I am very, very new to Matlab. I migrated c++ code to Matlab, because I knew vectors were involved in the problem, and thought I could get a performance boost using the language. I pretty much just translated the code line-by-line. My inexperience was obvious, since the code runs slower than it did in c++....

Obviously, I'm not taking full advantage of the language's features... or maybe the problem just isn't suited for it.

Below are the two code segments (both loops) that have become a huge bottle neck. It is a graph problem, with this iteration having 501 points (24675 edges). The program also used for much bigger test sets, up to 20,000 points, so speed is a necessity.

The first code segment takes about a minute. It reads in all the point values in a text file. master_graph is a map (int keys) of vectors (edges)

The fact that reading from a file is involved, it will obviously be slower, but is there a better way of doing this?Code:for i=1:(numEdges) %? change types to save space? line = fgets(fid); %# read line by line A = sscanf(line,'%i %i %i'); num1 = A(1); num2 = A(2); num3 = A(3); temp_node = num1; temp_edge.endpoint=num2; temp_edge.distance=num3; if (temp_edge.distance > max_distance_for_wb) max_distance_for_wb = temp_edge.distance; end if(isKey(master_graph,temp_node)) master_graph(temp_node) = [master_graph(temp_node) temp_edge]; else master_graph(temp_node) = temp_edge; end swap = temp_node; temp_node = temp_edge.endpoint; temp_edge.endpoint = swap; if(isKey(master_graph,temp_node)) master_graph(temp_node) = [master_graph(temp_node) temp_edge]; else master_graph(temp_node) = temp_edge; end end

The second code segment involves two nested for-loops. wsp and graph are in the same format as master_graph. It loops through each key and then each of the edges (stored in a vector mapped with that key). I know loops can be optimized with 'vectorization', but I'm kinda clueless. Any suggestions?

Any suggestions would be HUGELY appreciated. I need to speed this thing up anyway possible. The code runs in C++ in under a second. This code takes MINUTES. Hopefully I can avoid embarrassment in my suggestion of translating to matlab. Also, I only have access to R2010b.Code:% for each node in wsp %############################################ for it = 1:wsp.Count() %? for each edge in the graph key = thekeys{it}; for i = 1:length(graph(key)) thisEdge = graph(key); thisPoint = thisEdge(i); if (thisPoint.distance > max_edge_in_prim) continue; end if(terminal(thisPoint.endpoint)) str = sprintf('\tT'); fprintf(str); cost_of_addition = costFunc(thisPoint.distance, path_length(key)); else %disp('Not Terminal!'); str = sprintf('\t '); fprintf(str); cost_of_addition = (TRENCH_COST * thisPoint.distance); end % BENEFIT % calculate cost one time... curr_cost = costFunc(thisPoint.distance, path_length(key)); % added (TRENCH_COST *) below curr_cost = (WC * curr_cost) - (WB * benefit(thisPoint.endpoint)); str = sprintf('( %d , %d) C=%d B=%d T=%d',key,thisPoint.endpoint,costFunc(thisPoint.distance,path_length(key)), benefit(thisPoint.endpoint),curr_cost); fprintf(str); disp(' '); % curr_cost holds the overall value of which the min should % be tracked if (first || curr_cost < min) first = 0; min = curr_cost; select = thisPoint.endpoint; node = key; distance = thisPoint.distance; node_added = 1; cost_of_min = cost_of_addition; end end end

Thanks Greg