Exploiting Parallelism in a QPALM-based Solver for Optimal Control
This work addresses computational efficiency for optimal control applications, but it is incremental as it builds on an existing solver with parallelization techniques.
The paper tackled the problem of speeding up quadratic programs in optimal control by exploiting parallelism in the QPALM-OCP algorithm, resulting in an optimized C++ implementation that shows improved performance on benchmark problems compared to the original method.
We discuss the opportunities for parallelization in the recently proposed QPALM-OCP algorithm, a solver tailored to quadratic programs arising in optimal control. A significant part of the computational work can be carried out independently for the different stages in the optimal control problem. We exploit this specific structure to apply parallelization and vectorization techniques in an optimized C++ implementation of the method. Results for optimal control benchmark problems and comparisons to the original QPALM method are provided.