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> wrote:

>
>
>
> On 16 September 2013 09:03, Mikera <mike.r.anderson...@gmail.com> 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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