Bechamel is a toolkit to do a micro-benchmarking on your functions. It able to
be extended with your measures. Indeed, Bechamel provides only GC measures.
Then, from your target, you can choose to use
something else available on your target.
The main purpose is to able to use Bechamel on GNU/Linux, Mac OSX, Windows and
MirageOS. Monotonic clock is available in all of these platforms.
Then, we provide 2 algorithms to analyze datas:
OLS (Ordinary Least Square)
RANSAC (Random Sample Consensus)
These algorithms come from
core_bench (which uses a
REALTIME clock), and
operf-micro (which is available only on GNU/Linux).
The main goal of
bechamel (instead to be a yet another benchmark tool) is to
let the end-user to manipulate measures. We provide a not-easy-to-use API
which give an access to collected informations (main difference with
benchmark). From it, we can produce a JSON output - and allow an other analyze
with an other tool From it, we can produce a JSON output - and allow an other
analyze with an other tool (main difference with
And finally, because some counters can be available in some specific platforms
perf), we allow the user to define their own counters and use them in
bechamel.perf is one of them (it needs a fork a
however - a dunification of this package).
To define your measure, you need to make a new module which respect interface
Measure.UNSAFE. Main function is to blit/set your value (which can be
anything) from result of your counter.
perf provides some counters like
Cpu_clock, then, we need to
int64 ref to what the counter returns. We save it, we execute your
function some times and ask again to get value of your counter. Finally, we do
diff between your first value and your second one and cast it to a float (to
be able to analyze it).
At the end, we generate plenty of values which can be analyze by an OLS
algorithm or RANSAC.
bechamel has a little
notty backend to be able to print results in a fancy
way. An example is available in the binary - image shows you the output.
notty is not a part of the core
bechamel, so user can print
results like he wants - of course, it's a little annoying work already done in
bechamel.notty - but feel free to put an other backend.
Finally, at the core,
bechamel has converter to JSON and can generate JSON
output from collected values. From them, you can process a smarter analyze than
OLS or RANSAC for example - this is the main purpose of
bechamel, be able to
manipulate results and check some assumptions.
eqaf, for example, needs to check if the equality function computes arguments
in a constant time - so it's not a benchmark strictly speaking but the main loop
to collect results and analyze algorithms are needed to check this kind of
In other way, because
eqaf want to be available in many platform, a
monotonic-clock in Mac OSX, Windows and GNU/Linux is needed too.