On Thu, 2011-03-03 at 09:40 -0500, David Simcha wrote:
> Forgot to mention, though: The more idiomatic/shorter way to write
> something like this would be to perform a reduction on a
> (non-parallel, lazy, random access) std.parallelism.Map. The map
> function will be evaluated in parallel naturally, as the parallel
> reduction is performed. Maybe this should be an example in the docs
> for reduce. In your pi example:
>
> // Nested function inside main().
> double calculateTerm(int i) {
> immutable x = (i - 0.5) * delta ;
> return 1.0 / (1.0 + x * x);
> }
>
> immutable sum = taskPool.reduce!"a + b"(
> std.algorithm.map!calculateTerm(iota(n))
> );(The above is a slight oversimplification of the situation I have but . . . ) Sadly this doesn't seem to work. I tried: immutable pi = 4.0 * taskPool.reduce ! ( "a + b" ) ( 0.0 , taskPool.map ! ( partialSum ) ( inputData ) ) * delta ; and this works fine showing good scaling. However: immutable pi = 4.0 * taskPool.reduce ! ( "a + b" ) ( 0.0 , map ! ( partialSum ) ( inputData ) ) * delta ; forces serialization so no speed up. -- Russel. ============================================================================= Dr Russel Winder t: +44 20 7585 2200 voip: sip:[email protected] 41 Buckmaster Road m: +44 7770 465 077 xmpp: [email protected] London SW11 1EN, UK w: www.russel.org.uk skype: russel_winder
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