Setting up parallel computations for a single dataset, as opposed to spmd

I am working with a program that needs to enter in and out of a parfor loop many times, and the data I am working on is the same for all iterations and for all workers. The code stripped down and commented is below. The key is that the data is being sent to the workers over and over again, but never changes. SPMD or distributed arrays won't help (I believe!) because its the same dataset each time ie I do not want to carve it up into sections. Its the models I need to change, which are much smaller than the data (allWfs).

Is there a way to, say, predistribute an array (allWfs in this case) to each worker and keep it on the workers for the whole calculation?

Code:

%%%%TD_parameters is predefined

%allWfs is the data I am distributing around. It needs to be the same for all models and is never modified.

[ allWfs, ~ ] = load_data_syn(TD_parameters, t);

%%%%%%%%%%%

for iter = 1:TD_parameters.n_iter

%This is the parallel loop, where I do one iteration of the monte-carlo on each model.

parfor i = 1:TD_parameters.n_chains

mset(i) = TD_inversion_function_PT(mset(i), t, TD_parameters, allWfs);

end

%%%%%%%%This is the parallel tempering step that needs to happen after each parfor statement, which is why I am entering an exiting the parallel loop so many times.

inds = randperm(length(mset));

for m1 = 1:length(inds)

for m2 = 1:length(inds)

if mset(inds(m1)).T == mset(inds(m2)).T || m2 >= m1

continue

end

a = (mset(inds(m2)).llh - mset(inds(m1)).llh)*mset(inds(m1)).T;%mset[inds[m2]].lp - mset[inds[m1]].lp;

a = a + (mset(inds(m1)).llh - mset(inds(m2)).llh)*mset(inds(m2)).T;% + mset[inds[m1]].lp - mset[inds[m2]].lp;

thresh = log(rand());

if a > thresh

T1 = mset(inds(m1)).T;

mset(inds(m1)).T = mset(inds(m2)).T;

mset(inds(m2)).T = T1;

end

end

end

%%%%%%models are saved here, removed for conciseness

end

Answer 1

[Edric Ellis]

This is precisely the sort of thing that parallel.pool.Constant was designed for. You build a Constant once on the client, the data is transferred to the workers once, and then you can access it in multiple parfor loops (or spmd blocks...). In your case, you'd use it a bit like this:

[allWfs, ~] = load_data_syn(TD_parameters, t);
allWfsConstant = parallel.pool.Constant(allWfs);
for iter = 1:TD_parameters.n_iter
    parfor i = 1:TD_parameters.n_chains
        mset(i) = TD_inversion_function_PT(mset(i), t, TD_parameters, allWfsConstant.Value);
    end
    % etc...
end

Answer 2

[Joseph Byrnes]

This certainly looks promising! But I'm not sure I am using this correctly.

If I modify for this format

%%%%%%%%

[allWfs, ~] = load_data_syn(TD_parameters, t);

p = parpool('local');

disp('Distributing data to each worker before running the program')

allWfs_const = parallel.pool.Constant(allWfs);

TD_const = parallel.pool.Constant(TD_parameters);

for iter = 1:TD_parameters.n_iter

ticBytes(p)

parfor i = 1:TD_parameters.n_chains

mset(i) = TD_inversion_function_PT(mset(i), TD_const.Value, allWfs_const.Value);

%mset(i) = TD_inversion_function_PT(mset(i), TD_parameters, allWfs);

end

tocBytes(p)

% etc...

end

%%%%%%%%%%%%%%%

for two workers on my laptop, I get the exact same output if I do the line with the _const variables or if I switch the comments and use the non-const variables. Should I see a difference with ticBytes/tocBytes?

[Edric Ellis]

Yes, ticBytes / tocBytes should show the difference. Like this:

pool = parpool("local");

Starting parallel pool (parpool) using the 'local' profile ...
Connected to the parallel pool (number of workers: 2).

data = magic(1000);
%% Without Constant
t = ticBytes(pool);
for ii = 1:10
    parfor jj = 1:10
        sum(data, "all");
    end
end
tocBytes(pool, t)

             BytesSentToWorkers    BytesReceivedFromWorkers
             __________________    ________________________

    1            8.0168e+07               1.1144e+05       
    2            8.0146e+07                    90800       
    Total        1.6031e+08               2.0224e+05       

%% With Constant
t = ticBytes(pool);
dataC = parallel.pool.Constant(data);
for ii = 1:10
    parfor jj = 1:10
        sum(dataC.Value, "all");
    end
end
tocBytes(pool, t)

             BytesSentToWorkers    BytesReceivedFromWorkers
             __________________    ________________________

    1              8.17e+06               1.0539e+05       
    2            8.1657e+06               1.0127e+05       
    Total        1.6336e+07               2.0666e+05       

%% With Constant, using function-handle constructor
t = ticBytes(pool);
% Here we send just the function handle to the workers, and they execute it
% to build |magic(1000)|.
dataC = parallel.pool.Constant(@() magic(1000));
for ii = 1:10
    parfor jj = 1:10
        sum(dataC.Value, "all");
    end
end
tocBytes(pool, t)

             BytesSentToWorkers    BytesReceivedFromWorkers
             __________________    ________________________

    1            1.8063e+05               1.1231e+05       
    2            1.7209e+05               1.0405e+05       
    Total        3.5272e+05               2.1636e+05       

[Joseph Byrnes]

I can reproduce this numbers to the third decimal (2022a, osx with Big Sur)! I think the test case I was trying did not have a big enough run to show up with ticBytes.

Thank you.