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function X = solve_LP(r,f,model)
Parallelize msmf corr coeff.m (view source)
Revision as of 16:17, 20 July 2018
, 16:17, 20 July 2018→Around line 120 of msmf_corr_coeff solving LP problems
==Around line 120 of msmf_corr_coeff solving LP problems==
For a large R, e.g. R = 200, solve 200 linear programming problems in parallel should be beneficial, especially when the each LP itself is easy to solve (takes less than 0.1 seconds each). Initially we managed to use gurobi inside a parfor:
% Gurobi inisde parfor. For large R (>100). By Wei.
model.rhs = [full(constrB); full(constrM)];
% The function wrapper to use Gurobi
model.obj = f(:,r);
parameters.outputflag = 0;
result = gurobi(model, parameters);
X = result.x;
end However using Gurobi actually did not help with the code performance. This is possibly due to the cost to create models for each Gurobi object. Gurobi is indeed the best commercial solver in the market, but it should be used for solving large LPs (hundreds of thousands of constraints). We reversed back to using Matlab's native linprog: % Parallelly solve LPs with Matlab's native linprog parfor r = 1 : R options = optimset('Display', 'off'); [asgr(:, r), ~, eflag(r)] = linprog(f(:, r), [B;-B], [constrB; constrM], [], [], zeros(L, 1), ones(L,1),options); end
