scale petascale systemscomputing solutions Immense volume and Need to performance complexity of the monitoring & tuning in run- performance data time for extreme-scale systems Need for powerful and A review of existing usable performance performance visualization methods visualization tool for extreme- and tools for large scale system scale systems Performance Visualization for Large-scale Computing Systems: A Literature Review 3
  4. 4. PERFORMANCE VISUALIZATION Program Visualization Visual behavior Representations Data View Visual transformation Transformation Mappings Raw Data Views data tables Source: Card, 2002 Human Interaction• Goal: • Augmenting cognition with the human visual system’s highly tuned ability to see patterns and trends • Aid comprehension of the dynamics, intricacies, and properties of program execution Performance Visualization for Large-scale Computing Systems: A Literature Review 4
  5. 5. APPROACH TO PERFORMANCE VISUALIZATION Enabling access to performance data to beInstrumentation measured Recording selected data during the run-time of theMeasurement program Data analysis Analyzing data for performance visualization Mapping performance characteristics to proper Visualization visual representations and interactions Performance Visualization for Large-scale Computing Systems: A Literature Review 5
  6. 6. APPROACH TO PERFORMANCE VISUALIZATION• Instrumentation • What to be instrumented? Fidelity Reflect application Minimizing performance as perturbation of Pertubation closely as possible that behavior as much as possible • Approach • Hardware • Less performance degradation • Poor portability • Software • Better portability • Automation required for large-scale systems Performance Visualization for Large-scale Computing Systems: A Literature Review 6
  7. 7. APPROACH TO PERFORMANCE VISUALIZATION• Measurement • Tracing • More detailed execution information • Necessary for visualizing detailed program run-time behaviors • E.g., Virtue, Pajé • Profiling • Collects only summary statistics, mostly with hardware counters • Less pertubation by sacrificing fidelity • Allow data collection with long execution time • E.g., SvPablo • Trigger for recording action • Event-driven • Periodically (sampling) • Real-time or post-mortem? • For distributed application, real-time measurement and visualization is necessary Performance Visualization for Large-scale Computing Systems: A Literature Review 7
  8. 8. APPROACH TO PERFORMANCE VISUALIZATION• Data analysis • Microscopic and macroscopic metrics • Method • Data reduction • Multivariate statistical analysis • Application-specific analysis • Bates, 1995: Recognizing high-level program behaviors • AIMS: Pointing out causes of poor performance, generating scalability trends Performance Visualization for Large-scale Computing Systems: A Literature Review 8
  9. 9. APPROACH TO PERFORMANCE VISUALIZATION• Visualization • Basic visual components involved in information visualization (Card, 2002) • Spatial substrate • Marks • Connections • Enclosures Types of marks, source: Card, 2002 • Retinal properties • Temporal encoding Retinal properties, source: Card, 2002 Performance Visualization for Large-scale Computing Systems: A Literature Review 9
  10. 10. CLASSIFICATION OF PERFORMANCE VISUALIZATION TECHNIQUES Category Performance Visualization Example applications and studies Techniques Simple visual Pie charts, distribution, box plots, ParaGraph [2], PET [20], SvPablo [16], structures kiviat diagrams VAMPIR [21], Devise [22], AIMS [9] Timeline views Paje [23], AIMS [9], Devise [22], AerialVision [24], Paraver [25], SIEVE [14], Virtue [13], utilization and algorithm timeline views in [17] Information typologies SHMAP [26], Vista [4], Voyeur [27], processor and network port display in [28], hierarchical display in [12] Information landscape Triva [29], Cichild [30] Trees & networks Paradyn [18], Cone Trees [31], Virtue [13], [32] Composed visual Single-axis composition AIMS [9], Vista [4] structures Double-axis composition Devise [22], AerialVision [24] Case composition Triva [29] Interactive visual Interaction through controls (data Paje[23], data input, filtering, structure input, data transformation, visual and view manipulation in [28] mapping definition, view operations) and [32] Interaction through images Virtue [13], Cone Trees [31], (magnifying lens, cascading displays, Devise [22], direct manipulation of the linking and brushing, direct 3D cone and virtual threads in [32] manipulation of views and objects) Focus + context Macro-micro composite view Microscopic profile in [4], visual structures PC-Histogram in [24] Performance Visualization for Large-scale Computing Systems: A Literature Review 10
  11. 11. SIMPLE VISUAL STRUCTURES• Statistical charts • Provide an overview of important performance metrics • Enable quick identification a. PET: Bar chart of resource utilization b. Pajé Pie chart representing the percentage : of major problems percentage of different processors [22] of time with different number of active threads at a node [17] c. SvPablo: color matrix of metrics, each d. ParaGraph: Kiviat diagram showing load column representing a performance metric, imbalance among different processors [7] and color representing the value [13] Performance Visualization for Large-scale Computing Systems: A Literature Review 11
  12. 12. SIMPLE VISUAL STRUCTURES• Time-line views • Showing the evolution of performance statistics over time Utilization and overhead view in Alexandrov et al., 2010 Time views of utilization/computation/communication metrics of AerialVision AerialVision’s time view of runtime warp divergence breakdown Performance Visualization for Large-scale Computing Systems: A Literature Review 12
  13. 13. SIMPLE VISUAL STRUCTURES• Time-line views • Describing run-time behaviors and communication paths Virtue: time-tunnel displayPajé visualization of program execution and communication :AIMS: visualization of program executions ParaGraph: Space-time diagram Performance Visualization for Large-scale Computing Systems: A Literature Review 13
  14. 14. SIMPLE VISUAL STRUCTURES• Time-line views • • Facilitating source code level analysis AerialVision: PC-Histogram SIEVE: Contour-plot showing calls to a specific function Performance Visualization for Large-scale Computing Systems: A Literature Review 14
  15. 15. SIMPLE VISUAL STRUCTURES• Information typography Proposed hierarchical views of a complex reconfigurablePort display showing job computing applicationallocation, communication traffic,and route between nodes of acluster Performance Visualization for Large-scale Computing Systems: A Literature Review 15
  16. 16. SIMPLE VISUAL STRUCTURES• Information landscape a. Triva: information landscape based on b. Triva: information landscape based network typology on resource hierarchy c. Cichild: interpolated surfaces showing network delays between different sites Performance Visualization for Large-scale Computing Systems: A Literature Review 16
  17. 17. SIMPLE VISUAL STRUCTURES• Trees and networks a. Paradyn: Performance Consultant, b. Cone Trees: 3D visualization of tree showing a search hierarchy [14] structures [31] Virtue: Geographic network display [15] Performance Visualization for Large-scale Computing Systems: A Literature Review 17
  18. 18. COMPOSED STRUCTURE• Single-axis composition • Multiple graphs sharing single axis• Double-axis composition • Multiple graphs sharing AIMS: composite view of procedure execution graph on double axis each node and machine-load chart of each node• Case compositions • Two graphs having a single mark for each case fused Devise: message behavior visualization Performance Visualization for Large-scale Computing Systems: A Literature Review 18
  19. 19. INTERACTIVE STRUCTURES• Direct interaction through the visualization • Magifying lens • Panning, selecting, re-positioning • Cascading display (e.g., ConeTrees) • Use of gestures (e.g., Virtue)• Indirect interaction through controls • Interactions with underlying computation,Virtue: Magnifying lens such as data-related controls and definitions of visual mapping • View configurations • Scroll-bars, zoom in/out, sliders… Performance Visualization for Large-scale Computing Systems: A Literature Review 19
  20. 20. ATTENTION-REACTIVE VISUAL STRUCTURES • Limited usage in performance visualization systems AerialVision: PC histogramVista: Filmstrip view of utilization Performance Visualization for Large-scale Computing Systems: A Literature Review 20
  21. 21. SUMMARY & OUTLOOK• Summary issues that need to be addressed throughout the process of performance visualization• Review performance visualization techniques from 21 systems• Challenge: huge data size requires good scalability • Data abstraction method from scientific visualization • Visualization based on focus + context abstraction• Challenge: ergonomics and usability issues • Understanding of characteristics and limitations and human sensory and cognition capabilities Performance Visualization for Large-scale Computing Systems: A Literature Review 21
  22. 22. THANKS, AND QUESTIONS?Performance Visualization for Large-scale Computing Systems: A Literature Review 22

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