Optimizing Matlab through Just-In-Time Specialization

Abstract. Scientists are increasingly using dynamic programming languages like Matlab for prototyping and implementation. Effectively compiling Matlab raises many challenges due to the dynamic and complex nature of Matlab types. This paper presents a new JIT-based approach which specializes and optimizes functions on-the-fly based on the current types of function arguments. A key component of our approach is a new type inference algorithm which uses the run-time argument types to infer further type and shape information, which in turn provides new optimization opportunities. These techniques are implemented in McVM, our open implementation of a Matlab virtual machine. As this is the first paper reporting on McVM,

• Type: Conference
• Year: 2010
• Where: CC
• Authors: Maxime Chevalier-Boisvert, Laurie J. Hendren, Clark Verbrugge
• Keywords: CC 2010, MATLAB, Matlab Types, Matlab Virtual Machine, Programming Languages