Dynamic processor allocation for multiple RHC systems in multi-core computing environments

Abstract

This paper develops a new dynamic processor allocation algorithm for multiple receding horizon controllers (RHC) executing on a multi-core parallel computer. The proposed formulation accounts for bounded model uncertainty, sensor noise, and computation delay. A cost function appropriate for control of multiple coupled vehicle systems on multiple processors is used and an upper bound on the cost as a function of the execution horizon is employed. A parallel processing adaptation of the SNOPT optimization package is used and the efficiency factor of the parallel optimization routine is estimated through simulation benchmarks. Minimization of the cost function upper bound combined with the efficiency factor information results in a combinatorial optimization problem for dynamically allocating the optimal number of logical processors for each RHC subsystem. The new approach is illustrated through simulation of a leaderfollower control system for two 3DOF helicopters running on a computer with two quad-core processors.

Controlling software applications via resource allocation within the heartbeats framework

“…Varma et al present a modification of the PID control algorithm to synthesize a nqPID (not quite PID) control system to chose the CPU frequency of a computing unit [12]. In [13] a system that runs multiple receding horizon controllers on the same multi core machine is considered. The number of processors assigned to each subsystem is changed as well as the execution horizons of each controller, casting the proposed problem into an optimization one.…”