Thanks to both of you for these suggestions, they're good to know. In my
specific case, setting the *unchecked-math* flag true did indeed speed things
up slightly (by about 6%). The other change, though, with the double type
hints (I assume that's what those are), actually ran notably slower (over 20%
slower!).
Glen.
On Feb 5, 2014, at 8:13 PM, David Nolen <dnolen.li...@gmail.com> wrote:
> Also:
>
> (defn g ^double [^double x] (+ (Math/sin (* 2.3 x)) (Math/cos (* 3.7 x))))
>
>
> On Wed, Feb 5, 2014 at 2:07 PM, Alex Miller <a...@puredanger.com> wrote:
> Others have answered with many useful bits but I would mention that it would
> possibly make a significant performance difference if you added this to your
> code:
>
> (set! *unchecked-math* true)
>
>
>
> On Wednesday, February 5, 2014 7:17:13 AM UTC-6, Glen Fraser wrote:
> (sorry if you received an earlier mail from me that was half-formed, I hit
> send by accident)
>
> Hi there, I'm quite new to Clojure, and was trying to do some very simple
> benchmarking with other languages. I was surprised by the floating-point
> results I got, which differed (for the same calculation, using doubles)
> compared to the other languages I tried (including C++, SuperCollider, Lua,
> Python).
>
> My benchmark iteratively runs a function 100M times: g(x) <-- sin(2.3x) +
> cos(3.7x), starting with x of 0.
>
> In the other languages, I always got the result 0.0541718..., but in Clojure
> I get 0.24788989.... I realize this is a contrived case, but -- doing an
> identical sequence of 64-bit floating-point operations on the same machine
> should give the same answer. Note that if you only run the function for
> about ~110 iterations, you get the same answer in Clojure (or very close),
> but then it diverges.
>
> I assume my confusion is due to my ignorance of Clojure and/or Java's math
> library. I don't think I'm using 32-bit floats or the "BigDecimal" type (I
> even explicitly converted to double, but got the same results, and if I
> evaluate the type it tells me java.lang.Double, which seems right). Maybe
> Clojure's answer is "better", but I do find it strange that it's different.
> Can someone explain this to me?
>
> Here are some results:
>
> Clojure: ~23 seconds
> (defn g [x] (+ (Math/sin (* 2.3 x)) (Math/cos (* 3.7 x))))
> (loop [i 100000000 x 0] (if (pos? i) (recur (dec i) (g x)) x))
> ;; final x: 0.24788989279493556 (???)
>
> C++ (g++ -O2): ~4 seconds
> double g(double x) {
> return std::sin(2.3*x) + std::cos(3.7*x);
> }
> int main() {
> double x = 0;
> for (int i = 0; i < 100000000; ++i) {
> x = g(x);
> }
> std::cout << "final x: " << x << std::endl;
> return 0;
> }
> // final x: 0.0541718
>
> Lua: ~39 seconds
> g = function(x)
> return math.sin(2.3*x) + math.cos(3.7*x)
> end
>
> x = 0; for i = 1, 100000000 do x = g(x) end
> -- Final x: 0.054171801051906
>
> Python: ~72 seconds
> def g(x):
> return math.sin(2.3*x) + math.cos(3.7*x)
>
> x = 0
> for i in xrange(100000000):
> x = g(x)
>
> # Final x: 0.05417180105190572
>
> SClang: ~26 seconds
> g = { |x| sin(2.3*x) + cos(3.7*x) };
> f = { |x| 100000000.do{ x = g.(x) }; x};
> bench{ f.(0).postln };
> // final x: 0.054171801051906 (same as C++, Lua, Python; different from
> Clojure)
>
> Thanks,
> Glen.
>
>
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