Match virtual machine: An adaptive runtime system to execute MATLAB in parallel

Malay Haldar, Anshuman Nayak, Abhay Kanhere, Pramod Joisha, Nagaraj Shenoy, Alok Choudhary, Prithviraj Banerjee

Research output: Chapter in Book/Report/Conference proceedingChapter

8 Scopus citations


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.

Original languageEnglish (US)
Title of host publicationProceedings of the International Conference on Parallel Processing
Number of pages8
ISBN (Electronic)0769507689
StatePublished - 2000


  • Adaptive systems
  • Human computer interaction
  • Image processing
  • Limiting
  • Parallel processing
  • Runtime
  • Shape
  • Signal processing
  • Virtual machining

ASJC Scopus subject areas

  • Software
  • General Mathematics
  • Hardware and Architecture


Dive into the research topics of 'Match virtual machine: An adaptive runtime system to execute MATLAB in parallel'. Together they form a unique fingerprint.

Cite this