Allstats for ReduceImage

src/MATLAB/Allstats_ReduceImage.m

+%% Getting ALL Stats for Reduce Image
+
+tic
+%% Log scale - 100 steps : from 1MB to 2.7 GB
+% 1MB = 1024*1024 = 1048576 bytes
+% log(1MB) = 13.8629
+init_logsize = 13.8629;
+% Final image size = 2.7GB
+% log(2.7GB) = 21.7243
+final_logsize = 21.7243;
+% 100 steps between Initial and final image sizes
+% stepsize = 21.7243 - 13.8629 = 7.8614/100 = 0.078614
+stepsize = 0.078614;
+% Keep incrementing log sizes by 0.078614
+finalresult = struct('ImageSize',0,'ByteSize',0,'process',0,'Cuda_or_Matlab',0,'timer',0,'accuracy',0);
+% img_slice = partition_img(img,init_bytesize);
+ % Neighborhood size (3x3x3 window)
+ NeighborhoodX = 3;
+ NeighborhoodY = 3;
+ NeighborhoodZ = 3;
+ method = 'min';
+% [im, imagedata] = tiffReader();
+% img1=im(:,:,:,1);
+Image_bytesizes = [];
+for i = init_logsize:stepsize:final_logsize
+    bytesize = exp(i);
+    img1_slice = partition_img(img1,bytesize);
+    results = Getstats_ReduceImage(img1_slice,NeighborhoodX,NeighborhoodY,NeighborhoodZ,method,bytesize);
+    finalresult = cat(2,finalresult,results);
+    Image_bytesizes = [Image_bytesizes bytesize];
+end
+
+CUDA_structs = arrayfun(@(x)strcmp(x.Cuda_or_Matlab,'CUDA'),finalresult);
+CUDA_structs_indices = find(CUDA_structs);
+CUDA_times = horzcat(finalresult(CUDA_structs_indices).timer);
+Image_bytesizes = horzcat(finalresult(CUDA_structs_indices).ByteSize);
+MATLAB_structs = arrayfun(@(x)strcmp(x.Cuda_or_Matlab,'MATLAB'),finalresult);
+MATLAB_structs_indices = find(MATLAB_structs);
+MATLAB_times = horzcat(finalresult(MATLAB_structs_indices).timer);
+figure, hold on;
+plot(Image_bytesizes,CUDA_times,'r*');
+plot(Image_bytesizes,MATLAB_times,'g*');
+legend('CUDA','MATLAB');
+xlabel('Size of Image (bytes)')
+ylabel('Time taken (sec)');
+title('ReduceImage Race: CUDA vs MATLAB');
+toc
+
+