I am running a parfor loop in Matlab that takes a lot of time and I would like to know how many iterations are left. How can I get that info?
I don't believe you can get that information directly from MATLAB, short of printing something with each iteration and counting these lines by hand.
To see why, recall that each parfor iteration executes in its own workspace: while incrementing a counter within the loop is legal, accessing its "current" value is not (because this value does not really exist until completion of the loop). Furthermore, the parfor construct does not guarantee any particular execution order, so printing the iterator value isn't helpful.
cnt = 0;
parfor i=1:n
cnt = cnt + 1; % legal
disp(cnt); % illegal
disp(i); % legal ofc. but out of order
end
Maybe someone does have a clever workaround, but I think that the independent nature of the parfor iterations belies taking a reliable count. The restrictions mentioned above, plus those on using evalin, etc. support this conclusion.
As #Jonas suggested, you could obtain the iteration count via side effects occurring outside of MATLAB, e.g. creating empty files in a certain directory and counting them. This you can do in MATLAB of course:
fid = fopen(['countingDir/f' num2str(i)],'w');
fclose(fid);
length(dir('countingDir'));
Try this FEX file: http://www.mathworks.com/matlabcentral/fileexchange/32101-progress-monitor--progress-bar--that-works-with-parfor
You can easily modify it to return the iteration number instead of displaying a progress bar.
Something like a progress bar could be done similar to this...
Before the parfor loop :
fprintf('Progress:\n');
fprintf(['\n' repmat('.',1,m) '\n\n']);
And during the loop:
fprintf('\b|\n');
Here we have m is the total number of iterations, the . shows the total number of iterations and | shows the number of iterations completed. The \n makes sure the characters are printed in the parfor loop.
With Matlab 2017a or later you can use a data queue or a pollable data queue to achieve this. Here's the MathWorks documentation example of how to do a progress bar from the first link :
function a = parforWaitbar
D = parallel.pool.DataQueue;
h = waitbar(0, 'Please wait ...');
afterEach(D, #nUpdateWaitbar);
N = 200;
p = 1;
parfor i = 1:N
a(i) = max(abs(eig(rand(400))));
send(D, i);
end
function nUpdateWaitbar(~)
waitbar(p/N, h);
p = p + 1;
end
end
End result :
If you just want to know how much time is left approximately, you can run the program once record the max time and then do this
tStart = tic;
parfor i=1:n
tElapsed = toc(tStart;)
disp(['Time left in min ~ ', num2str( ( tMax - tElapsed ) / 60 ) ]);
...
end
I created a utility to do this:
http://www.mathworks.com/matlabcentral/fileexchange/48705-drdan14-parforprogress
Related
Suppose we are running an infinite for loop in MATLAB, and we want to store the iterative values in a vector. How can we declare the vector without knowing the size of it?
z=??
for i=1:inf
z(i,1)=i;
if(condition)%%condition is met then break out of the loop
break;
end;
end;
Please note first that this is bad practise, and you should preallocate where possible.
That being said, using the end keyword is the best option for extending arrays by a single element:
z = [];
for ii = 1:x
z(end+1, 1) = ii; % Index to the (end+1)th position, extending the array
end
You can also concatenate results from previous iterations, this tends to be slower since you have the assignment variable on both sides of the equals operator
z = [];
for ii = 1:x
z = [z; ii];
end
Sadar commented that directly indexing out of bounds (as other answers are suggesting) is depreciated by MathWorks, I'm not sure on a source for this.
If your condition computation is separate from the output computation, you could get the required size first
k = 0;
while ~condition
condition = true; % evaluate the condition here
k = k + 1;
end
z = zeros( k, 1 ); % now we can pre-allocate
for ii = 1:k
z(ii) = ii; % assign values
end
Depending on your use case you might not know the actual number of iterations and therefore vector elements, but you might know the maximum possible number of iterations. As said before, resizing a vector in each loop iteration could be a real performance bottleneck, you might consider something like this:
maxNumIterations = 12345;
myVector = zeros(maxNumIterations, 1);
for n = 1:maxNumIterations
myVector(n) = someFunctionReturningTheDesiredValue(n);
if(condition)
vecLength = n;
break;
end
end
% Resize the vector to the length that has actually been filled
myVector = myVector(1:vecLength);
By the way, I'd give you the advice to NOT getting used to use i as an index in Matlab programs as this will mask the imaginary unit i. I ran into some nasty bugs in complex calculations inside loops by doing so, so I would advise to just take n or any other letter of your choice as your go-to loop index variable name even if you are not dealing with complex values in your functions ;)
You can just declare an empty matrix with
z = []
This will create a 0x0 matrix which will resize when you write data to it.
In your case it will grow to a vector ix1.
Keep in mind that this is much slower than initializing your vector beforehand with the zeros(dim,dim) function.
So if there is any way to figure out the max value of i you should initialize it withz = zeros(i,1)
cheers,
Simon
You can initialize z to be an empty array, it'll expand automatically during looping ...something like:
z = [];
for i = 1:Inf
z(i) = i;
if (condition)
break;
end
end
However this looks nasty (and throws a warning: Warning: FOR loop index is too large. Truncating to 9223372036854775807), I would do here a while (true) or the condition itself and increment manually.
z = [];
i = 0;
while !condition
i=i+1;
z[i]=i;
end
And/or if your example is really what you need at the end, replace the re-creation of the array with something like:
while !condition
i=i+1;
end
z = 1:i;
As mentioned in various times in this thread the resizing of an array is very processing intensive, and could take a lot of time.
If processing time is not an issue:
Then something like #Wolfie mentioned would be good enough. In each iteration the array length will be increased and that is that:
z = [];
for ii = 1:x
%z = [z; ii];
z(end+1) = ii % Best way
end
If processing time is an issue:
If the processing time is a large factor, and you want it to run as smooth as possible, then you need to preallocating.If you have a rough idea of the maximum number of iterations that will run then you can use #PluginPenguin's suggestion. But there could still be a change of hitting that preset limit, which will break (or severely slow down) the program.
My suggestion:
If your loop is running infinitely until you stop it, you could do occasional resizing. Essentially extending the size as you go, but only doing it once in a while. For example every 100 loops:
z = zeros(100,1);
for i=1:inf
z(i,1)=i;
fprintf("%d,\t%d\n",i,length(z)); % See it working
if i+1 >= length(z) %The array as run out of space
%z = [z; zeros(100,1)]; % Extend this array (note the semi-colon)
z((length(z)+100),1) = 0; % Seems twice as fast as the commented method
end
if(condition)%%condition is met then break out of the loop
break;
end;
end
This means that the loop can run forever, the array will increase with it, but only every once in a while. This means that the processing time hit will be minimal.
Edit:
As #Cris kindly mentioned MATLAB already does what I proposed internally. This makes two of my comments completely wrong. So the best will be to follow what #Wolfie and #Cris said with:
z(end+1) = i
Hope this helps!
I have a code in MATLAB in which I'm running monte-carlo simulations using parfor instead of simple for loop to convert the code from sequential to parallel. Following is the piece of code which is inside the parfor loop.
But MATLAB gives an error saying "Valid indices for local_Q_mega_sub_seed are restricted in parfor loop". Suggested action says to "Fix the index" and it suggests to use "Sliced Variables". I've been struggling to use this concept. I have read https://blogs.mathworks.com/loren/2009/10/02/using-parfor-loops-getting-up-and-running/#12 and https://www.mathworks.com/matlabcentral/answers/123922-sliced-variables-in-parfor-loop-restricted-indexing along with MATLAB documentation https://www.mathworks.com/help/distcomp/sliced-variable.html and https://www.mathworks.com/help/distcomp/parfor.html but I'm not getting it right.
Could anyone please let me know how can I use sliced variables in the given piece of code so that I could get an idea?
index_f = 1;
subseed_step = (sub_seed_transmitted_at/fs_local)*sintablen_mega_frequency;
for i = 1 : fs_local
local_Q_mega_sub_seed(i) = SINTAB(round(index_f));
local_I_mega_sub_seed(i) = COSTAB(round(index_f));
index_f = index_f + subseed_step;
if index_f>sintablen_mega_frequency
index_f = index_f - sintablen_mega_frequency;
end
You're not showing enough context here, but I bet the problem here is similar to this one:
parfor ii = 1:10
for jj = 1:10
tmp(jj) = rand
end
out(ii) = sum(tmp);
end
In this case, the parfor machinery cannot categorically prove that the way tmp is being used is independent of the order of iterations of the parfor loop. This is because it appears as though values assigned to tmp in one iteration of the parfor loop are still being used in the next iteration.
Fortunately, there's a very simple workaround for this case - convince parfor that you are not doing anything dependent on the order of evaluation of the iterations of the loop by resetting the variable. In the simple case above, this means:
parfor ii = 1:10
% reset 'tmp' at the start of each parfor loop iteration
tmp = [];
for jj = 1:10
tmp(jj) = rand
end
out(ii) = sum(tmp);
end
I'm looping in parallel and changing a variable if a condition is met. Super idiomatic code that I'm sure everyone has written a hundred times:
trials = 100;
greatest_so_far = 0;
best_result = 0;
for trial_i = 1:trials
[amount, result] = do_work();
if amount > greatest_so_far
greatest_so_far = amount;
best_result = result;
end
end
If I wanted to replace for by parfor, how can I ensure that there aren't race conditions when checking whether we should replace greatest_so_far? Is there a way to lock this variable outside of the check? Perhaps like:
trials = 100;
greatest_so_far = 0;
best_result = 0;
parfor trial_i = 1:trials
[amount, result] = do_work();
somehow_lock(greatest_so_far);
if amount > greatest_so_far
greatest_so_far = amount;
best_result = result;
end
somehow_unlock(greatest_so_far);
end
Skewed answer. It does not exactly solve your problem, but it might help you avoiding it.
If you can afford the memory to store the outputs of your do_work() in some vectors, then you could simply run your parfor on this function only, store the result, then do your scoring at the end (outside of the loop):
amount = zeros( trials , 1 ) ;
result = zeros( trials , 1 ) ;
parfor trial_i = 1:trials
[amount(i), result(i)] = do_work();
end
[ greatest_of_all , greatest_index ] = max(amount) ;
best_result = result(greatest_index) ;
Edit/comment : (wanted to put that in comment of your question but it was too long, sorry).
I am familiar with .net and understand completely your lock/unlock request. I myself tried many attempts to implement a kind of progress indicator for very long parfor loop ... to no avail.
If I understand Matlab classification of variable correctly, the mere fact that you assign greatest_so_far (in greatest_so_far=amount) make Matlab treat it as a temporary variable, which will be cleared and reinitialized at the beginning of every loop iteration (hence unusable for your purpose).
So an easy locked variable may not be a concept we can implement simply at the moment. Some convoluted class event or file writing/checking may do the trick but I am afraid the timing would suffer greatly. If each iteration takes a long time to execute, the overhead might be worth it, but if you use parfoor to accelerate a high number of short execution iterations, then the convoluted solutions would slow you down more than help ...
You can have a look at this stack exchange question, you may find something of interest for your case: Semaphores and locks in MATLAB
The solution from Hoki is the right way to solve the problem as stated. However, as you asked about race conditions and preventing them when loop iterations depend on each other you might want to investigate spmd and the various lab* functions.
You need to use SPMD to do this - SPMD allows communication between the workers. Something like this:
bestResult = -Inf;
bestIndex = NaN;
N = 97;
spmd
% we need to round up the loop range to ensure that each
% worker executes the same number of iterations
loopRange = numlabs * ceil(N / numlabs);
for idx = 1:numlabs:loopRange
if idx <= N
local_result = rand(); % obviously replace this with your actual function
else
local_result = -Inf;
end
% Work out which index has the best result - use a really simple approach
% by concatenating all the results this time from each worker
% allResultsThisTime will be 2-by-numlabs where the first row is all the
% the results this time, and the second row is all the values of idx from this time
allResultsThisTime = gcat([local_result; idx]);
% The best result this time - consider the first row
[bestResultThisTime, labOfBestResult] = max(allResultsThisTime(1, :));
if bestResultThisTime > bestResult
bestResult = bestResultThisTime;
bestIndex = allResultsThisTime(2, labOfBestResult);
end
end
end
disp(bestResult{1})
disp(bestIndex{1})
I run a lot of long simulations in Matlab, typically taking from a couple of minutes to a couple of hours, so to speed things up I decided to run the simulations simultaneously using a parfor loop.
arglist = [arg1, arg2, arg3, arg4];
parfor ii = 1:size(arglist, 2)
myfun(arglist(ii));
end
Everything worked just fine, except for one thing: the progress printing. Since each simulation takes a lot of time, I usually print progress using something like
prevlength = 0;
for ii = 1:tot_iter
% Some calculations here
msg = sprintf('Working on %d of %d, %.2f percent done', ii, tot_iter, ii/tot_iter);
fprintf(repmat('\b', 1, prevlength))
fprintf(msg);
prevlength = numel(msg);
end
but, as could be expected, when doing this inside a parfor loop, you get chaos.
I have googled a lot in search of a solution and have found a bunch of "parfor progress printers" like this one. However, all of them print the progress of the entire parfor loop instead of showing how far each of the individual iterations have come. Since I only have about 4-8 iterations in the parfor loop, but each iteration takes about an hour, this approach isn't very helpful to me.
The ideal solution for me would be something that looks like this
Working on 127 of 10000, 1.27 percent done
Working on 259 of 10000, 2.59 percent done
Working on 3895 of 10000, 38.95 percent done
Working on 1347 of 10000, 13.47 percent done
that is, each simulation gets one line showing how far it has run. I'm not sure though if this is possible at all, I can at least not imagine any way to do this.
Another way would be to do something like this
Sim 1: 1.27% Sim 2: 2.59% Sim 3: 38.95% Sim 4: 13.47%
that is, show all the progresses on the same line. To do this, you would need to keep track of what position on the line each simulation is to write on and write there, without erasing the other progresses. I can't figure out how this would be done, is this possible to do?
If there is some other solution to my problem (showing the progress of each individual iteration) that I haven't thought of, I'd be happy to hear about it.
Since this is the first time I ask a question here on SO it is quite possible that there is something that I have missed; if so, please feel free to comment below.
Edit
After receiving this answer, I thought that I should share how I used it to solve my problem since I didn't use it exactly as in the answer, in case someone else encounters the same problem.
Here is a small test program with basically the same structure as my program, making use of the progress bar (parfor_progress) mentioned in the answer:
function parfor_progress_test()
cpus = feature('numCores');
matlabpool('open', cpus);
cleaner = onCleanup(#mycleaner);
args = [1000, 1000, 1000, 1000];
m = sum(args);
parfor_progress(m);
parfor ii = 1:size(args,2)
my_fun(args(ii));
end
parfor_progress(0);
end
function my_fun(N)
for ii = 1:N
pause(rand*0.01);
parfor_progress;
end
end
function mycleaner
matlabpool close;
fclose all;
end
Simple Progress Bar
Something like a progress bar could be done similar to this...
Before the parfor loop :
fprintf('Progress:\n');
fprintf(['\n' repmat('.',1,m) '\n\n']);
And during the loop:
fprintf('\b|\n');
Here we have m is the total number of iterations, the . shows the total number of iterations and | shows the number of iterations completed. The \n makes sure the characters are printed in the parfor loop.
Progress Bar and Percentage Completion
Otherwise you could try this: http://www.mathworks.com/matlabcentral/fileexchange/32101-progress-monitor--progress-bar--that-works-with-parfor
It will display a progress bar and percentage completion but can be easily modified to just include the percentage completion or progress bar.
This function amends a character to a file on every iteration and then reads the number of characters written to that file which indicates the number of iterations completed. This file accessing method is allowed in parfor's.
Assuming you correctly add the above to your MATLAB path somehow, you can then use the following:
arglist = [arg1, arg2, arg3, arg4];
parfor_progress(size(arglist, 2)); % Set the total number of iterations
parfor ii = 1:size(arglist, 2)
myfun(arglist(ii));
parfor_progress; % Increment the progress counter
end
parfor_progress(0); % Reset the progress counter
Time to Completion and Percentage Completion
There is also a function called showTimeToCompletion() which is available from: https://www.soundzones.com/software/sound-zone-tools/
and works alongside parfor_progress. This function allows you to print a detailed summary of the progress of a parfor loop (or any loop for that matter) which contains the start time, length of time running, estimated finish time and percentage completion. It makes smart use of the \b (backspace) character so that the command window isn't flooded with text. Although not strictly a progress 'bar' it is perhaps more informative.
The third example in the header of the function file,
fprintf('\t Completion: ');
showTimeToCompletion; startTime=tic;
len=1e2;
p = parfor_progress( len );
parfor i = 1:len
pause(1);
p = parfor_progress;
showTimeToCompletion( p/100, [], [], startTime );
end
outputs the following to the command window:
Completion: 31.00%
Remaining: 00:00:23
Total: 00:00:33
Expected Finish: 3:30:07PM 14-Nov-2017
Useful for estimating the completion of a running simulation, especially one that may take hours or days.
Starting in R2013b, you can use PARFEVAL to evaluate your function asynchronously and have the client display progress updates. (Obviously this approach is not quite as simple as adding stuff to your PARFOR loop). There's an example here.
The Diary property of the Future returned by PARFEVAL is updated continuously while processing, so that might also be useful if you have a small number of large tasks.
Starting in R2017a, you can use parallel.pool.DataQueue and afterEach to implement a waitbar for parfor, like so:
if isempty(gcp('nocreate'))
parpool('local', 3);
end
dq = parallel.pool.DataQueue;
N = 10;
wb = waitbar(0, 'Please wait...');
% Use the waitbar's UserData to track progress
wb.UserData = [0 N];
afterEach(dq, #(varargin) iIncrementWaitbar(wb));
afterEach(dq, #(idx) fprintf('Completed iteration: %d\n', idx));
parfor idx = 1:N
pause(rand());
send(dq, idx);
end
close(wb);
function iIncrementWaitbar(wb)
ud = wb.UserData;
ud(1) = ud(1) + 1;
waitbar(ud(1) / ud(2), wb);
wb.UserData = ud;
end
after exploring #Edric answer I found that there is an example in the Matlab documentation that exactly implements a waitbar for a pareval loop. Check help FetchNext
N = 100;
for idx = N:-1:1
% Compute the rank of N magic squares
F(idx) = parfeval(#rank, 1, magic(idx));
end
% Build a waitbar to track progress
h = waitbar(0, 'Waiting for FevalFutures to complete...');
results = zeros(1, N);
for idx = 1:N
[completedIdx, thisResult] = fetchNext(F);
% store the result
results(completedIdx) = thisResult;
% update waitbar
waitbar(idx/N, h, sprintf('Latest result: %d', thisResult));
end
% Clean up
delete(h)
I am having trouble using struct arrays in Matlab's parfor loop. The following code has 2 problems I do not understand:
s=struct('a',{},'b',{});
if matlabpool('size')==0
matlabpool open local 2
end
for j = 1:2
parfor k=1:4
fprintf('[%d,%d]\n',k,j)
s(j,k).a = k;
s(j,k).b = j;
end
end
matlabpool close
It fails with an error Error using parallel_function (line 589)
Insufficient number of outputs from right hand side of equal sign to satisfy assignment.
On output, variable s is a vector, not an array (as it should be, even if the code breaks before finishing).
EDIT the problem is solved if I initialize the struct arrays to the correct size, by:
s=struct('a',cell(2,4),'b',cell(2,4));
However, I would still be happy to get insights about the problem (e.g is it rally a bug, as suggested by Oleg Komarov)
It was originally working fine for me but then I don't know what happens. In general you need to be careful with parfor loops and there are ample documentation on how to align everything. Two different words of advice.
First and more importantly, the parfor loop is on the outside loop:
function s = foo
s=struct('a',{},'b',{});
parfor j = 1:2
for k=1:4
fprintf('[%d,%d]\n',k,j)
s(j,k).a = k;
s(j,k).b = j;
end
end
Two, Matlab gets very picky about writing the main exit variable (i.e. the variable contained in the parfor loop which is indexed to the loop, in your case, s). You first want to create a dummy variable that holds all the innerloop information, and then writes to it once at the end of the loops. Example:
function s = khal
s=struct('a',{},'b',{});
parfor j = 1:2
dummy=struct('a',{},'b',{});
for k=1:4
fprintf('[%d,%d]\n',k,j)
dummy(k).a = k;
dummy(k).b = j;
end
s(j,:) = dummy;
end
You don't have a problem here, but it can get complicated in other instances