+1 for Iain’s point of view. — John
On Jan 15, 2014, at 5:16 PM, Iain Dunning <iaindunn...@gmail.com> wrote: > From a philosophical POV alone, I think its inconsistent that we > a) Don't save people from overflows, but > b) Silently do Int32 math as Int64 behind the scenes to presumably save > themselves from themselves > > I think the overflow behaviour suprises some people, but only because they've > been trained on Python etc. instead of C, but the Int32 behaviour would > surprise pretty much everyone given how Julia normally acts (as the manual > says, its falls into the more "no automatic coversion" family of languages) > > On Wednesday, January 15, 2014 4:28:15 PM UTC-5, Földes László wrote: > Sorry for the wrong info, I was switching between a 32 bit and a 64 bit > machine (SSH terminal), and I just happened to run the script on the 32 bit > machine... > > On Wednesday, January 15, 2014 12:37:07 AM UTC+1, Przemyslaw Szufel wrote: > Foldes, > > I went for your solution and got a time increase from > 2.1 seconds (64bit integers) to 17.78 seconds (32 bit dow-casting). > Seems like casting is no cheap... > > Any other ideas possibilities? > > All best, > Przemyslaw > > P.S. > Naturally I realize that this is toy example and normally in a typical > production code we would rather use real numbers for computations not ints. > I am asking just out of curiosity ;-) > > > On Wednesday, 15 January 2014 00:25:20 UTC+1, Földes László wrote: > 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
