Role of D in Python and performance computing [was post on using go 1.5 and GC latency]

[Laeeth Isharc via Digitalmars-d-learn]

> . Of course systems like Numba change the Python performance 
> game, which undermines D's potential in the Python-verse, as it 
> does C and C++. Currently I am investigating 
> Python/Numba/Chapel as the way of doing performance computing. 
> Anyone who just uses Python/NumPy/SciPy is probably not doing 
> performance computing, NumPy is so slow (*).

Can you elaborate ?

> The issue here for me is that Chapel provides something that C, 
> C++, D, Rust, Numba, NumPy, cannot – Partitioned Global Address 
> Space (PGAS) programming. This directly attacks the 
> multicore/multiprocessor/cluster side of computing, but not the 
> GPGPU side, at least not per se.

What's the best reference to learn more about PGAS?

Thanks.


Laeeth.