Re: How to Declare a new pragma ?
On Monday, 22 December 2014 at 00:55:08 UTC, Mike Parker wrote: On 12/22/2014 9:21 AM, FrankLike wrote: Now ,x64 mainform always have the console window,and the entry is main. could you do it? Thank you. Since 64-bit DMD uses the Microsoft toolchain, you need to pass a parameter on the command line to the MS linker. Linker parameters are passed with -L parameter See [1] for information about the /SUBSYSTEM option, which is what you want in this case. Probably something like this: -L/SUBSYSTEM:WINDOWS,5.02 [1] http://msdn.microsoft.com/en-us/library/fcc1zstk.aspx Thank you. -L/ENTRY:mainCRTStartup it's ok
math.log() benchmark of first 1 billion int using std.parallelism
Hi everybody, I am a java developer and used C/C++ only for some home projects so I never mastered native programming. I am currently learning D and I find it fascinating. I was reading the documentation about std.parallelism and I wanted to experiment a bit with the example Find the logarithm of every number from 1 to 10_000_000 in parallel. So, first, I changed the limit to 1 billion and ran it. I was blown away by the performance, the program ran in: 4 secs, 670 ms and I used a workUnitSize of 200. I have an i7 4th generation processor with 8 cores. Then I was curios to try the same test in Java just to see how much slower will that be (at least that was what I expected). I used Java's ExecutorService with a pool of 8 cores and created 5_000_000 tasks, each task was calculating log() for 200 numbers. The whole program ran in 3 secs, 315 ms. Now, can anyone explain why this program ran faster in Java? I ran both programs multiple times and the results were always close to this execution times. Can the implementation of log() function be the reason for a slower execution time in D? I then decided to ran the same program in a single thread, a simple foreach/for loop. I tried it in C and Go also. This are the results: - D: 24 secs, 32 ms. - Java: 20 secs, 881 ms. - C: 21 secs - Go: 37 secs I run Arch Linux on my PC. I compiled D programs using dmd-2.066 and used no compile arguments (dmd prog.d). I used Oracle's Java 8 (tried 7 and 6, seems like with Java 6 the performance is a bit better then 7 and 8). To compile the C program I used: gcc 4.9.2 For Go program I used go 1.4 I really really like the built in support in D for parallel processing and how easy is to schedule tasks taking advantage of workUnitSize. Thanks, Iov
Re: math.log() benchmark of first 1 billion int using std.parallelism
On Monday, 22 December 2014 at 10:12:52 UTC, Iov Gherman wrote: Now, can anyone explain why this program ran faster in Java? I ran both programs multiple times and the results were always close to this execution times. Can the implementation of log() function be the reason for a slower execution time in D? I then decided to ran the same program in a single thread, a simple foreach/for loop. I tried it in C and Go also. This are the results: - D: 24 secs, 32 ms. - Java: 20 secs, 881 ms. - C: 21 secs - Go: 37 secs I run Arch Linux on my PC. I compiled D programs using dmd-2.066 and used no compile arguments (dmd prog.d). I used Oracle's Java 8 (tried 7 and 6, seems like with Java 6 the performance is a bit better then 7 and 8). To compile the C program I used: gcc 4.9.2 For Go program I used go 1.4 I really really like the built in support in D for parallel processing and how easy is to schedule tasks taking advantage of workUnitSize. Thanks, Iov DMD is generally going to produce the slowest code. LDC and GDC will normally do better.
Re: math.log() benchmark of first 1 billion int using std.parallelism
I run Arch Linux on my PC. I compiled D programs using dmd-2.066 and used no compile arguments (dmd prog.d) You should try use some arguments -O -release -inline -noboundscheck and maybe try use gdc or ldc should help with performance can you post your code in all languages somewhere? I like to try it on my machine :)
Re: math.log() benchmark of first 1 billion int using std.parallelism
On Monday, 22 December 2014 at 10:35:52 UTC, Daniel Kozak via Digitalmars-d-learn wrote: I run Arch Linux on my PC. I compiled D programs using dmd-2.066 and used no compile arguments (dmd prog.d) You should try use some arguments -O -release -inline -noboundscheck and maybe try use gdc or ldc should help with performance can you post your code in all languages somewhere? I like to try it on my machine :) Btw. try use C log function, maybe it would be faster: import core.stdc.math;
Re: ini library in OSX
On Saturday, 20 December 2014 at 08:09:06 UTC, Joel wrote: On Monday, 13 October 2014 at 16:06:42 UTC, Robert burner Schadek wrote: On Saturday, 11 October 2014 at 22:38:20 UTC, Joel wrote: On Thursday, 11 September 2014 at 10:49:48 UTC, Robert burner Schadek wrote: some self promo: http://code.dlang.org/packages/inifiled I would like an example? go to the link and scroll down a page How do you use it with current ini files ([label] key=name)? I think I don't follow? readINIFile(CONFIG_STRUCT, filename.ini); ?
Re: math.log() benchmark of first 1 billion int using std.parallelism
On Mon, 2014-12-22 at 10:12 +, Iov Gherman via Digitalmars-d-learn wrote: […] - D: 24 secs, 32 ms. - Java: 20 secs, 881 ms. - C: 21 secs - Go: 37 secs Without the source codes and the commands used to create and run, it is impossible to offer constructive criticism of the results. However a priori the above does not surprise me. I'll wager ldc2 or gdc will beat dmd for CPU-bound code, so as others have said for benchmarking use ldc2 or gdc with all optimization on (-O3). If you used gc for Go then switch to gccgo (again with -O3) and see a huge performance improvement on CPU-bound code. Java beating C and C++ is fairly normal these days due to the tricks you can play with JIT over AOT optimization. Once Java has proper support for GPGPU, it will be hard for native code languages to get any new converts from JVM. Put the source up and I and others will try things out. -- Russel. = Dr Russel Winder t: +44 20 7585 2200 voip: sip:russel.win...@ekiga.net 41 Buckmaster Roadm: +44 7770 465 077 xmpp: rus...@winder.org.uk London SW11 1EN, UK w: www.russel.org.uk skype: russel_winder
Re: math.log() benchmark of first 1 billion int using std.parallelism
On Monday, 22 December 2014 at 11:11:07 UTC, aldanor wrote:
Just tried it out myself (E5 Xeon / Linux):
D version: 19.64 sec (avg 3 runs)
import core.stdc.math;
void main() {
double s = 0;
foreach (i; 1 .. 1_000_000_000)
s += log(i);
}
// build flags: -O -release
C version: 19.80 sec (avg 3 runs)
#include math.h
int main() {
double s = 0;
long i;
for (i = 1; i 10; i++)
s += log(i);
return 0;
}
// build flags: -O3 -lm
Replacing import core.stdc.math with import std.math in the D
example increases the avg runtime from 19.64 to 23.87 seconds
(~20% slower) which is consistent with OP's statement.
Re: math.log() benchmark of first 1 billion int using std.parallelism
On Monday, 22 December 2014 at 10:40:45 UTC, Daniel Kozak wrote:
On Monday, 22 December 2014 at 10:35:52 UTC, Daniel Kozak via
Digitalmars-d-learn wrote:
I run Arch Linux on my PC. I compiled D programs using
dmd-2.066 and used no compile arguments (dmd prog.d)
You should try use some arguments -O -release -inline
-noboundscheck
and maybe try use gdc or ldc should help with performance
can you post your code in all languages somewhere? I like to
try it on
my machine :)
Btw. try use C log function, maybe it would be faster:
import core.stdc.math;
Just tried it out myself (E5 Xeon / Linux):
D version: 19.64 sec (avg 3 runs)
import core.stdc.math;
void main() {
double s = 0;
foreach (i; 1 .. 1_000_000_000)
s += log(i);
}
// build flags: -O -release
C version: 19.80 sec (avg 3 runs)
#include math.h
int main() {
double s = 0;
long i;
for (i = 1; i 10; i++)
s += log(i);
return 0;
}
// build flags: -O3 -lm
Re: DUB build questions
On Saturday, 20 December 2014 at 08:36:15 UTC, Russel Winder via Digitalmars-d-learn wrote: On Sat, 2014-12-20 at 05:46 +, Dicebot via Digitalmars-d-learn wrote: On Saturday, 20 December 2014 at 04:15:00 UTC, Rikki Cattermole wrote: b) Can I do parallel builds with dub. CMake gives me Makefiles so I can make -j does dub have a similar option? No Worth noting that it is not actually a dub problem as much, it is simply not worth adding parallel builds because separate compilation is much much slower with existing D front-end implementation and even doing it in parallel is sub-optimal compared to dump-it-all-at-once. From previous rounds of this sort of question (for the SCons D tooling), the consensus of the community appeared to be that the only time separate module compilation was really useful was for mixed D, C, C++, Fortran systems. For pure D systems, single call of the compiler is deemed far better than traditional C, C++, Fortran compilation strategy. This means the whole make -j thing is not an issue, it just means that Dub is only really dealing with the all D situation. The corollary to this is that DMD, LDC and GDC really need to make use of all parallelism they can, which I suspect is more or less none. Chapel has also gone the compile all modules with a single compiler call strategy as this enables global optimization from source to executable. Thanks for the info everyone. I've used dub for just on two days now and I'm hooked! At first I was very unsure about giving up my Makefiles, being the build system control freak that I am, but it really shines at rapid development. As for out of source builds, it is a non-issue really. I like running the build outside the project tree but I can use gitignore and targetPath. For larger projects where we need to manage dependencies, generate code, run SWIG etc. I'd still use both SCons or CMake. Regarding parallel builds, make -j on CMake Makefiles and dub build feel about the same, and that's all I care about. I'm still not sure how dub would scale for large projects with 100s-1000s of source modules. DMD ran out of memory in the VM (1Gb) at around 70 modules but CMake works due to separate compilation of each module ... I think. However, I didn't investigate due to lack of time so I wouldn't score this against dub. I am sure it can do it if I take the time to figure it out properly. Cheers, uri
optimization / benchmark tips a good topic for wiki ?
Replacing import core.stdc.math with import std.math in the D example increases the avg runtime from 19.64 to 23.87 seconds (~20% slower) which is consistent with OP's statement. + GDC/LDC vs DMD + nobounds, release Do you think we should start a topic on D wiki front page for benchmarking/performance tips to organize peoples' experience of what works? I took a quick look and couldn't see anything already. And it seems to be a topic that comes up quite frequently (less on forum than people doing their own benchmarks and it getting picked up on reddit etc). I am not so experienced in this area otherwise I would write a first draft myself. Laeeth
Re: DUB build questions
On 23/12/2014 1:39 a.m., uri wrote: On Saturday, 20 December 2014 at 08:36:15 UTC, Russel Winder via Digitalmars-d-learn wrote: On Sat, 2014-12-20 at 05:46 +, Dicebot via Digitalmars-d-learn wrote: On Saturday, 20 December 2014 at 04:15:00 UTC, Rikki Cattermole wrote: b) Can I do parallel builds with dub. CMake gives me Makefiles so I can make -j does dub have a similar option? No Worth noting that it is not actually a dub problem as much, it is simply not worth adding parallel builds because separate compilation is much much slower with existing D front-end implementation and even doing it in parallel is sub-optimal compared to dump-it-all-at-once. From previous rounds of this sort of question (for the SCons D tooling), the consensus of the community appeared to be that the only time separate module compilation was really useful was for mixed D, C, C++, Fortran systems. For pure D systems, single call of the compiler is deemed far better than traditional C, C++, Fortran compilation strategy. This means the whole make -j thing is not an issue, it just means that Dub is only really dealing with the all D situation. The corollary to this is that DMD, LDC and GDC really need to make use of all parallelism they can, which I suspect is more or less none. Chapel has also gone the compile all modules with a single compiler call strategy as this enables global optimization from source to executable. Thanks for the info everyone. I've used dub for just on two days now and I'm hooked! At first I was very unsure about giving up my Makefiles, being the build system control freak that I am, but it really shines at rapid development. As for out of source builds, it is a non-issue really. I like running the build outside the project tree but I can use gitignore and targetPath. For larger projects where we need to manage dependencies, generate code, run SWIG etc. I'd still use both SCons or CMake. Regarding parallel builds, make -j on CMake Makefiles and dub build feel about the same, and that's all I care about. I'm still not sure how dub would scale for large projects with 100s-1000s of source modules. DMD ran out of memory in the VM (1Gb) at around 70 modules but CMake works due to separate compilation of each module ... I think. However, I didn't investigate due to lack of time so I wouldn't score this against dub. I am sure it can do it if I take the time to figure it out properly. Cheers, uri To build anything with dmd seriously you need about 2gb of ram available. Yes its a lot, but its fast. Also use subpackages. They are your friend.
Re: math.log() benchmark of first 1 billion int using std.parallelism
Hi Guys, First of all, thank you all for responding so quick, it is so nice to see D having such an active community. As I said in my first post, I used no other parameters to dmd when compiling because I don't know too much about dmd compilation flags. I can't wait to try the flags Daniel suggested with dmd (-O -release -inline -noboundscheck) and the other two compilers (ldc2 and gdc). Thank you guys for your suggestions. Meanwhile, I created a git repository on github and I put there all my code. If you find any errors please let me know. Because I am keeping the results in a big array the programs take approximately 8Gb of RAM. If you don't have enough RAM feel free to decrease the size of the array. For java code you will also need to change 'compile-run.bsh' and use the right memory parameters. Thank you all for helping, Iov
Re: math.log() benchmark of first 1 billion int using std.parallelism
On Monday, 22 December 2014 at 17:05:19 UTC, Iov Gherman wrote: Hi Guys, First of all, thank you all for responding so quick, it is so nice to see D having such an active community. As I said in my first post, I used no other parameters to dmd when compiling because I don't know too much about dmd compilation flags. I can't wait to try the flags Daniel suggested with dmd (-O -release -inline -noboundscheck) and the other two compilers (ldc2 and gdc). Thank you guys for your suggestions. Meanwhile, I created a git repository on github and I put there all my code. If you find any errors please let me know. Because I am keeping the results in a big array the programs take approximately 8Gb of RAM. If you don't have enough RAM feel free to decrease the size of the array. For java code you will also need to change 'compile-run.bsh' and use the right memory parameters. Thank you all for helping, Iov Link to your repo?
Re: math.log() benchmark of first 1 billion int using std.parallelism
On Monday, 22 December 2014 at 17:16:05 UTC, bachmeier wrote: On Monday, 22 December 2014 at 17:05:19 UTC, Iov Gherman wrote: Hi Guys, First of all, thank you all for responding so quick, it is so nice to see D having such an active community. As I said in my first post, I used no other parameters to dmd when compiling because I don't know too much about dmd compilation flags. I can't wait to try the flags Daniel suggested with dmd (-O -release -inline -noboundscheck) and the other two compilers (ldc2 and gdc). Thank you guys for your suggestions. Meanwhile, I created a git repository on github and I put there all my code. If you find any errors please let me know. Because I am keeping the results in a big array the programs take approximately 8Gb of RAM. If you don't have enough RAM feel free to decrease the size of the array. For java code you will also need to change 'compile-run.bsh' and use the right memory parameters. Thank you all for helping, Iov Link to your repo? Sorry, forgot about it: https://github.com/ghermaniov/benchmarks
Re: math.log() benchmark of first 1 billion int using std.parallelism
So, I did some more testing with the one processing in paralel: --- dmd: 4 secs, 977 ms --- dmd with flags: -O -release -inline -noboundscheck: 4 secs, 635 ms --- ldc: 6 secs, 271 ms --- gdc: 10 secs, 439 ms I also pushed the new bash scripts to the git repository.
Re: math.log() benchmark of first 1 billion int using std.parallelism
On Monday, 22 December 2014 at 17:28:12 UTC, Iov Gherman wrote: So, I did some more testing with the one processing in paralel: --- dmd: 4 secs, 977 ms --- dmd with flags: -O -release -inline -noboundscheck: 4 secs, 635 ms --- ldc: 6 secs, 271 ms --- gdc: 10 secs, 439 ms I also pushed the new bash scripts to the git repository. Flag suggestions: ldc2 -O3 -release -mcpu=native -singleobj gdc -O3 -frelease -march=native
Re: math.log() benchmark of first 1 billion int using std.parallelism
On Monday, 22 December 2014 at 17:28:12 UTC, Iov Gherman wrote: So, I did some more testing with the one processing in paralel: --- dmd: 4 secs, 977 ms --- dmd with flags: -O -release -inline -noboundscheck: 4 secs, 635 ms --- ldc: 6 secs, 271 ms --- gdc: 10 secs, 439 ms I also pushed the new bash scripts to the git repository. import std.math, std.stdio, std.datetime; -- try replacing std.math with core.stdc.math.
Re: Inheritance and in-contracts
https://github.com/D-Programming-Language/dmd/pull/4200
Re: math.log() benchmark of first 1 billion int using std.parallelism
On Monday, 22 December 2014 at 18:00:18 UTC, aldanor wrote: On Monday, 22 December 2014 at 17:28:12 UTC, Iov Gherman wrote: So, I did some more testing with the one processing in paralel: --- dmd: 4 secs, 977 ms --- dmd with flags: -O -release -inline -noboundscheck: 4 secs, 635 ms --- ldc: 6 secs, 271 ms --- gdc: 10 secs, 439 ms I also pushed the new bash scripts to the git repository. import std.math, std.stdio, std.datetime; -- try replacing std.math with core.stdc.math. Tried it, it is worst: 6 secs, 78 ms while the initial one was 4 secs, 977 ms and sometimes even better.
Re: math.log() benchmark of first 1 billion int using std.parallelism
On Monday, 22 December 2014 at 17:50:20 UTC, John Colvin wrote: On Monday, 22 December 2014 at 17:28:12 UTC, Iov Gherman wrote: So, I did some more testing with the one processing in paralel: --- dmd: 4 secs, 977 ms --- dmd with flags: -O -release -inline -noboundscheck: 4 secs, 635 ms --- ldc: 6 secs, 271 ms --- gdc: 10 secs, 439 ms I also pushed the new bash scripts to the git repository. Flag suggestions: ldc2 -O3 -release -mcpu=native -singleobj gdc -O3 -frelease -march=native Tried it, here are the results: --- ldc: 6 secs, 271 ms --- ldc -O3 -release -mcpu=native -singleobj: 5 secs, 686 ms --- gdc: 10 secs, 439 ms --- gdc -O3 -frelease -march=native: 9 secs, 180 ms
Re: Inheritance and in-contracts
On Monday, 22 December 2014 at 19:11:13 UTC, Ali Çehreli wrote: On 12/22/2014 10:06 AM, aldanor wrote: https://github.com/D-Programming-Language/dmd/pull/4200 Thank you! This fixes a big problem with the contracts in D. Ali It's not my PR but I just thought this thread would be happy to know :)
Re: Inheritance and in-contracts
On 12/22/2014 10:06 AM, aldanor wrote: https://github.com/D-Programming-Language/dmd/pull/4200 Thank you! This fixes a big problem with the contracts in D. Ali
Re: Inheritance and in-contracts
On 22/12/14 19:06, aldanor via Digitalmars-d-learn wrote: https://github.com/D-Programming-Language/dmd/pull/4200 Yes, I saw that PR with some joy -- thanks for the link! :-)
Re: math.log() benchmark of first 1 billion int using std.parallelism
On Monday, 22 December 2014 at 18:23:29 UTC, Iov Gherman wrote: On Monday, 22 December 2014 at 18:00:18 UTC, aldanor wrote: On Monday, 22 December 2014 at 17:28:12 UTC, Iov Gherman wrote: So, I did some more testing with the one processing in paralel: --- dmd: 4 secs, 977 ms --- dmd with flags: -O -release -inline -noboundscheck: 4 secs, 635 ms --- ldc: 6 secs, 271 ms --- gdc: 10 secs, 439 ms I also pushed the new bash scripts to the git repository. import std.math, std.stdio, std.datetime; -- try replacing std.math with core.stdc.math. Tried it, it is worst: 6 secs, 78 ms while the initial one was 4 secs, 977 ms and sometimes even better. Strange... for me, core.stdc.math.log is about twice as fast as std.math.log.
Re: Inheritance and in-contracts
On 22/12/14 20:12, aldanor via Digitalmars-d-learn wrote: On Monday, 22 December 2014 at 19:11:13 UTC, Ali Çehreli wrote: On 12/22/2014 10:06 AM, aldanor wrote: https://github.com/D-Programming-Language/dmd/pull/4200 Thank you! This fixes a big problem with the contracts in D. Ali It's not my PR but I just thought this thread would be happy to know :) Actually, the author is a friend of mine, and an all-round wonderful guy. :-)
Re: math.log() benchmark of first 1 billion int using std.parallelism
On Monday, 22 December 2014 at 18:27:48 UTC, Iov Gherman wrote: On Monday, 22 December 2014 at 17:50:20 UTC, John Colvin wrote: On Monday, 22 December 2014 at 17:28:12 UTC, Iov Gherman wrote: So, I did some more testing with the one processing in paralel: --- dmd: 4 secs, 977 ms --- dmd with flags: -O -release -inline -noboundscheck: 4 secs, 635 ms --- ldc: 6 secs, 271 ms --- gdc: 10 secs, 439 ms I also pushed the new bash scripts to the git repository. Flag suggestions: ldc2 -O3 -release -mcpu=native -singleobj gdc -O3 -frelease -march=native Tried it, here are the results: --- ldc: 6 secs, 271 ms --- ldc -O3 -release -mcpu=native -singleobj: 5 secs, 686 ms --- gdc: 10 secs, 439 ms --- gdc -O3 -frelease -march=native: 9 secs, 180 ms That's very different to my results. I see no important difference between ldc and dmd when using std.math, but when using core.stdc.math ldc halves its time where dmd only manages to get to ~80%
How to get the processid by exe's name in D?
Now,if you want to know whether a exe is in processes ,you must use the win API.Do you have any other idea?
Re: How to get the processid by exe's name in D?
The windows api is how I'd do it - look up how to do it in C, then do the same thing in D.
Re: math.log() benchmark of first 1 billion int using std.parallelism
That's very different to my results. I see no important difference between ldc and dmd when using std.math, but when using core.stdc.math ldc halves its time where dmd only manages to get to ~80% What CPU do you have? On my Intel Core i3 I have similar experience as Iov Gherman, but on my Amd FX4200 I have same results as you. Seems std.math.log is not good for my AMD CPU :)
Re: ini library in OSX
On Monday, 22 December 2014 at 11:04:10 UTC, Robert burner Schadek wrote: On Saturday, 20 December 2014 at 08:09:06 UTC, Joel wrote: On Monday, 13 October 2014 at 16:06:42 UTC, Robert burner Schadek wrote: On Saturday, 11 October 2014 at 22:38:20 UTC, Joel wrote: On Thursday, 11 September 2014 at 10:49:48 UTC, Robert burner Schadek wrote: some self promo: http://code.dlang.org/packages/inifiled I would like an example? go to the link and scroll down a page How do you use it with current ini files ([label] key=name)? I think I don't follow? readINIFile(CONFIG_STRUCT, filename.ini); ? I have a ini file that has price goods date etc for each item. I couldn't see how you could have (see below). It's got more than section, I don't know how to do that with your library. In this form: [section0] day=1 month=8 year=2013 item=Fish'n'Chips cost=3 shop=Take aways comment=Don't know the date [section1] day=1 month=8 year=2013 item=almond individually wrapped chocolates (for Cecily), through-ties cost=7 shop=Putaruru - Dairy (near Hotel 79) comment=Don't know the date or time. Also, what is CONFIG_STRUCT? - is that for using 'struct' instead of 'class'?
