Parallelize JIT functions

[mhostetter]

Improves performance for #439.

Matrix multiplication

In [1]: import galois

In [2]: GF = galois.GF(2**16, compile="jit-calculate")

In [3]: A = GF.Random((500, 500), seed=1)

In [4]: A = GF.Random((300, 400), seed=1)

In [5]: B = GF.Random((400, 500), seed=2)

# Before
In [6]: %timeit A @ B
1.49 s ± 14.7 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)

# After
In [7]: %timeit A @ B
152 ms ± 732 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)

Polynomial evaluation

In [1]: import galois

In [2]: GF = galois.GF(2**16, compile="jit-calculate")

In [3]: f = galois.Poly.Random(100, seed=1, field=GF)

In [4]: x = GF.Random(100_000, seed=1)

# Before
In [6]: %timeit f(x)
220 ms ± 745 µs per loop (mean ± std. dev. of 7 runs, 1 loop each)

# After
In [6]: %timeit f(x)
31.3 ms ± 1.03 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)

[codecov]

Codecov Report

Base: 96.38% // Head: 96.38% // Increases project coverage by +0.00% 🎉

Coverage data is based on head (25cfcf9) compared to base (153614a).
Patch coverage: 100.00% of modified lines in pull request are covered.

Additional details and impacted files

@@              Coverage Diff               @@
##           release/0.3.x     #440   +/-   ##
==============================================
  Coverage          96.38%   96.38%           
==============================================
  Files                 42       42           
  Lines               5529     5533    +4     
==============================================
+ Hits                5329     5333    +4     
  Misses               200      200           

Impacted Files	Coverage Δ
src/galois/_domains/_function.py	97.00% <100.00%> (+0.03%)	⬆️
src/galois/_domains/_linalg.py	95.55% <100.00%> (+0.01%)	⬆️
src/galois/_polys/_dense.py	96.80% <100.00%> (+0.01%)	⬆️

Help us with your feedback. Take ten seconds to tell us how you rate us. Have a feature suggestion? Share it here.

☔ View full report at Codecov.
📢 Do you have feedback about the report comment? Let us know in this issue.