Pew is a benchmarking library written in Rust based of Google's C++ Benchmarking library. It is currently in very alpha stages (I'd consider it an MVP). It was built with to be able to do the following (which you cannot do in the rust benchmarking library):
1) Pause and unpause the benchmark timer 2) Run multiple benchmarks by specifying a range of arguments 3) Creating some initial state that gets passed to all runs of the benchmark
Currently, it runs the benchmark enough times such that it runs for at least 1 second and then averages all those runs.
TODO: How do we make this more statistically significant? Run the benchmark till the variance settles?
This is available on crates.io. You can link it as a library,
or cargo install to also get the transpose script (see output).
The main exported macro is pew_main!. It accepts a comma separated list of
one of the following
<func_ident> -> RANGE(<lower_bound_expr>, <upper_bound_expr>, <mul_expr>)
<func_ident> -> GENRANGE(<generator_func_ident>, <lower_bound_expr>, <upper_bound_expr>, <mul_expr>)
where:
func_ident is the name of a function in scope. If using RANGE,
func_ident should have type Fn(&mut pew::State<u64>). If using
GENRANGE, func_ident should have type Fn(&mut pew::State<T>)
where T depends on the generator type (see below).lower_bound_expr, upper_bound_expr, and mul_expr are all numerical
types representing the lower, upper, and multiplcation value for the
benchmark. If using RANGE, state.get_input() will return all values
from i = lower_bound; i <= lower_bound; i *= mul. If using GENRANGE,
the generator function will receives the aforementioned values.generator_func_ident is the name of a function in scope. The function
type should be Fn(n: usize) -> T for some T: Clone + Default. This function will
be called once for every i in the range (see above). It will be generated
once per benchmark and cloned every time if the benchmark is run multiple
times. Note that cloning is not counted in the benchmark time.There are examples in the examples/ directory of how to use this. Basically,
you just want to define your benchmark functions and call pew_main! as
described above.
TODO: Add more examples
The output is a comma separated list of benchmark results (this is what
cargo cargo run --example example1 will output):
Name,Time (ns)
bm_vector_range/1024,102541
bm_vector_range/4096,423289
bm_vector_range/16384,1627492
bm_vector_range/65536,6692188
bm_vector_range/262144,26717609
bm_vector_range/1048576,106552932
bm_vector_gen/1024,102316
bm_vector_gen/4096,416523
bm_vector_gen/16384,1657982
bm_vector_gen/65536,6566634
bm_vector_gen/262144,26780184
bm_vector_gen/1048576,105760350
Oftentimes I run multiple benchmarks on the same range and plot the results.
I find it is easier to plot the results by transposing the output. There is
a binary pew_transpose that does just that. It can be run by piping the
output of the benchmark code:
cargo run --example example1 | pew_transpose
The transposed output of the above would be:
Size,bm_vector_range,bm_vector_gen
1024,105974,106845
4096,418835,409143
16384,1646391,1655855
65536,6566094,6668369
262144,27025772,26948818
1048576,108144239,107596626
TODO: Add more output types (e.g. pretty printed, JSON, etc).
This code is licensed under Apache 2.0.