[WIP] Added functionality of parallel maximal independent set

[pnijhara]

What does this PR change?

This PR implements the parallel maximal independent set via Luby's random permutation mechanism (solving issue #144)

• Add parallel implementation of maximal_independent_set algorithm
• Implements Luby-style randomized parallel algorithm for speedup on large graphs (50K+ nodes)
• Works best on large graphs (n>50,000)

What is your approach, and why did you choose it?

A standard parallel MIS algorithm assigns a random priority to every vertex once per round, then selects all locally maximal vertices at the same time:

while graph not empty:
    generate random priority for each vertex
    S = { u | priority(u) > priority(v) for all v in N(u) }
    add S to MIS
    remove S ∪ N(S) from graph

Why this is parallel:

• Priority comparisons for all vertices are independent operations.
• Set S can be selected in one parallel pass.
• All vertices in S are guaranteed independent.
• Removing S ∪ N(S) can also be done in parallel.

This matches the PRAM formulation and is widely used in CPU and GPU environments.

Brief summary of changes (1–2 lines)

• Added a file algorithms/mis.py
• Added tests for algorithms/mis.py in algorithms/tests/test_mis.py
• Found in the local benchmark tests that for node count less than 50K, sequential code is working best; however, for larger graphs such as n = 100K and 1M, parallel code is working best. This may be because of joblib's parallelization overhead. I tested this in C++ with OpenMP. The same issue persists there, but with a lesser node count.

[pnijhara]

@dschult please review it.

[dschult]

Thanks for this!

Some formatting suggestions before diving into the code/tests:

• we typically don't put error messages on the "assert" command. The pytest report of the assert failure is sufficient.
• we also typically dont include a comment line at the beginning of the test when the test function's name is sufficient. If the test involves soemthing special or unexpected, then a couple line doc_string (or comment) is used. We aren't building docs for the tests.
• instead of building a sequential version of the code inside nx-parallel, does it make sense to just "fall back" to the NetworkX version?