(set! *unchecked-math* true)
(defn g ^double [^double x] (+ (Math/sin (* 2.3 x)) (Math/cos (* 3.7 x))))
(time (loop [i 100000000 x 0.0] (if (pos? i) (recur (dec i) (g x)) x)))
This is nearly 50% faster than the original version on my machine. Note
that x is bound to 0.0 in the loop, which allows the optimized g to be
invoked.
On Wed, Feb 5, 2014 at 4:41 PM, Glen Fraser <holag...@gmail.com> wrote:
> 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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