| ... | @@ -17,8 +17,7 @@ Profiling results across the whole application: Includes the following profiling |
... | @@ -17,8 +17,7 @@ Profiling results across the whole application: Includes the following profiling |
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Profiling results per hotspot: Includes the hotspot ID, source file, start and end line of the specific hotspot, as well as the following indicators:
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Profiling results per hotspot: Includes the hotspot ID, source file, start and end line of the specific hotspot, as well as the following indicators:
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* CPU cycles
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* CPU cycles
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* Ratio of cache misses
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* Ratio of cache misses
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The hotspots can be identified at two granularity levels: At function-level and at loop-level. Developers can configure this selecting by “Hotspot Granularity”. The indicator values for each hotspot are adjusted based on the granularity level.
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The hotspots can be identified at two granularity levels: At function-level and at loop-level. Developers can configure this selecting by “Hotspot Granularity”.
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The values of the indicators are obtained by dynamic analysis, by using the flow described in 3.1.1. However, they can also be obtained on an actual embedded platform, if available.
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Figure 3 shows the values of a subset of the acceletor-specific indicators (i.e. the ones that influence the accelerator decision in higher degree than the others) for each hotspot. The values of these indicators are shown when “Full Analysis” is initially selected. The “Hotspot Granularity” is also applicable in this case.
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Figure 3 shows the values of a subset of the acceletor-specific indicators (i.e. the ones that influence the accelerator decision in higher degree than the others) for each hotspot. The values of these indicators are shown when “Full Analysis” is initially selected. The “Hotspot Granularity” is also applicable in this case.
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