[julia-users] Re: Julia vs C++-11 for random walks

[Frank Kampas]

Microsoft C code is not very fast these days.  You might want to compare 
with MinGW.

On Monday, January 5, 2015 9:56:07 AM UTC-5, lapeyre@gmail.com wrote:
>
> Hi, here is a comparison of Julia and C++ for simulating a random walk 
> .
>
> It is the first Julia program I wrote. I just pushed it to github.
>
> --John
>
>

Re: [julia-users] Re: Julia vs C++-11 for random walks

[lapeyre . math122a]

Ok. It's done.  Just to be sure I understood what I read on a github forum; 
there is no way for me to attach a label to the PR. So the labels are 
always added by someone else ?

--John

On Monday, January 5, 2015 9:25:18 PM UTC+1, Viral Shah wrote:
>
> Thanks. Do create a PR. 
>
> -viral 
>
>
>
> > On 06-Jan-2015, at 1:53 am, lapeyre@gmail.com  wrote: 
> > 
> > I meant randbool() in v0.3, where it was a more direct call, not 
> randbool() in v0.4. 
> > Anyway, I just found the problem and patched it. Adding one '@inline' 
> now makes rand(Bool) in v0.4 
> > about as fast as randbool() in v0.3. 
> > 
> > Should I open an issue (bug report), or just make a PR ? 
> > 
> > On Monday, January 5, 2015 8:59:02 PM UTC+1, Viral Shah wrote: 
> > I doubt that rand(Bool) is any slower, since randbool() calls 
> rand(Bool). It is worth filing this as a performance regression. 
> > 
> > -viral 
> > 
> > On Monday, January 5, 2015 9:41:45 PM UTC+5:30, lapeyre@gmail.com 
> wrote: 
> >  It may be in part the implementation of the RNG. I think it is also in 
> part whether the abstraction is optimized away. 
> > Notice that Julia v0.3 is faster than v0.4. This is probably randbool() 
> vs. rand(Bool). 
> > 
> > On Monday, January 5, 2015 4:50:56 PM UTC+1, Isaiah wrote: 
> > Very neat. Just in case this gets posted to the interwebz, it is worth 
> pointing out that the performance advantage for Julia can probably be 
> explained by differences in the underlying RNG. We use dsFMT, which is 
> known to be one of (if not the?) fastest MT libraries around. I could not 
> find any published comparisons in a quick google, but based on this test 
> harness [1], dsFMT may be significantly faster than std::mt19937: 
> > 
> > ``` 
> > ihnorton@julia:~/tmp/cpp-random-test$ ./random-real 
> > C++11 : 2.34846 
> > Boost : 0.371674 
> > dSFMT : 0.281255 
> > GSL   : 0.649981 
> > ``` 
> > 
> > [1] https://github.com/yomichi/cpp-random-test 
> > 
> > 
> > On Mon, Jan 5, 2015 at 10:12 AM,  wrote: 
> > Oh, and, (I forgot to mention!)  the Julia code runs much faster. 
> > 
> > 
> > On Monday, January 5, 2015 3:56:07 PM UTC+1, lapeyre@gmail.com 
> wrote: 
> > Hi, here is a comparison of Julia and C++ for simulating a random walk. 
> > 
> > It is the first Julia program I wrote. I just pushed it to github. 
> > 
> > --John 
> > 
> > 
>
>

Re: [julia-users] Re: Julia vs C++-11 for random walks

[Viral Shah]

Thanks. Do create a PR.

-viral



> On 06-Jan-2015, at 1:53 am, lapeyre.math1...@gmail.com wrote:
> 
> I meant randbool() in v0.3, where it was a more direct call, not randbool() 
> in v0.4.
> Anyway, I just found the problem and patched it. Adding one '@inline' now 
> makes rand(Bool) in v0.4
> about as fast as randbool() in v0.3.
> 
> Should I open an issue (bug report), or just make a PR ? 
> 
> On Monday, January 5, 2015 8:59:02 PM UTC+1, Viral Shah wrote:
> I doubt that rand(Bool) is any slower, since randbool() calls rand(Bool). It 
> is worth filing this as a performance regression.
> 
> -viral
> 
> On Monday, January 5, 2015 9:41:45 PM UTC+5:30, lapeyre@gmail.com wrote:
>  It may be in part the implementation of the RNG. I think it is also in part 
> whether the abstraction is optimized away.
> Notice that Julia v0.3 is faster than v0.4. This is probably randbool() vs. 
> rand(Bool).
> 
> On Monday, January 5, 2015 4:50:56 PM UTC+1, Isaiah wrote:
> Very neat. Just in case this gets posted to the interwebz, it is worth 
> pointing out that the performance advantage for Julia can probably be 
> explained by differences in the underlying RNG. We use dsFMT, which is known 
> to be one of (if not the?) fastest MT libraries around. I could not find any 
> published comparisons in a quick google, but based on this test harness [1], 
> dsFMT may be significantly faster than std::mt19937:
> 
> ```
> ihnorton@julia:~/tmp/cpp-random-test$ ./random-real
> C++11 : 2.34846
> Boost : 0.371674
> dSFMT : 0.281255
> GSL   : 0.649981
> ```
> 
> [1] https://github.com/yomichi/cpp-random-test
> 
> 
> On Mon, Jan 5, 2015 at 10:12 AM,  wrote:
> Oh, and, (I forgot to mention!)  the Julia code runs much faster.
> 
> 
> On Monday, January 5, 2015 3:56:07 PM UTC+1, lapeyre@gmail.com wrote:
> Hi, here is a comparison of Julia and C++ for simulating a random walk.
> 
> It is the first Julia program I wrote. I just pushed it to github.
> 
> --John
> 
> 

Re: [julia-users] Re: Julia vs C++-11 for random walks

[lapeyre . math122a]

I meant randbool() in v0.3, where it was a more direct call, not randbool() 
in v0.4.
Anyway, I just found the problem and patched it. Adding one '@inline' now 
makes rand(Bool) in v0.4
about as fast as randbool() in v0.3.

Should I open an issue (bug report), or just make a PR ? 

On Monday, January 5, 2015 8:59:02 PM UTC+1, Viral Shah wrote:
>
> I doubt that rand(Bool) is any slower, since randbool() calls rand(Bool). 
> It is worth filing this as a performance regression.
>
> -viral
>
> On Monday, January 5, 2015 9:41:45 PM UTC+5:30, lapeyre@gmail.com 
> wrote:
>>
>>  It may be in part the implementation of the RNG. I think it is also in 
>> part whether the abstraction is optimized away.
>> Notice that Julia v0.3 is faster than v0.4. This is probably randbool() 
>> vs. rand(Bool).
>>
>> On Monday, January 5, 2015 4:50:56 PM UTC+1, Isaiah wrote:
>>>
>>> Very neat. Just in case this gets posted to the interwebz, it is worth 
>>> pointing out that the performance advantage for Julia can probably be 
>>> explained by differences in the underlying RNG. We use dsFMT, which is 
>>> known to be one of (if not the?) fastest MT libraries around. I could not 
>>> find any published comparisons in a quick google, but based on this test 
>>> harness [1], dsFMT may be significantly faster than std::mt19937:
>>>
>>> ```
>>> ihnorton@julia:~/tmp/cpp-random-test$ ./random-real
>>> C++11 : 2.34846
>>> Boost : 0.371674
>>> dSFMT : 0.281255
>>> GSL   : 0.649981
>>> ```
>>>
>>> [1] https://github.com/yomichi/cpp-random-test
>>>
>>>
>>> On Mon, Jan 5, 2015 at 10:12 AM,  wrote:
>>>
 Oh, and, (I forgot to mention!)  the Julia code runs much faster.


 On Monday, January 5, 2015 3:56:07 PM UTC+1, lapeyre@gmail.com 
 wrote:
>
> Hi, here is a comparison of Julia and C++ for simulating a random walk 
> .
>
> It is the first Julia program I wrote. I just pushed it to github.
>
> --John
>
>
>>>

Re: [julia-users] Re: Julia vs C++-11 for random walks

[Viral Shah]

I doubt that rand(Bool) is any slower, since randbool() calls rand(Bool). 
It is worth filing this as a performance regression.

-viral

On Monday, January 5, 2015 9:41:45 PM UTC+5:30, lapeyre@gmail.com wrote:
>
>  It may be in part the implementation of the RNG. I think it is also in 
> part whether the abstraction is optimized away.
> Notice that Julia v0.3 is faster than v0.4. This is probably randbool() 
> vs. rand(Bool).
>
> On Monday, January 5, 2015 4:50:56 PM UTC+1, Isaiah wrote:
>>
>> Very neat. Just in case this gets posted to the interwebz, it is worth 
>> pointing out that the performance advantage for Julia can probably be 
>> explained by differences in the underlying RNG. We use dsFMT, which is 
>> known to be one of (if not the?) fastest MT libraries around. I could not 
>> find any published comparisons in a quick google, but based on this test 
>> harness [1], dsFMT may be significantly faster than std::mt19937:
>>
>> ```
>> ihnorton@julia:~/tmp/cpp-random-test$ ./random-real
>> C++11 : 2.34846
>> Boost : 0.371674
>> dSFMT : 0.281255
>> GSL   : 0.649981
>> ```
>>
>> [1] https://github.com/yomichi/cpp-random-test
>>
>>
>> On Mon, Jan 5, 2015 at 10:12 AM,  wrote:
>>
>>> Oh, and, (I forgot to mention!)  the Julia code runs much faster.
>>>
>>>
>>> On Monday, January 5, 2015 3:56:07 PM UTC+1, lapeyre@gmail.com 
>>> wrote:

 Hi, here is a comparison of Julia and C++ for simulating a random walk 
 .

 It is the first Julia program I wrote. I just pushed it to github.

 --John


>>

Re: [julia-users] Re: Julia vs C++-11 for random walks

[lapeyre . math122a]

 It may be in part the implementation of the RNG. I think it is also in 
part whether the abstraction is optimized away.
Notice that Julia v0.3 is faster than v0.4. This is probably randbool() vs. 
rand(Bool).

On Monday, January 5, 2015 4:50:56 PM UTC+1, Isaiah wrote:
>
> Very neat. Just in case this gets posted to the interwebz, it is worth 
> pointing out that the performance advantage for Julia can probably be 
> explained by differences in the underlying RNG. We use dsFMT, which is 
> known to be one of (if not the?) fastest MT libraries around. I could not 
> find any published comparisons in a quick google, but based on this test 
> harness [1], dsFMT may be significantly faster than std::mt19937:
>
> ```
> ihnorton@julia:~/tmp/cpp-random-test$ ./random-real
> C++11 : 2.34846
> Boost : 0.371674
> dSFMT : 0.281255
> GSL   : 0.649981
> ```
>
> [1] https://github.com/yomichi/cpp-random-test
>
>
> On Mon, Jan 5, 2015 at 10:12 AM, > 
> wrote:
>
>> Oh, and, (I forgot to mention!)  the Julia code runs much faster.
>>
>>
>> On Monday, January 5, 2015 3:56:07 PM UTC+1, lapeyre@gmail.com wrote:
>>>
>>> Hi, here is a comparison of Julia and C++ for simulating a random walk 
>>> .
>>>
>>> It is the first Julia program I wrote. I just pushed it to github.
>>>
>>> --John
>>>
>>>
>

Re: [julia-users] Re: Julia vs C++-11 for random walks

[Isaiah Norton]

Very neat. Just in case this gets posted to the interwebz, it is worth
pointing out that the performance advantage for Julia can probably be
explained by differences in the underlying RNG. We use dsFMT, which is
known to be one of (if not the?) fastest MT libraries around. I could not
find any published comparisons in a quick google, but based on this test
harness [1], dsFMT may be significantly faster than std::mt19937:

```
ihnorton@julia:~/tmp/cpp-random-test$ ./random-real
C++11 : 2.34846
Boost : 0.371674
dSFMT : 0.281255
GSL   : 0.649981
```

[1] https://github.com/yomichi/cpp-random-test


On Mon, Jan 5, 2015 at 10:12 AM,  wrote:

> Oh, and, (I forgot to mention!)  the Julia code runs much faster.
>
>
> On Monday, January 5, 2015 3:56:07 PM UTC+1, lapeyre@gmail.com wrote:
>>
>> Hi, here is a comparison of Julia and C++ for simulating a random walk
>> .
>>
>> It is the first Julia program I wrote. I just pushed it to github.
>>
>> --John
>>
>>

[julia-users] Re: Julia vs C++-11 for random walks

[lapeyre . math122a]

Oh, and, (I forgot to mention!)  the Julia code runs much faster.

On Monday, January 5, 2015 3:56:07 PM UTC+1, lapeyre@gmail.com wrote:
>
> Hi, here is a comparison of Julia and C++ for simulating a random walk 
> .
>
> It is the first Julia program I wrote. I just pushed it to github.
>
> --John
>
>