You optimized your code to apply a loop interchange mechanism that gave you about 22 seconds of improvement in the application execution time. To understand whether you got rid of the hotspot and what kind of optimization you got per function, re-run the Hotspots analysis on the optimized code and compare results:
Compare Results Before and After Optimization
The Summary window opens displaying application-level performance statistics for both results and their difference values.
Identify the Performance Gain
The Result Summary section of the Summary window shows difference information as follows: <Result 1 metric> – <Result 2 metric> = <metric Difference>.
You see that after optimization all metrics values have reduced significantly, though CPI Rate is still an issue (>1).
Switch to the Bottom-up window to view the CPU time usage per function for each result and their differences side by side.
Since for the second run you removed the
multiply1 function, its time shows up in the Difference column as a performance gain.
Click the CPU Time:r002ah column to sort the data in the grid by this column.
multiply2 function shows up on top as the biggest CPU Time hotspot for the result
r002ah, though it performs much better than
multiply1. You may try to optimize the code further using more advanced algorithms, for example, block-structuring access to matrix data to maximize cache reuse.