Hi Christophe,

Looks like a good patch to me - would you be able to submit it to JIRA?

I already submitted an issue to add primitive support for statically 
compiled functions (http://dev.clojure.org/jira/browse/CLJ-1263) which I 
think would complement yours nicely. The combination of the two should give 
float support that is comparable to Java in most cases.

On Tuesday, 17 September 2013 19:25:04 UTC+8, Christophe Grand wrote:
>
> Here is the mundane patch I described earlier: 
> https://github.com/cgrand/clojure/commit/4c202ad9757ce47ac9e669847c0e5bf68785e2d6
>
> It adds four functions (add-, multiply-, divide- and subtract-float), 
> backs them with their corresponding bytecodes and enhance the conversion 
> emitted when going from long/int to double/float.
>
> Please give it a try.
>
> It doesn't help with functions taking primitive but it's another problem.
>
> Christophe
>
> On Mon, Sep 16, 2013 at 7:03 PM, James Reeves 
> <ja...@booleanknot.com<javascript:>
> > wrote:
>
>>
>>
>>
>> On 16 September 2013 09:03, Mikera <mike.r.an...@gmail.com 
>> <javascript:>>wrote:
>>
>>>
>>> Obviously this is just a microbenchmark, but it fits my general 
>>> experience that floats are a reasonable bit faster than doubles, typically 
>>> 20-100% (doubles are closer when it is pure number crunching since 64-bit 
>>> CPUs are actually pretty good at doubles, floats have a bigger advantage 
>>> when you are manipulating a lot of data points and hence memory bandwidth 
>>> matters more)
>>>
>>> Code here for those interested:
>>> src/test/java/mikera/vectorz/performance/FloatVsDoubleBenchmark.java
>>>
>>
>> That's a pretty interesting result. I ran some tests of my own, based on 
>> your code, as I wondered whether or not the time to instantiate the array 
>> of doubles was biasing the test. My goal was to see whether or not I'd get 
>> a similar result running an array of floats through a method that processed 
>> doubles. (See: https://gist.github.com/weavejester/6583367)
>>
>> It turns out that I get a similar result. Passing floats to a method that 
>> takes doubles slows things down by a similar amount, unless I've somehow 
>> botched up the test. Considering that converting between single and double 
>> precision should be pretty cheap on the CPU, I'm surprised at the 
>> difference.
>>
>> This somewhat changes my view on things. It doesn't affect me in 
>> practice, but I can see how someone might be frustrated by having to drop 
>> down to Java to achieve performance for floating point calculations.
>>  
>> - James
>>
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>
>
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