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    Laurent Bernardin

    Maple was conceived over forty years ago as a general purpose system for mathematical calculations.  Its strength, however, has always been its community. The work of hundreds of researchers from around the world has produced a... more
    Maple was conceived over forty years ago as a general purpose system for mathematical calculations.  Its strength, however, has always been its community. The work of hundreds of researchers from around the world has produced a mathematical engine unique in its depth, breath and efficiency. Forward thinking educators have used Maple to transform the way mathematics is taught, all the way supporting each other with advice, examples and myriads of Maple worksheets. Scientists and engineers have been taking advantage of the power and ease of use of the Maple system to help them in their discovery and the development of new products. Together we have tackled environmental issues, taken on disease and reached for the stars.   At Maplesoft, we are firm believers that Math Matters and our mission is to provide technology to explore, derive, capture, solve and disseminate mathematical problems and their applications, and to make math easier to learn, understand, and use. This mission, we sh...
    ABSTRACT
    Research Interests:
    Computer algebra is a branch of scientific computation. There are several characteristic features that distinguish computer algebra from numeric alanalysis, the other principal branch of scientific computation. (1) Computer algebra... more
    Computer algebra is a branch of scientific computation. There are several characteristic features that distinguish computer algebra from numeric alanalysis, the other principal branch of scientific computation. (1) Computer algebra involves computation in algebraic structures, such as finitely presented groups, polynomial rings, rational function fields, algebraic and transcendental extensions of the rational numbers, or differential and difference fields. (2) Computer algebra manipulates formulas. Whereas in numerical computation the input and output of algorithms are basically (integer or floating point) numbers, the input and output of computer algebra algorithms are generally formulas.
    Research Interests:
    Solving equations and systems of equations symbolically is a key feature of every Computer Algebra System. This review examines the capabilities of the six best known general purpose systems to date in the area of general algebraic and... more
    Solving equations and systems of equations symbolically is a key feature of every Computer Algebra System. This review examines the capabilities of the six best known general purpose systems to date in the area of general algebraic and transcendental equation solving. Areas explicitly not covered by this review are differential equations and numeric or polynomial system solving as special purpose systems exist for these kinds of problems.The aim is to provide a benchmark for comparing Computer Algebra Systems in a specific domain. We do not intend to give a rating of overall capabilities as for example [8].
    Motivation: We announce the availability of the second release of Darwin v. 2.0, an interpreted computer language especially tailored to researchers in the biosciences. The system is a general tool applicable to a wide range of problems.... more
    Motivation: We announce the availability of the second release of Darwin v. 2.0, an interpreted computer language especially tailored to researchers in the biosciences. The system is a general tool applicable to a wide range of problems. Results: This second release improves Darwin version 1.6 in several ways: it now contains (1) a larger set of libraries touching most of the classical problems from computational biology (pairwise alignment, all versus all alignments, tree construction, multiple sequence alignment), (2) an expanded set of general purpose algorithms (search algorithms for discrete problems, matrix decomposition routines, complex/long integer arithmetic operations), (3) an improved language with a cleaner syntax, (4) better on-line help, and (5) a number of fixes to user-reported bugs. Availability: Darwin is made available for most operating systems free of charge from the Computational Biochemistry Research Group (CBRG), reachable at http://cbrg.inf.ethz.ch. Contact...
    We ported the computer algebra system Maple V to the Intel Paragon a massively parallel distributed memory machine In or der to take advantage of the parallel architecture we extended the Maple kernel with a set of message passing... more
    We ported the computer algebra system Maple V to the Intel Paragon a massively parallel distributed memory machine In or der to take advantage of the parallel architecture we extended the Maple kernel with a set of message passing primitives based on the Paragon s native message passing library Using these primitives we implemented a parallel version of Karatsuba multiplication for univariate polynomials overZp Our speedup timings illustrate the practicability of our approach On top of the message passing primitives we have implemented a higher level model of parallel processing based on the manager worker scheme a managing Maple process on one node of the paral lel machine submits processing requests to Maple processes residing on di erent nodes then asynchronously collects the results This model proves to be convenient for interactive usage of a distributed memory machine
    implementation of algebraic algorithms. We suggest uses of many of Java's innovative features for symbolic software de- sign problems. We discuss the suitability of Java for generic programming, a methodology whose origins... more
    implementation of algebraic algorithms. We suggest uses of many of Java's innovative features for symbolic software de- sign problems. We discuss the suitability of Java for generic programming, a methodology whose origins actually are in computer algebra. We believe the software component ap- proach is required for designing modern systems that in- clude computer algebra. We describe ways in which Java can be used to adapt legacy software into components, and we present our ideas how component interfaces can be struc- tured.