- Renamed struct_.py -> structs.py again.
- Removed lfs.csv, instead prefering script specific csv files.
- Added *-diff make rules for quick comparison against a previous
result, results are now implicitly written on each run.
For example, `make code` creates lfs.code.csv and prints the summary, which
can be followed by `make code-diff` to compare changes against the saved
lfs.code.csv without overwriting.
- Added nargs=? support for -s and -S, now uses a per-result _sort
attribute to decide sort if fields are unspecified.
- Fixed added/removed count in scripts when an entry has no field in
the expected results
- Fixed a python-sort-type issue when by-field is missing in a result
- Changed --(tool)-tool to --(tool)-path in scripts, this seems to be
a more common name for this sort of flag.
- Changed BUILDDIR to not have implicit slash, makes Makefile internals
a bit more readable.
- Fixed some outdated names hidden in less-often used ifdefs.
Based loosely on Linux's perf tool, perfbd.py uses trace output with
backtraces to aggregate and show the block device usage of all functions
in a program, propagating block devices operation cost up the backtrace
for each operation.
This combined with --trace-period and --trace-freq for
sampling/filtering trace events allow the bench-runner to very
efficiently record the general cost of block device operations with very
little overhead.
Adopted this as the default side-effect of make bench, replacing
cycle-based performance measurements which are less important for
littlefs.
This adds -P/--propagate and -Z/--depth to perf.py for showing recursive
results, making it easy to narrow down on where spikes in performance
come from.
This ended up being a bit different from stack.py's recursive results,
as we end up with different (diminishing) numbers as we descend.
This provides 2 things:
1. perf integration with the bench/test runners - This is a bit tricky
with perf as it doesn't have its own way to combine perf measurements
across multiple processes. perf.py works around this by writing
everything to a zip file, using flock to synchronize. As a plus, free
compression!
2. Parsing and presentation of perf results in a format consistent with
the other CSV-based tools. This actually ran into a surprising number of
issues:
- We need to process raw events to get the information we want, this
ends up being a lot of data (~16MiB at 100Hz uncompressed), so we
paralellize the parsing of each decompressed perf file.
- perf reports raw addresses post-ASLR. It does provide sym+off which
is very useful, but to find the source of static functions we need to
reverse the ASLR by finding the delta the produces the best
symbol<->addr matches.
- This isn't related to perf, but decoding dwarf line-numbers is
really complicated. You basically need to write a tiny VM.
This also turns on perf measurement by default for the bench-runner, but at a
low frequency (100 Hz). This can be decreased or removed in the future
if it causes any slowdown.
