Evaluation of CPU profiling tools: gperftools, Valgrind and gprof (2015)

Re:Evaluation of CPU profiling tools: gperftools, Valgrind a... by foota on Monday November 11, 2019 @09:02PM (#21510867)

Well, I'll start by saying I'm not familiar with any of those tools. Took a quick look at them though. It looks like Paraver offers a time domain look at performance? And cube seems to offer time based and a graphviz of the call tree.

In a flame graph the width of a stack frame correlates to the % of CPU time spent in that stack frame, and the y is the particular call stack.

This means that you can quickly tell what functions, and from what call sites, are the most expensive.

The only visualization I know of that matches the ability to quickly zero in on things, while maintaining context, is a graph of call stack with frames colored by cumulative CPU time, but that has the issue that laying out the graph is hard, and seeing everything at once is difficult.

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Re:Evaluation of CPU profiling tools: gperftools, Valgrind a... by gnufx on Tuesday November 12, 2019 @09:04AM (#21514122)

That may be OK in simple cases where you can easily eyeball it, if you're only interested in aggregated CPU time as a metric, and if you win most from optimizing the obvious function in all modes of the program. That's not necessarily the case in complex scientific codes, for instance, especially parallel ones.

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Re:Evaluation of CPU profiling tools: gperftools, Valgrind a... by foota on Tuesday November 12, 2019 @05:04PM (#21518671)

This is true. It's more useful for optimizing usage than it is for deep sleuthing of "why is this particular thing performing poorly".

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