Nathan Tippy wrote them. I just ran the setup.sh script after installing 
OpenJDK 7 on the Ubuntu machine. I'm not sure how much tweaking is reasonable 
to allow for Java. For example, it's unreasonable to build a custom NumPy that 
uses a better BLAS – because most people just won't do that. It's the 
responsibility of each system to have good defaults.

> On Mar 30, 2014, at 3:15 PM, Jake Bolewski <[email protected]> wrote:
> 
> How are you running the benchmarks?  These types of micro-benchmarks in Java 
> are really difficult to get right.
> 
>> On Sunday, March 30, 2014 1:25:15 PM UTC-4, Stefan Karpinski wrote:
>> Ok, the Java mandel benchmark code cheats by manually inlining and strength 
>> reducing all the operations on complex numbers. This benchmark needs to use 
>> a complex number type like everyone else.
>> 
>> 
>>> On Sun, Mar 30, 2014 at 1:18 PM, Stefan Karpinski <[email protected]> 
>>> wrote:
>>> Ok, this may be more interesting than I thought, but not in a good way for 
>>> Java. Here are some preliminary results after getting this to run on our 
>>> benchmark machine:
>>> 
>>> benchmark   C        Java   relative
>>> 1   fib      0.07081        2.792345         39.43433130913713
>>> 2    parse_int      0.231028         4.104516       17.766314039856642
>>> 3    mandel 0.416994         0.272333       0.6530861355319262
>>> 4    quicksort      0.600815         1.850908       3.080662100646622
>>> 5    pi_sum 55.112839        55.533128      1.0076259725977825
>>> 6    rand_mat_stat  16.684055        63.864488      3.827875657326711
>>> 7    rand_mat_mul   106.070995       614.264555     5.791069981006589
>>> 8    printfd        27.725935        145.029354     5.230819231163891
>>> 
>>> Those are some rough numbers for Java. It's getting clobbered by C, 
>>> Fortran, Julia, Go, JavaScript and sometimes even Python. Brutal. We 
>>> definitely need some Java pros to take a look at the code and make sure 
>>> it's a fair comparison. The mandel result is also suspicious because it 
>>> doesn't seem reasonable that Java can be beating C and Fortran by that much.
>>> 
>>> 
>>>> On Sun, Mar 30, 2014 at 11:43 AM, Stefan Karpinski <[email protected]> 
>>>> wrote:
>>>> I merged the Java benchmarks, but couldn't get them to run: 
>>>> https://github.com/JuliaLang/julia/issues/6317. If anyone is a Java pro 
>>>> and wants to take a crack at this, that would be most appreciated.
>>>> 
>>>> 
>>>>> On Sun, Mar 30, 2014 at 11:10 AM, Isaiah Norton <[email protected]> 
>>>>> wrote:
>>>>> No. http://docs.julialang.org/en/latest/manual/performance-tips/
>>>>> 
>>>>> 
>>>>>> On Sun, Mar 30, 2014 at 11:06 AM, Freddy Chua <[email protected]> wrote:
>>>>>> I did some simple benchmark on for loop
>>>>>> 
>>>>>> a=0
>>>>>> for i=1:1000000000
>>>>>>  a+=1
>>>>>> end
>>>>>> 
>>>>>> The C equivalent runs way faster... does that mean julia is slow on 
>>>>>> loops ?
>>>>>> 
>>>>>>> On Sunday, March 30, 2014 10:06:20 PM UTC+8, Isaiah wrote:
>>>>>>> https://github.com/JuliaLang/julia/tree/master/test/perf
>>>>>>> 
>>>>>>> >  I also wonder why no tests were done with Java..
>>>>>>> 
>>>>>>> There is an open PR for Java, which you could check out and try:
>>>>>>> 
>>>>>>> https://github.com/JuliaLang/julia/pull/5260
>>>>>>> 
>>>>>>> 
>>>>>>> 
>>>>>>>> On Sun, Mar 30, 2014 at 9:55 AM, Freddy Chua <[email protected]> wrote:
>>>>>>>> Hi, 
>>>>>>>> 
>>>>>>>> I wonder where can I download the source code of these benchmarks, I 
>>>>>>>> want to try it on my own... I also wonder why no tests were done with 
>>>>>>>> Java..
>>>>>>>> 
>>>>>>>> 
>>>>>>>> Fortran         Julia  Python  R        Matlab Octave  Mathe-matica    
>>>>>>>>  JavaScript     Go
>>>>>>>> gcc 4.8.1      0.2     2.7.3   3.0.2   R2012a   3.6.4  8.0     V8 
>>>>>>>> 3.7.12.22    go1
>>>>>>>> fib    0.26    0.91    30.37   411.36  1992.00 3211.81  64.46  2.18    
>>>>>>>> 1.03
>>>>>>>> parse_int       5.03   1.60    13.95   59.40    1463.16        7109.85 
>>>>>>>> 29.54   2.43     4.79
>>>>>>>> quicksort      1.11    1.14     31.98  524.29  101.84  1132.04  35.74  
>>>>>>>> 3.51    1.25
>>>>>>>> mandel  0.86   0.85    14.19   106.97   64.58  316.95  6.07    3.49    
>>>>>>>>  2.36
>>>>>>>> pi_sum 0.80    1.00     16.33  15.42   1.29    237.41   1.32   0.84    
>>>>>>>> 1.41
>>>>>>>> rand_mat_stat   0.64   1.66    13.52   10.84    6.61   14.98   4.52    
>>>>>>>> 3.28     8.12
>>>>>>>> rand_mat_mul   0.96    1.01     3.41   3.98    1.10    3.41     1.16   
>>>>>>>> 14.60   8.51
>> 

Reply via email to