Parfor to speed up loops

Hi, i have a dual core processor, i wish to make use of parfor to speed up my for loop processing how do i do that? Basically i understand the i have to initialise matlabpool(2) and parfor i=1:NPARTICLES and also matlabpool close.

How do i implement it in my coding? Thanks

      if CDiff < ODiff
          dt = CDiff;
          % Predict step
            for i=1:NPARTICLES
              particles(i)= predict (particles(i), V,G,Qe, WHEELBASE,dt, SWITCH_PREDICT_NOISE);
            end
          cIndex = cIndex + 1;

      else
          dt = ODiff;
          z1 = Ob(:,OIndex);
          z = cell2mat (z1);
          z(1) = z(1)/100;
          % Predict step
          for i=1:NPARTICLES
              particles(i)= predict (particles(i), V,G,Qe, WHEELBASE,dt, SWITCH_PREDICT_NOISE);
          end

          % Perform update
          for i=1:NPARTICLES
              [zf,idf,zn]= data_associate(particles(i),z,R);

              if ~isempty(zf) % observe map features
                  w= compute_weight(particles(i), zf,idf, R); % w = p(z_k | x_k)
                     if w <= 1e-5
                       w = 1e-5;
                     end

                  particles(i).w= particles(i).w * w;
                  particles(i)= feature_update(particles(i), zf, idf, R);
              end

              if ~isempty(zn) % observe new features, augment map
                  particles(i)= add_feature(particles(i), zn,R);
              end
          end

          particles= resample_particles(particles, NEFFECTIVE, SWITCH_RESAMPLE);
          dt2 = timestamp(cIndex+1)-Obser_time(OIndex);

          for i=1:NPARTICLES
             particles(i)= predict (particles(i), V,G,Qe, WHEELBASE,dt2, SWITCH_PREDICT_NOISE);
          end

Answer 1

[Ken Atwell]

You code looks good to go.

1. Replace the "for" with "parfor"
2. "matlabpool open" before starting
3. "matlabpool close" when you're all done

But, before you do any of that, in deference to Amdahl's Law, I would be tempted to run this code through the profiler first to be certain that the bits to be parallelized make up a meaningful percentage of the program.