Parallelizing AT with MatlabMPI

Abstract

The Accelerator Toolbox (AT) is a high-level collection of tools and scripts specifically oriented toward solving problems dealing with computational accelerator physics. It is integrated into the MATLAB environment, which provides an accessible, intuitive interface for accelerator physicists, allowing researchers to focus the majority of their efforts on simulations and calculations, rather than programming and debugging difficulties. Efforts toward parallelization of AT have been put in place to upgrade its performance to modern standards of computing. We utilized the packages MatlabMPI and pMatlab, which were developed by MIT Lincoln Laboratory, to set up a message-passing environment that could be called within MATLAB, which set up the necessary pre-requisites for multithread processing capabilities. On local quad-core CPUs, we were able to demonstrate processor efficiencies of roughly 95% and speed increases of nearly 380%. By exploiting the efficacy of modern-day parallel computing, we were able to demonstrate incredibly efficient speed increments per processor in AT's beam-tracking functions. Extrapolating from prediction, we can expect to reduce week-long computation runtimes to less than 15 minutes. This is a huge performance improvement and has enormous implications for the future computing power of the accelerator physics group at SSRL. However, one of the downfalls of parringpass is its current lack of transparency; the pMatlab and MatlabMPI packages must first be well-understood by the user before the system can be configured to run the scripts. In addition, the instantiation of argument parameters requires internal modification of the source code. Thus, parringpass, cannot be directly run from the MATLAB command line, which detracts from its flexibility and user-friendliness. Future work in AT's parallelization will focus on development of external functions and scripts that can be called from within MATLAB and configured on multiple nodes, while expending minimal communication overhead with the integrated MATLAB library.