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Description
We have received feedback that a Jupyter notebook with a "minimum working example" would be really good for new users to understand the process of generating patterns from gs_patterns for use with tools like Spatter. To facilitate this process, we'd like to create a notebook that covers the following topics:
Use either Lulesh or Bronson as an example for this notebook
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Introduction
Go over all the steps in the process (listed below). -
Finding Regions of Interest with vTune
Using Intel's vTune hotspots tool, how can a user determine which regions of their code are the most relevant? -
Using PIN to extract traces
- Using the hotspots from 2), detail how we can annotate the code with ROI pragmas and generate PIN traces.
- Show how long this process takes for a sample application
- Feeding traces to gs_patterns to get Spatter-compatible patterns
- Using traces from 3) generate Spatter-compatible JSON files.
- Briefly describe how gs_patterns bucketizes and "selects" patterns
- Show how long this takes (s) and how large (MB) the output can be
- Further analysis of gs_patterns output
- Detail how we can potentially identify exact calls and line numbers that generate significant patterns within our application.
- Show an example graph
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