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Performance Modeling and Benchmarking of Event-Based ... - DVS

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98 CHAPTER 5. BENCHMARKING OF EVENT-BASED SYSTEMS<br />

Figure 5.17: Formal Measurement Points during SPECjms2007 Run [214]<br />

Collecting Runtime stats 1 for the last 300 sec. statistics complete in 0 seconds<br />

=======Interaction 1 =======<br />

- Predicted Sent/Received: 61672.71 / 61672.71<br />

- Measured Sent/Received: 62509(+1.36 %) / 62510(+1.36 %)<br />

=======Interaction 2 =======<br />

- Predicted Sent/Received: 27341.57 / 31658.66<br />

- Measured Sent/Received: 28143(+2.93 %) / 32604(+2.99 %)<br />

=======Interaction 3 =======<br />

- Predicted Sent/Received: 674.55 / 6745.45<br />

- Measured Sent/Received: 703(+4.22 %) / 7030(+4.22 %)<br />

=======Interaction 4 =======<br />

- Predicted Sent/Received: 21877.14 / 21877.14<br />

- Measured Sent/Received: 21899(+0.1 %) / 21896(+0.09 %)<br />

=======Interaction 5 =======<br />

- Predicted Sent/Received: 77869.59 / 77869.59<br />

- Measured Sent/Received: 79321(+1.86 %) / 79323(+1.87 %)<br />

=======Interaction 6 =======<br />

- Predicted Sent/Received: 1919.96 / 19199.58<br />

- Measured Sent/Received: 1860(-3.12 %) / 18599(-3.13 %)<br />

=======Interaction 7 =======<br />

- Predicted Sent/Received: 1383.68 / 13836.83<br />

- Measured Sent/Received: 1414(+2.19 %) / 14139(+2.18 %)<br />

Time to collect <strong>and</strong> process periodic runtime stats (msec): 428<br />

Figure 5.18: Output <strong>of</strong> Run Time Reporter<br />

The final reporter generates a set <strong>of</strong> detailed result files. These provide the data in different<br />

granularity <strong>and</strong> allow in-depth analysis <strong>of</strong> the run.<br />

2. Run Time Reporter<br />

The run time reporter collects periodically measurements <strong>and</strong> statistics on the satellites<br />

<strong>and</strong> forwards them to the controller node, where they are processed to generate run time<br />

reports. These reports provides information on the running system <strong>and</strong> how current message<br />

counts differ from model’s prediction (see Figure 5.18). By this, an early identification<br />

<strong>of</strong> message backlogs at run time is possible.

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