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The growing synergy between Web Services and Gridbased technologies [7] will potentially enable profound, dynamic interactions between scientific applications dispersed in geographic, institutional, and conceptual space. Such deep interoperability requires the simplicity, robustness, and extensibility for which SOAP [4, 3] was conceived, thus making it a natural lingua franca. Concomitant with these advantages, however, is a degree of inefficiency that may limit the applicability of SOAP to some situations. In this paper, we investigate the limitations of SOAP for high-performance scientific computing. We analyze the processing of SOAP messages, and identify the issues of each stage. We present a high-performance SOAP implementation and a schema-specific parser based on the results of our investigation. After our SOAP optimizations are implemented, the most significant bottleneck is ASCII/double conversion. Instead of handling this using extensions to SOAP, we recommend a multiprotocol approach that uses SOAP to negotiate faster binary protocols between messaging participants. 1

Object-oriented programming languages have always distinguished between "primitive" and "user-defined" data types, and in the case of languages like C++ and Java, the primitives are not even treated as objects, further fragmenting the programming model. The distinction is especially problematic when a particular programming community requires primitive-level support for a new data type, as for complex, intervals, fixed-point numbers, and so on.

this paper is to present a method for handling non-preventable and nonavoidable catastrophic exceptions in embedded hard real-time environments in a well-structured and predictable way, and as painlessly as possible. First, apt hardware and software platforms which are pre-requisite for predictable system behaviour are briefly presented. Then, some existing techniques are shown and their suitability for implementation in embedded hard real-time environments is discussed. Further, a classification of exceptions and our own approach for handling them is presented and elaborated. Finally, a method for the estimation of the resulting temporal behaviour is described. 1 Introduction

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A computer simulation, such as a genetic algorithm, that uses IEEE standard oating-point arithmetic may not produce exactly the same results in two dierent runs, even if it is rerun on the same computer with the same input and random number seeds. Researchers should not simply assume that the results from one run replicate those from another but should verify this by actually comparing the data. However, researchers who are aware of this pitfall can reliably replicate simulations, in practice. This paper discusses the problem and suggests solutions.

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Floating-point arithmetic is defined by the IEEE-754 standard and has often been formalized. We propose a new Coq formalization based on the bit-level representation of the standard and we prove strong links between this new formalization and a previous high-level one. In this process, we have defined functions for any rounding mode described by the standard. Our library can now be applied to certify both software and hardware. Developing results in those two dramatically different directions, like no other formal development so far, guarantees that nothing was forgotten or poorly specified in our formalization. It also lets us compare our work with the existing bit-level formalizations developed with other proof assistants.

We explicit the link between the computer arithmetic problem of providing correctly rounded algebraic functions and some diophantine approximation issues. This allows to get bounds on the accuracy with which intermediate calculations must be performed to correctly round these functions.

Underflow is a floating-point phenomenon. Although the use of gradual underflow as defended in [2] and [5] is now widespread, most numerical analysts may not be aware of the fact that several implementations of the same principle are in existence, leading to different behaviour of code on different platforms, mainly with respect to exception signaling. We intend to thoroughly discuss the slight differences among these implementations. Examples will be taken from current hardware and from our own multiprecision software class library. Throughout the discussion the focus is on the analysis of the phenomenon and not on any implementation issues. Many programmers are also unaware of the fact that the IEEE 754 and 854 standards do not guarantee that a program will deliver identical results on all conforming systems. Of all the differences that can occur cross-platform, the underflow exception is just one. ? Research Director FWO-Vlaanderen ffl Supported by an NOI-grant from the Universi...