![]() |
Re: OPR-computation-related linear algebra problem
Sorry I'm a bit late to the party.
I'm running Octave 3.2.4, so an older version than flameout Hardware is Dell E6420 laptop (CPU i7-2640M @ 2.8GHz) Win 7 64bit Code:
octave:2> N = load('N.dat'); |
Re: OPR-computation-related linear algebra problem
Quote:
Interestingly, the Pascal and C++ compilers I used are essentially identical. Only the front ends are different (for the different languages). Is it possible that the difference in timing is due to the differences in the memory access due to the data structures we used? |
Re: OPR-computation-related linear algebra problem
Quote:
What machine & OS was used? |
Re: OPR-computation-related linear algebra problem
Quote:
|
Re: OPR-computation-related linear algebra problem
1 Attachment(s)
Quote:
Quote:
For comparison, I compiled your code using Free Pascal and the Cholesky decomposition ran in 11.9 seconds on my computer. |
Re: OPR-computation-related linear algebra problem
I haven't used Pascal in a long time, but seem to remember it storing 2D arrays with different elements adjacent. It was column-major and C was row-major. The notation isn't important, but accessing adjacent elements in the cache will be far faster than jumping by 20Kb to pickup up the next element.
Greg McKaskle |
Re: OPR-computation-related linear algebra problem
I don't have direct access to my desktop at the moment, I was doing that remotely with Logmein however for some reason I lost the connection and have not got it back yet.
I tried it on a GTX555M with only 24 cuda cores. It was 50% slower than my laptop processor(Core i7 2670QM quad core running at 2.2GHz) I will post here as soon as I get to my desktop. I was able to get 0.015 seconds using sparse matrices, however GPU processing does not support sparse matrices directly. I doubt that I can get any faster results than that. Quote:
|
Re: OPR-computation-related linear algebra problem
Quote:
Linux, Windows XP/7, 32 or 64 ? |
Re: OPR-computation-related linear algebra problem
Matlab 2012b
here are the results Normal Matrices(CPU and GPU(555M)) Using inv(N)*d: CPU 1.874s GPU 2.146s using N\d: CPU 0.175s GPU 0.507s Sparse Matrices(Only CPU) Using inv(N)*d: CPU 0.967s using N\d: CPU 0.015s Cannot get sparse matrices into the GPU easily. The times are only for the solve operation. Quote:
|
Re: OPR-computation-related linear algebra problem
Quote:
Code:
#define ELEMENT(M, i,j) (M[(i)*((i)+1)/2+(j)]) |
Re: OPR-computation-related linear algebra problem
Just installed Octave3.6.4_gcc4.6.2_20130408 on this computer. Results: GNU Octave, version 3.6.4 Anybody know why Octave takes so long to load N ? Load N times, all on the same computer: Delphi....0.6 seconds |
Re: OPR-computation-related linear algebra problem
LV times were on this computer
Win 7 Professional 64-bit Xeon CPU E5-1620 3.6GHz 16G RAM Greg McKaskle |
Re: OPR-computation-related linear algebra problem
RLaB is not a contender for fastest speed, but it's definitely the tiniest linear algebra app out there. It weighs in at under 1.5MB. Makes a wonderful pop-up for that quick calculation, or for high-school students just learning linear algebra. Very easy to use... and free. Welcome to RLaB. New users type `help INTRO'The second solution method (x=solve(N,d,"S")) tells RLaB that the matrix is symmetric, so it uses LAPACK subroutine DSYTRF (Bunch-Kaufman diagonal pivoting) to solve, which cuts the time in half. |
Re: OPR-computation-related linear algebra problem
Quote:
Quote:
|
Re: OPR-computation-related linear algebra problem
Is anybody else running Octave on a machine with 32-bit-XP Pro? Are you having the same 30 second delay for Octave to load, and 90 seconds to load the 12MB N.dat file? |
| All times are GMT -5. The time now is 07:55. |
Powered by vBulletin® Version 3.6.4
Copyright ©2000 - 2017, Jelsoft Enterprises Ltd.
Copyright © Chief Delphi