Improve Benchmarking Framework

[jon-chuang]

Benchmarking currently uses a statistical confidence to determine the number of iterations. However, this can lead to extremely long-running benchmarks. Hence, I suggest to limit the number of iterations by utilising benchmarking based on a max timeout.

This is the standard seen in C++ and Go. In this paradigm, fast results for fast developer iteration are more important than statistical significance.

[ValarDragon]

I think we should also better separate out MSM benches in the benchmarks, the time delays are way too long for benching field arithmetic changes.

[jon-chuang]

Actually, I've come to realise the long benching times comes not from the inadequacy of the benchmarking framework, but from the fact that generating the random data is done on a single thread and takes very long.

My suggestion is to use constant data which we can generate in a data.rs file.

[jon-chuang]

Alternatively, we can use a fn_once

[Pratyush]

Ah that's unforunate, but we can just parallelize the generation of the data, or maybe just sample a single input, and then mutate it somehow (eg: double it) to obtain the rest of the inputs?

[ValarDragon]

doubling it isn't great, because that introduces data dependencies into the core benchmark

[Pratyush]

No I mean, instead of doing

for i in 0..1000 {
	input.push(G::rand(&mut rng)
}
bencher.iter(...);

we do

let g = G::rand(&mut rng);
for i in 0..1000 {
	input.push(*g.double_in_place());
}
bencher.iter(...);

[jon-chuang]

I've used lazy static and it's insanely fast now, so I think no one will have any more complaints. I'll push changes soon

[jon-chuang]

oh but for MSM we might have to use a pseudo-uniform distribution, generated by multiplying generator with random scalars in small range.

[jon-chuang]

Actually, I realised for the particular case of MSM, bencher by default takes at least 300 samples, so it's just completely inadequate.