How to share a HashMap in parallel computing

Setup

I am trying to parallelize an algorithm that runs the same code on each row of a matrix (and then postprocesses the results.)

There are some computations that occur in the processing of multiple rows (this reoccurence is hard to predict).

Therefore, currently I call an object that performs these computations and saves the results in a HashMap, so when processing row $n$ needs computations that were already done for row $m$ they don't need to be done again.

It does not affect the outcome of the algorithm in which order the rows are processed.

Problem

I am not able to use the HashMap in parallel code, each worker ends up with its own HashMap.

PS

I understand the philosophy behind this behavior. Yet in my example, order does not matter and I would like to circumvent the standard behavior.

Minimal working example:

classdef MyPar <handle
    properties
        map;
    end
    methods 
        function obj=MyPar()
            obj.map=containers.Map('KeyType','double','ValueType','any');
        end
        function y=compute(obj,n)
           if ~obj.map.isKey(n)
               obj.map(n)=sin(n);
               fprintf('Did not find key ''%d''\n',n)
           else
               fprintf('Found key ''%d''\n',n)
           end
           y=obj.map(n);
        end
    end
    methods(Static)
        function R=test()
            c=MyPar();
            Nworkers=3;
            A=ones(Nworkers,2);
            spmd(Nworkers)
               R=c.compute(A(labindex,1))+c.compute(A(labindex,2));
            end    
        end
    end
end

Running MyPar.test() gives

>> MyPar.test();
Lab 1: 
  Did not find key '1'
  Found key '1'
Lab 2: 
  Did not find key '1'
  Found key '1'
Lab 3: 
  Did not find key '1'
  Found key '1'

In this trivial example, I would wish to have a code where two of the workers don't need to do their own computations at all (because the only computation ever done is compute(1))