Class with static variables in parallel global optimization algorithm

2019 2 8
2 个回答
更新时间：2019 3 21
15 次查看（30 天）

0 个投票

Hello,
I have a global optimization program dealing with large matrices (several gigabytes of data), so in order to save memory, a class with static variables was implemented similar to the implementation in Static Data, and then one object of this class is created, initialized and passed as an argument to a function handle acting as the objective function of global multistage optimization algorithm (Particle Swarm + Pattern Search). When parallelization in optimoptions is true:
optimoptions( ...
'UseParallel', true);
The optimization always yields false results, but when parallelization is turned off, it works correctly.
Thanks in advance!

请先登录，再回答此问题。

回答（2 个）

Matt J
Matt J 2019-2-8
编辑：Matt J 2019-2-8

0 个投票

All variables are cloned when parallelization is used. Each parallel worker operates with an independent copy of any variable sent to it.

5 个评论
显示 3更早的评论 隐藏 3更早的评论

Omar Kamel
Omar Kamel 2019-2-8
So as they are persistent variables, they are cloned/created with their initial null value?
In other words, how can I force Matlab to copy the object with its data to each parallel worker?
Omar Kamel
Omar Kamel 2019-2-8
This is the code of the class:
classdef cDampingConstData
properties
end
methods (Static )
function out = setget_A_0_0(data)
persistent Var;
if nargin
Var = data;
end
out = Var;
end
function out = setget_delta_A_to_delta_d(data)
persistent Var;
if nargin
Var = data;
end
out = Var;
end
end
end
Matt J
Matt J 2019-2-8
Okay, but we also need to see how it is used in the optimization.
Omar Kamel
Omar Kamel 2019-2-14
编辑：Omar Kamel 2019-2-14
Sorry for the late reply.
%create object and initialize
dampingModelDataObject = cDampingConstData; %create object of type cDampingConstData
dampingModelDataObject.setget_delta_A_to_delta_d(delta_A_to_delta_d); %initialize object with fields
dampingModelDataObject.setget_A_0_0(A_0_0); %initialize object with fields
dampingModelDataObject.setget_states_num(A_0_0); %initialize object with fields
%objective function handler, object is passed to it with another constant inputs and d as variable
fun = @(d) DampIT.SumModalDamping_sparse_oo(reshape(d,1,1,num_damping_coefficients), dampingModelDataObject,targetModalDamping);
%optimization options
options = optimoptions('particleswarm', 'Display', 'iter', ...
'HybridFcn', {@patternsearch, patternsearch_hybrid_options}, ... %hybrid optimization
'MaxTime', obj.settings.pp_swarm_maxTime, ...
'MaxIterations', obj.settings.pp_swarm_maxIter, ...
'FunctionTolerance', obj.settings.pp_swarm_tolFun, ...
'PlotFcn', { @pswplotbestf}, ...
'SwarmSize', obj.settings.pp_swarm_swarmSize, ...
'OutputFcn', memLog_swarm, ...
'UseParallel', useparallel_flag, ... %true
'UseVectorized', false, ...
'MaxStallIterations', obj.settings.pp_swarm_maxStallIter, ...
'InitialSwarmMatrix', InitialSwarmMatrix);
%problem settings
problem.solver = 'particleswarm';
problem.objective = fun;
problem.nvars = num_damping_coefficients;
problem.lb = x_start;
problem.ub = x_end;
problem.options = options;
%start optimization
[d_optimized, fval, exitflag, output] = particleswarm(problem);

请先登录，再进行评论。

Walter Roberson
Walter Roberson 2019-2-14

0 个投票

Look again at the link you provided . Notice the point about static data not being saved with an object . The process of sending variables to parallel workers involves save and load.

3 个评论
显示 1更早的评论 隐藏 1更早的评论

Omar Kamel
Omar Kamel 2019-3-21
编辑：Omar Kamel 2019-3-21
I couldn't understand your answer.
What I want to implement is that: save a matrix in memory (constant matrix), pass this matrix to a function that is evaluated with parfor, so every worker shoud use only the instance that is saved only 1 time in the memory
parfor i = 1:1000
out = some_function(constant_matrix, variable_data)
end
This constant_matrix is created before this parfor command.
Walter Roberson
Walter Roberson 2019-3-21
https://www.mathworks.com/help/parallel-computing/parallel.pool.constant.html
However, that saves the matrix once per worker, not "only 1 time in the memory". If you strictly need "only 1 time in the memory" then you should look in the File Exchange for https://www.mathworks.com/matlabcentral/fileexchange/28572-sharedmatrix which uses operating system shared memory.

请先登录，再进行评论。

类别

在 帮助中心 和 File Exchange 中查找有关 Surrogate Optimization 的更多信息

产品

标签

编辑：

Matt J
Matt J
2019-3-21

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by