2,078 research outputs found
Modified affine arithmetic in tensor form for trivariate polynomial evaluation and algebraic surface plotting
This paper extends the modified affine arithmetic in matrix form method for
bivariate polynomial evaluation and algebraic curve plotting in 2D to modified affine
arithmetic in tensor form for trivariate polynomial evaluation and algebraic surface
plotting in 3D. Experimental comparison shows that modified affine arithmetic in
tensor form is not only more accurate but also much faster than standard affine
arithmetic when evaluating trivariate polynomials
Enhancing numerical constraint propagation using multiple inclusion representations
Building tight and conservative enclosures of the solution set is of crucial importance in the design of efficient complete solvers for numerical constraint satisfaction problems (NCSPs). This paper proposes a novel generic algorithm enabling the cooperative use, during constraint propagation, of multiple enclosure techniques. The new algorithm brings into the constraint propagation framework the strength of techniques coming from different areas such as interval arithmetic, affine arithmetic, and mathematical programming. It is based on the directed acyclic graph (DAG) representation of NCSPs whose flexibility and expressiveness facilitates the design of fine-grained combination strategies for general factorable systems. The paper presents several possible combination strategies for creating practical instances of the generic algorithm. The experiments reported on a particular instance using interval constraint propagation, interval arithmetic, affine arithmetic, and linear programming illustrate the flexibility and efficiency of the approac
Toward accurate polynomial evaluation in rounded arithmetic
Given a multivariate real (or complex) polynomial and a domain ,
we would like to decide whether an algorithm exists to evaluate
accurately for all using rounded real (or complex) arithmetic.
Here ``accurately'' means with relative error less than 1, i.e., with some
correct leading digits. The answer depends on the model of rounded arithmetic:
We assume that for any arithmetic operator , for example or , its computed value is , where is bounded by some constant where , but
is otherwise arbitrary. This model is the traditional one used to
analyze the accuracy of floating point algorithms.Our ultimate goal is to
establish a decision procedure that, for any and , either exhibits
an accurate algorithm or proves that none exists. In contrast to the case where
numbers are stored and manipulated as finite bit strings (e.g., as floating
point numbers or rational numbers) we show that some polynomials are
impossible to evaluate accurately. The existence of an accurate algorithm will
depend not just on and , but on which arithmetic operators and
which constants are are available and whether branching is permitted. Toward
this goal, we present necessary conditions on for it to be accurately
evaluable on open real or complex domains . We also give sufficient
conditions, and describe progress toward a complete decision procedure. We do
present a complete decision procedure for homogeneous polynomials with
integer coefficients, {\cal D} = \C^n, and using only the arithmetic
operations , and .Comment: 54 pages, 6 figures; refereed version; to appear in Foundations of
Computational Mathematics: Santander 2005, Cambridge University Press, March
200
A recursive Taylor method for algebraic curves and surfaces
This paper examines recursive Taylor methods for multivariate polynomial evaluation over an interval, in the context of algebraic curve and surface plotting as a particular application representative of similar problems in CAGD. The modified affine arithmetic method (MAA), previously shown to be one of the best methods for polynomial evaluation over an interval, is used as a benchmark; experimental results show that a second order recursive Taylor method (i) achieves the same or better graphical quality compared to MAA when used for plotting, and (ii) needs fewer arithmetic operations in many cases. Furthermore, this method is simple and very easy to implement. We also consider which order of Taylor method is best to use, and propose that second order Taylor expansion is generally best. Finally, we briefly examine theoretically the relation between the Taylor method and the MAA method
Modified Affine Arithmetic Is More Accurate than Centered Interval Arithmetic or Affine Arithmetic
In this paper we give mathematical proofs of two new results relevant to evaluating algebraic functions over a box-shaped region: (i) using interval arithmetic in centered form is always more accurate than standard a#ne arithmetic, and (ii) modified a#ne arithmetic is always more accurate than interval arithmetic in centered form. Test results show that modified a#ne arithmetic is not only more accurate but also much faster than standard a#ne arithmetic. We thus suggest that modified a#ne arithmetic is the method of choice for evaluating algebraic functions, such as implicit surfaces, over a box
Precision analysis for hardware acceleration of numerical algorithms
The precision used in an algorithm affects the error and performance of individual computations, the
memory usage, and the potential parallelism for a fixed hardware budget. However, when migrating
an algorithm onto hardware, the potential improvements that can be obtained by tuning the precision
throughout an algorithm to meet a range or error specification are often overlooked; the major reason
is that it is hard to choose a number system which can guarantee any such specification can be met.
Instead, the problem is mitigated by opting to use IEEE standard double precision arithmetic so as to be
āno worseā than a software implementation. However, the flexibility in the number representation is one
of the key factors that can be exploited on reconfigurable hardware such as FPGAs, and hence ignoring
this potential significantly limits the performance achievable.
In order to optimise the performance of hardware reliably, we require a method that can tractably
calculate tight bounds for the error or range of any variable within an algorithm, but currently only a
handful of methods to calculate such bounds exist, and these either sacrifice tightness or tractability,
whilst simulation-based methods cannot guarantee the given error estimate. This thesis presents a new
method to calculate these bounds, taking into account both input ranges and finite precision effects,
which we show to be, in general, tighter in comparison to existing methods; this in turn can be used to
tune the hardware to the algorithm specifications.
We demonstrate the use of this software to optimise hardware for various algorithms to accelerate
the solution of a system of linear equations, which forms the basis of many problems in engineering
and science, and show that significant performance gains can be obtained by using this new approach in
conjunction with more traditional hardware optimisations
TMsim : an algorithmic tool for the parametric and worst-case simulation of systems with uncertainties
This paper presents a general purpose, algebraic toolānamed TMsimāfor the combined parametric and worst-case analysis of systems with bounded uncertain parameters.The tool is based on the theory of Taylor models and represents uncertain variables on a bounded domain in terms of a Taylor polynomial plus an interval remainder accounting for truncation and round-off errors.This representation is propagated from inputs to outputs by means of a suitable redefinition of the involved calculations, in both scalar and matrix form. The polynomial provides a parametric approximation of the variable, while the remainder gives a conservative bound of the associated error. The combination between the bound of the polynomial and the interval remainder provides an estimation of the overall (worst-case) bound of the variable. After a preliminary theoretical background, the tool (freely available online) is introduced step by step along with the necessary theoretical notions. As a validation, it is applied to illustrative examples as well as to real-life problems of relevance in electrical engineering applications, specifically a quarter-car model and a continuous time linear equalizer
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