Abstract | ||
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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. |
Year | DOI | Venue |
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2000 | 10.1109/ICPP.2000.876100 | ICPP |
Keywords | Field | DocType |
user friendliness,match virtual machine,popular language,adaptive runtime system,matlab code,applications matlab,image processing application,parallel processing technique,user intervention,runtime system,execute matlab,performance statically,popular matlab feature,virtual machine,limiting,signal processing,adaptive systems,parallel programming,image processing,automatic parallelization,shape,parallel processing,virtual machines,human computer interaction | Signal processing,MATLAB,Virtual machine,Computer science,Adaptive system,Parallel computing,Image processing,Runtime verification,Distributed computing,Runtime system,Automatic parallelization | Conference |
ISSN | ISBN | Citations |
0190-3918 | 0-7695-0768-9 | 6 |
PageRank | References | Authors |
0.76 | 10 | 7 |
Name | Order | Citations | PageRank |
---|---|---|---|
Malay Haldar | 1 | 98 | 10.78 |
Anshuman Nayak | 2 | 96 | 10.31 |
Abhay Kanhere | 3 | 9 | 1.51 |
Pramod Joisha | 4 | 18 | 1.31 |
Nagaraj Shenoy | 5 | 72 | 6.49 |
Alok Choudhary | 6 | 205 | 11.94 |
Prithviraj Banerjee | 7 | 2763 | 337.99 |