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Old 5th April 2009
Graaf_van_Vlaanderen Graaf_van_Vlaanderen is offline
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Default DragonFly BSD evaluation

I successfully installed DragonFly BSD on a Tyan S2892. There are however several issues:

1. The kernel only sees 3GB of the 4GB of memory. I think this is a typical i86 desease, which also exists in FreeBSD. I guess to solve this a kernel recompile is required...or the AMD64 version if it would be available in DragonFly BSD

2. The DragonFly BSD kernel apparently only sees one core of the total 4 CPU cores available: two dual core Operon 275 CPUs or the CPU load spreading is simply wrong.

Here is a test that proves this, by running a GNU Octave script (see below) that measures the calculation time.
In the first test I just ran one script, the second time the script was run two times at the same time.

Elapsed time for a 100X100 matrix:

Single run in FreeBSD (AMD64): 74s
Single run in DragonFlyBSD: 66s

Two concurrent runs in FreeBSD (AMD64): 74s for each run
Two concurrent runs in DragonFlyBSD: 132s for each run

FreeBSD is doing what you expect, spread the load, while DragonFlyBSD seems to put to different processes in one core.

Any thoughts?

clear all
% (5)
cumulate = 0; p = 0; vt = 0; vr = 0; vrt = 0; rvt = 0; RV = 0; j = 0; k = 0;
x2 = 0; R = 0; Rxx = 0; Ryy = 0; Rxy = 0; Ryx = 0; Rvmax = 0; f = 0;
for i = 1:runs
  x = abs(randn(100,100));
    % Calculation of Escoufier's equivalent vectors
    p = size(x, 2);
    vt = [1:p];                                % Variables to test
    vr = [];                                   % Result: ordered variables
    RV = [1:p];                                % Result: correlations
    for j = 1:p                                % loop on the variable number
      Rvmax = 0;
      for k = 1:(p-j+1)                        % loop on the variables
        if j == 1
          x2 = [x, x(:, vt(k))];
          x2 = [x, x(:, vr), x(:, vt(k))];     % New table to test
        R = corrcoef(x2);                      % Correlations table
        Ryy = R(1:p, 1:p);
        Rxx = R(p+1:p+j, p+1:p+j);
        Rxy = R(p+1:p+j, 1:p);
        Ryx = Rxy';
        rvt = trace(Ryx*Rxy)/((trace(Ryy^2)*trace(Rxx^2))^0.5); % RV calculation
        if rvt > Rvmax
          Rvmax = rvt;                         % test of RV
          vrt(j) = vt(k);                      % temporary held variable
      vr(j) = vrt(j);                          % Result: variable
      RV(j) = Rvmax;                           % Result: correlation
      f = find(vt~=vr(j));                     % identify the held variable
      vt = vt(f);                              % reidentify variables to test
  timing = toc;
  cumulate = cumulate + timing;
times(5, 3) = timing;
disp(['Escoufier''s method on a 100x100 matrix (mixed)________ (sec): ' num2str(timing)])
clear x; clear p; clear vt; clear vr; clear vrt; clear rvt; clear RV; clear j; clear k;
clear x2; clear R; clear Rxx; clear Ryy; clear Rxy; clear Ryx; clear Rvmax; clear f;
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