Match Virtual Machine : An Adaptive Runtime System to execute MATLAB in
Parallel
Malay Haldar, Anshuman Nayak, Abhay Kanhere, Pramod Joisha, Nagaraj Shenoy, Alok Choudhary and Prithviraj Banerjee
Abstract
MATLAB is one of the most popular languages for desktop
numerical computations as well as for signal and image processing
applications. Applying parallel processing techniques to improve
performance of MATLAB codes has been the goal of many recent works.
Most current frameworks require the user to specify parallelism and/or
information regarding type/shape of the variables, thereby sacrificing
the user friendliness which is one of the most popular MATLAB
features. Other systems work on a restricted subset of MATLAB,
thereby limiting the class of applications MATLAB can support. We
present a runtime system capable of executing MATLAB code in parallel
without any user intervention. The runtime system performs
automatic parallelization and type/shape inference of the code at
runtime. A unique feature of the runtime system is its capability
to automatically adapt to changes in the underlying architecture,
making it particularly useful for systems where predicting performance
statically is difficult. We present experimental results obtained for
the runtime system running on SGI Origin2000 shared memory multiprocessor.