2011/3/24 Dmitrey <tm...@ukr.net>:

> Are there any plans for merging bottleneck into numpy?

No plans, but no particular opposition. bottleneck is a good place to
experiment with these optimizations. When they settle, it might be
worth folding them back in.

> Also, are those benchmarks valid for ordinary numpy only or numpy with
> MKL/ACML or it doesn't matter?

Doesn't matter.

> If I have huge arrays and multicore CPU, will numpy with MKL/ACML or
> something else involve parallel computations with numpy funcs like amin,
> amax, argmin, nanargmin etc?

No. MKL/ACML focus on parallelizing expensive computation like
matrix-matrix multiplication, not things like finding the minimum
elements of an array.

-- 
Robert Kern

"I have come to believe that the whole world is an enigma, a harmless
enigma that is made terrible by our own mad attempt to interpret it as
though it had an underlying truth."
  -- Umberto Eco
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