You can force the literals by enclosing them in int32():
p = [int32(0) for i=1:20000]
result = [int32(0) for i=1:20000]
k = int32(0)
n = int32(2)
while k < int32(20000)
i = int32(0)
On Wednesday, January 15, 2014 12:04:23 AM UTC+1, Przemyslaw Szufel wrote:
>
> Simon,
> Thanks!
> I changed in Cython to
> def primes_list(int kmax):
> cdef int k, i
> cdef long long n
> cdef long long p[20000]
> and now I am getting 2.1 seconds - exactly the same time as Julia and Java
> with longs...
>
> Since the computational difference between 64bit longs and 32bit ints is
> soo high - is there any way to rewrite my toy example to force Julia to do
> 32 bit int calculations?
>
> All best,
> Przemyslaw Szufel
>
>
> On Tuesday, 14 January 2014 23:55:12 UTC+1, Simon Kornblith wrote:
>>
>> In C long is only guaranteed to be at least 32 bits (IIRC it's 64 bits
>> on 64-bit *nix but 32-bit on 64-bit Windows). long long is guaranteed to
>> be at least 64 bits (and is 64 bits on all systems I know of).
>>
>> Simon
>>
>> On Tuesday, January 14, 2014 5:46:04 PM UTC-5, Przemyslaw Szufel wrote:
>>>
>>> Simon,
>>> Thanks for the explanation!
>>> In Java int is 32 bit as well.
>>> I have just replaced ints with longs in Java and found out that now I
>>> get the Java speed also very similar to Julia.
>>>
>>> However I tried in Cython:
>>> def primes_list(int kmax):
>>> cdef int k, i
>>> cdef long n
>>> cdef long p[20000]
>>> ...
>>>
>>> and surprisingly the speed did not change...at first I thought that
>>> maybe something did not compile or is in cache - but I made sure - it's not
>>> the cache.
>>> Cython speed remains unchanged regardles using int or long?
>>> I know that now it becomes other language question...but maybe someone
>>> can explain?
>>>
>>> All best,
>>> Przemyslaw Szufel
>>>
>>>
>>> On Tuesday, 14 January 2014 23:29:40 UTC+1, Simon Kornblith wrote:
>>>>
>>>> With a 64-bit build, Julia integers are 64-bit unless otherwise
>>>> specified. In C, you use ints, which are 32-bit. Changing them to long
>>>> long
>>>> makes the C code perform similarly to the Julia code on my system.
>>>> Unfortunately, it's hard to operate on 32-bit integers in Julia, since +
>>>> promotes to 64-bit by default (am I missing something)?
>>>>
>>>> Simon
>>>>
>>>> On Tuesday, January 14, 2014 4:32:16 PM UTC-5, Przemyslaw Szufel wrote:
>>>>>
>>>>> Dear Julia users,
>>>>>
>>>>> I am considering using Julia for computational projects.
>>>>> As a first to get a feeling of the new language a I tried to benchmark
>>>>> Julia speed against other popular languages.
>>>>> I used an example code from the Cython tutorial:
>>>>> http://docs.cython.org/src/tutorial/cython_tutorial.html [ the code
>>>>> for finding n first prime numbers].
>>>>>
>>>>> Rewriting the code in different languages and measuring the times on
>>>>> my Windows laptop gave me the following results:
>>>>>
>>>>> Language | Time in seconds (less=better)
>>>>>
>>>>> Python: 65.5
>>>>> Cython (with MinGW): 0.82
>>>>> Java : 0.64
>>>>> Java (with -server option) : 0.64
>>>>> C (with MinGW): 0.64
>>>>> Julia (0.2): 2.1
>>>>> Julia (0.3 nightly build): 2.1
>>>>>
>>>>> All the codes for my experiments are attached to this post (Cython i
>>>>> Python are both being run starting from the prim.py file)
>>>>>
>>>>> The thing that worries me is that Julia takes much much longer than
>>>>> Cython ,,,
>>>>> I am a beginner to Julia and would like to kindly ask what am I doing
>>>>> wrong with my code.
>>>>> I start Julia console and use the command include ("prime.jl") to
>>>>> execute it.
>>>>>
>>>>> This code looks very simple and I think the compiler should be able to
>>>>> optimise it to at least the speed of Cython?
>>>>> Maybe I my code has been written in non-Julia style way and the
>>>>> compiler has problems with it?
>>>>>
>>>>> I will be grateful for any answers or comments.
>>>>>
>>>>> Best regards,
>>>>> Przemyslaw Szufel
>>>>>
>>>>
