[DEV] Add function to parallelize SDDP

Author: frapac

examples/parallel_sddp.jl

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+
+import StochDynamicProgramming
+
+require("damsvalley.jl")
+
+# Perform n parallel passes:
+N_PARALLEL_COMPUTATIONS = 3
+# Synchronize cuts every n iterations:
+SYNCHRONIZE = 5
+
+# Import model and params in main worker
+# /!\ This line must be before redefinition of seed!
+model, params = init_problem()
+
+# Redefine seeds in every processes to maximize randomness:
+@everywhere srand()
+
+params.maxItNumber = SYNCHRONIZE
+# First pass of algorithm to define value functions in memory:
+V = StochDynamicProgramming.solve_SDDP(model, params)[1]
+
+# Count number of available CPU:
+ncpu = nprocs() - 1
+println("\nLaunch simulation on ", ncpu, " processes")
+workers = procs()[2:end]
+
+# As we distribute computation in n process, we perform forward pass in parallel:
+params.forwardPassNumber = max(1, round(Int, params.forwardPassNumber/ncpu))
+
+# Start parallel computation:
+for i in 1:N_PARALLEL_COMPUTATIONS
+    # Distribute computation of SDDP in each process:
+    refs = [@spawnat w StochDynamicProgramming.solve_SDDP(model, params, V, 1)[1] for w in workers]
+    # Catch the result in the main process:
+    V = StochDynamicProgramming.catcutsarray([fetch(r) for r in refs]...)
+    # We clean the resultant cuts:
+    StochDynamicProgramming.remove_redundant_cuts!(V)
+    StochDynamicProgramming.prune_cuts!(model, params, V)
+    println("Lower bound at pass ", i, ": ", StochDynamicProgramming.get_lower_bound(model, params, V))
+end
+