A MATLAB to Fortran 90 translator and its effectiveness
ICS '96 Proceedings of the 10th international conference on Supercomputing
Computer architecture (2nd ed.): a quantitative approach
Computer architecture (2nd ed.): a quantitative approach
Heuristic Algorithms for Scheduling Independent Tasks on Nonidentical Processors
Journal of the ACM (JACM)
Dynamic mapping of a class of independent tasks onto heterogeneous computing systems
Journal of Parallel and Distributed Computing - Special issue on software support for distributed computing
Compiling MATLAB Programs to ScaLAPACK: Exploiting Task and Data Parallelism
IPPS '96 Proceedings of the 10th International Parallel Processing Symposium
A MATLAB Compiler for Distributed, Heterogeneous, Reconfigurable Computing Systems
FCCM '00 Proceedings of the 2000 IEEE Symposium on Field-Programmable Custom Computing Machines
Dynamic, Competitive Scheduling of Multiple DAGs in a Distributed Heterogeneous Environment
HCW '98 Proceedings of the Seventh Heterogeneous Computing Workshop
Otter: Bridging the Gap between MATLAB and ScaLAPACK
HPDC '98 Proceedings of the 7th IEEE International Symposium on High Performance Distributed Computing
MultiMATLAB: MATLAB on Multiple Processors
MultiMATLAB: MATLAB on Multiple Processors
Results from a Parallel MATLAB Compiler
IPPS '98 Proceedings of the 12th. International Parallel Processing Symposium on International Parallel Processing Symposium
Rapid Development of Real-Time Systems using RTExpress(tm)
IPPS '98 Proceedings of the 12th. International Parallel Processing Symposium on International Parallel Processing Symposium
Architecture and implementation of a distributed reconfigurable metacomputer
ISPDC'03 Proceedings of the Second international conference on Parallel and distributed computing
Transparent runtime parallelization of the R scripting language
Journal of Parallel and Distributed Computing
Automatic compilation of MATLAB programs for synergistic execution on heterogeneous processors
Proceedings of the 32nd ACM SIGPLAN conference on Programming language design and implementation
Optimizing MATLAB through just-in-time specialization
CC'10/ETAPS'10 Proceedings of the 19th joint European conference on Theory and Practice of Software, international conference on Compiler Construction
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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.