Thanks! Realized that a bit too late (Looked into the pmap source
code, but that's about it).
I've split my job decision roughly 1000 x 1000 - now I'm getting 8
times speedup, on 8 core machine:
(reduce +
(pmap
(fn [_]
(reduce +
(map (fn [_]
(+ (pnpoly np xp yp 0.5 0.5)
(pnpoly np xp yp 0.5 1.5)
(pnpoly np xp yp -0.5 1.5)
(pnpoly np xp yp 0.75 2.25)
(pnpoly np xp yp 0.0 2.01)
(pnpoly np xp yp -0.5 2.5)
(pnpoly np xp yp -1.0 -0.5)
(pnpoly np xp yp -1.5 0.5)
(pnpoly np xp yp -2.25 -1.0)
(pnpoly np xp yp 0.5 -0.25)
(pnpoly np xp yp 0.5 -1.25)
(pnpoly np xp yp -0.5 -2.5)))
(range 0 1000))))
(range 0 1000)))
Clojure is reasonable :)
Jeffrey Straszheim wrote:
> It is pretty common to get a slowdown when moving from map to pmap. It just
> means that the thread scheduling overhead is greater than the gain from
> parallelizing the code. The behavior might be very different w/ larger data
> sets, or w/ more CPU's. It is often best to leave parallelism as an option
> to the client of your library.
> Are you using the latest build? pmap now uses Java futures and they run in
> a cached thread pool. If so, try running the algorithm a few times and see
> if it speeds up as the thread pool winds up.
>
> On Fri, Mar 6, 2009 at 1:31 PM, Dimiter malkia Stanev <[email protected]>wrote:
>
> >
> > Hi guys, anyone has an insight into the problem I'm running into?
> >
> > On Mar 4, 2:27 am, "Dimiter \"malkia\" Stanev" <[email protected]>
> > wrote:
> > > Hi guys,
> > >
> > > In the example below, if map is replaced with pmap, it goes twice
> > > slower on my MBP (2 CPUs).
> > >
> > > I believe it's probably the (reduce + ...) causing it, but I can't
> > > explain it.
> > >
> > > Version with map:
> > > user> (time (pnpolytest))
> > > "Elapsed time: 3903.533 msecs"
> > > 6000000
> > >
> > > Version with pmap:
> > > user> (time (pnpolytest))
> > > "Elapsed time: 7995.565 msecs"
> > >
> > > What I'm doing wrong here?
> > >
> > > (defn- pnpoly [npol #^floats xp #^floats yp x y]
> > > (let [npol (int npol)
> > > x (float x)
> > > y (float y)]
> > > (loop [r (int 0)
> > > i (int 0)
> > > xi (aget xp (dec npol))
> > > yi (aget yp (dec npol))]
> > > (if (< i npol)
> > > (let [xj xi xi (aget xp i)
> > > yj yi yi (aget yp i)]
> > > (if (or (= (> yi y) (> yj y))
> > > (>= x (+ xi (/ (* (- xj xi)
> > > (- y yi))
> > > (- yj yi)))))
> > > (recur (bit-not r) (inc i) xi yi)
> > > (recur r (inc i) xi yi)))
> > > (- r)))))
> > >
> > > (defn pnpolytest []
> > > (let [xp
> > > (float-array
> > > [+0.0 +1.0 +1.0 +0.0 +0.0
> > > +1.0 -0.5 -1.0 -1.0 -2.0
> > > -2.5 -2.0 -1.5 -0.5 +1.0
> > > +1.0 +0.0 -0.5 -1.0 -0.5])
> > > yp
> > > (float-array
> > > [+0.0 +0.0 +1.0 +1.0 +2.0
> > > +3.0 +2.0 +3.0 0.0 -0.5
> > > -1.0 -1.5 -2.0 -2.0 -1.5
> > > -1.0 -0.5 -1.0 -1.0 -0.5])
> > > npol 20]
> > > (reduce +
> > > ;; Replace the nex map with pmap,
> > > ;; and things slow down
> > > (map (fn [_]
> > > (+ (pnpoly npol xp yp 0.5 0.5)
> > > (pnpoly npol xp yp 0.5 1.5)
> > > (pnpoly npol xp yp -0.5 1.5)
> > > (pnpoly npol xp yp 0.75 2.25)
> > > (pnpoly npol xp yp 0.0 2.01)
> > > (pnpoly npol xp yp -0.5 2.5)
> > > (pnpoly npol xp yp -1.0 -0.5)
> > > (pnpoly npol xp yp -1.5 0.5)
> > > (pnpoly npol xp yp -2.25 -1.0)
> > > (pnpoly npol xp yp 0.5 -0.25)
> > > (pnpoly npol xp yp 0.5 -1.25)
> > > (pnpoly npol xp yp -0.5 -2.5)))
> > > (range 0 1000000)))))
> > >
> > > Thanks,
> > > Dimiter "malkia" Stanev
> > >
> >
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