Product category:
Design and Development Software
News Release from: The MathWorks | Subject: Parallel Computing Toolbox
Edited by the Electronicstalk Editorial
Team on 13 May 2008
Toolboxes combine in parallel
development
Parallel computing capabilities are now integrated inside the optimisation solvers of MathWorks Optimisation Toolbox and Genetic Algorithm and Direct Search Toolbox.
The MathWorks has integrated its Parallel Computing Toolbox with its widely used Matlab optimisation toolboxes to help further simplify the development of parallel applications Parallel computing capabilities are now integrated inside the optimisation solvers of MathWorks Optimisation Toolbox and Genetic Algorithm and Direct Search Toolbox, enabling users to solve computationally-intensive optimisation problems on multicore computers and computer clusters without significantly changing their existing programs
This article was originally published on Electronicstalk on 22 Feb 2002 at 8.00am (UK)
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The MathWorks optimisation toolboxes give engineers and scientists the tools needed to find optimal solutions, perform tradeoff analysis, balance multiple design alternatives and quickly incorporate optimisation methods in their algorithms and models.
The integration of select optimisation solvers with Parallel Computing Toolbox allows for the use of available computational resources to solve more computationally-intensive problems than previously possible on a single core.
The result is a reduction in the time to solution for optimisation problems that are amenable to parallel computing.
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Example applications include calibrating an automotive engine control unit with experimental data, identifying an aircraft design that minimises noise while maximising fuel efficiency and selecting a portfolio of stocks that maximise gains while minimising risk.
According to Jie Wu, High-Performance Computing (HPC) Analyst for IDC: "Although revenue for hardware going into HPC reached an all-time high of US $11.5 billion in 2007, software development in this area will continue to be the number-one roadblock to further adoption of this advanced hardware".
"The MathWorks is taking the necessary steps toward helping the industry overcome this major hurdle by building solutions that allow engineers and scientist to easily program applications that make use of advanced parallel computing platforms".
"This latest announcement demonstrates our company's continued commitment to helping the industry overcome the challenges associated with development of parallel applications", says Silvina Grad-Freilich, Manager of Parallel Computing and Application Deployment Marketing of The MathWorks.
"The parallel computing capabilities provided within our toolboxes allow Matlab users to develop parallel applications using exactly the same functions that they use in their serial programs, empowering engineers and scientists to experience the benefits of high-performance computing without necessitating that they learn new skill sets".
Additional features with this release include support for two additional widely used schedulers in the Parallel Computing Toolbox: PBS Pro from Altair Grid Technologies and Torque.
Support for third-party schedulers enable cluster administrators to integrate MathWorks parallel computing tools into their existing distributed computing environments.
Parallel Computing Toolbox offers features that simplify the development of parallel applications in Matlab, including programming constructs such as parallel "for" loops and distributed arrays that let users harness multicore and multiprocessor hardware environments.
These constructs can be used without learning a complex parallel language or making significant changes to existing serial code.
Optimisation Toolbox extends the Matlab technical computing environment with tools and widely used algorithms for standard and large-scale optimisation.
These algorithms solve constrained and unconstrained continuous and discrete problems.
The toolbox includes functions for linear programming, quadratic programming, nonlinear optimisation, nonlinear least squares, solving systems of nonlinear equations, multi-objective optimisation and binary integer programming.
Genetic Algorithm and Direct Search Toolbox software extends the optimisation capabilities in Matlab and Optimisation Toolbox products with tools for using genetic algorithms, simulated annealing and direct search.
These algorithms can be used for problems that are difficult to solve with traditional optimisation techniques, including problems that are not well defined or are difficult to model mathematically.
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