DYNAMIC COMPILER OPTIMIZATION TECHNIQUES FOR MATLAB by

MATLAB has gained widespread acceptance among engineers and scientists. Several aspects of the language such as dynamic loading and typing, safe updates, copy semantics for arrays, and support for higher-order functions contribute to its appeal, but at the same time provide many challenges to the compiler and virtual machine. MATLAB is a dynamic language. Traditional implementations of the language use interpreters and have been found to be too slow for large computations. More recently, researchers and software developers have been developing JIT compilers for MATLAB and other dynamic languages. This the-sis is about the development of new compiler analyses and transformations for a MATLAB JIT compiler, McJIT, which is based on the LLVM JIT compiler toolkit. The new contributions include a collection of novel analyses for optimizing copying of arrays, which are performed when a function is first compiled. We designed and imple-mented four analyses to support an efficient implementation of array copy semantics in a MATLAB JIT compiler. Experimental results show that copy optimization is essential for performance improvement in a compiler for the MATLAB language