MaJIC

MaJIC: A Matlab just in time compiler. This paper describes our experience with MaJIC, a just-in-time compiler for MATLAB. In the recent past, several compiler projects claimed large performance improvements when processing MATLAB code. Most of these projects are static compilers suited for batch processing; MaJIC is a just-in-time compiler. The compilation process is transparent to the user. This impacts the modus operandi of the compiler, resulting in a few interesting analysis techniques. Our experiments with MaJIC indicate large speedups when compared to the interpreter, and reasonable performance when compared to static compilers.

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References in zbMATH (referenced in 9 articles , 1 standard article )

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  1. Wiik, Jonatan; Boström, Pontus: Contract-based verification of MATLAB-style matrix programs (2016)
  2. Kotthaus, Helena; Korb, Ingo; Lang, Michel; Bischl, Bernd; Rahnenführer, Jörg; Marwedel, Peter: Runtime and memory consumption analyses for machine learning R programs (2015)
  3. Li, Jiangtian; Ma, Xiaosong; Yoginath, Srikanth; Kora, Guruprasad; Samatova, Nagiza F.: Transparent runtime parallelization of the R scripting language (2011) ioport
  4. Hunyadi, Levente: MatForce: supporting rapid algorithm development by automated translation of MatLab prototypes into C++ (2008)
  5. Almási, Gheorghe; De Rose, Luiz; Fraguela, Basilio B.; Moreira, José; Padua, David: Programming for locality and parallelism with hierarchically tiled arrays (2004)
  6. Chauhan, Arun; Kennedy, Ken: Slice-hoisting for array-size inference in MATLAB (2004)
  7. Kawabata, Hideyuki; Suzuki, Mutsumi; Kitamura, Toshiaki: A MATLAB-based code generator for sparse matrix computations (2004)
  8. Okamoto, Masayuki; Isbister, Katherine; Nakanishi, Hideyuki; Ishida, Toru: Supporting cross-cultural communication with a large-screen system (2002)
  9. Almasi, George; Padua, David A.: MaJIC: A Matlab just in time compiler (2001)