This paper describes the management of register spills in a retargetable C compiler. Spills are rare, which means that testing is a bigger problem than performance. The trade-offs have been arranged so that the common case (no spills) generates respectable code quickly and the uncommon case (spills) is less efficient but as simple as possible. The technique has proven practical and is in production use on VAX, Motorola 68020, SPARC and MIPS machines. KEY WORDS ANSI C code generation compilers register allocation register spilling INTRODUCTION When register allocators run out of registers, they generate code to spill one or more busy registers into temporaries and code to reload those values when they are needed again. The trend in compiling research is increasing the sophistication --- and the implementation and execution costs --- of the techniques that avoid spills.

We describe an algorithm that efficiently implements the first-fit strategy for dynamic storage allocation. The algorithm imposes a storage overhead of only one word per allocated block (plus a few percent of the total space used for dynamic storage), and the time required to allocate or free a block is O(log W), where W is the maximum number of words allocated dynamically. The algorithm is faster than many commonly used algorithms, especially when many small blocks are allocated, and has good worst-case behavior. It is relatively easy to implement and could be used internally by an operating system or to provide run-time support for high-level languages such as Pascal and Ada. A Pascal implementation is given in the Appendix.

Data for yield maps can be obtained from modern combine harvesters equipped with a dierential global positioning system and a yield monitoring system. Due to delay and smoothing eects in the combine harvester the recorded yield data for a location represents a shifted weighted average of yield previously harvested along the swath. The unobserved yield is assumed to be a Gaussian random eld and the yield monitoring system data is modelled as a convolution of the yield and an impulse response function. This results in an unusual spatial covariance structure (depending on the driving pattern of the combine harvester) for the yield monitoring system data. Parameters of the impulse response function and the spatial covariance function of the yield are estimated using maximum likelihood. The tted model is assessed using certain empirical directional covariograms and the yield is nally predicted using the inferred statistical model.

Selecting the right numerical solver or the most appropriate numerical package for a particular simulation problem it is increasingly difficult for users without an extensive mathematical background and deeper knowledge in numerical analysis. In this paper we propose a model-driven combined decision-simulation framework for automatically selecting a numerical method for a given set of equation system. We also propose a formal paradigm based on domain-specific languages for specification of structural and behavioral aspects of the numerical equation solving process. Starting from a declarative description of the equation system that need to be solved, our system is able to detect the nature of the equations, perform symbolic manipulations of the equations, and transform them into a domain-specific model. We describe the motivation for such a system, its main features, and a prototype environment together with a usage example.

This paper provides some reflections on the field of mathematical software on the occasion of John Rice's 65th birthday. I describe some of the common themes of research in this field and recall some significant events in its evolution. Finally, I raise a number of issues that are of concern to future developments.

. This document is an excerpt from the current hypertext version of an article that appeared in Walter Gautschi (ed.), Mathematics of Computation 1943--1993: A Half-Century of Computational Mathematics, Proceedings of Symposia in Applied Mathematics 48, American Mathematical Society, Providence, RI 02940, 1994. The symposium was held at the University of British Columbia August 9--13, 1993, in honor of the fiftieth anniversary of the journal Mathematics of Computation. The original abstract follows. Higher transcendental functions continue to play varied and important roles in investigations by engineers, mathematicians, scientists and statisticians. The purpose of this paper is to assist in locating useful approximations and software for the numerical generation of these functions, and to offer some suggestions for future developments in this field. 4.7. Zeta Function. 4.7.1. Real Arguments. Algorithms: [CHT71], [Luk69b], [PB72]. Software Packages: [Mar65, Algol]. Intermediate Libr...

this document is subject to change without notice. VISUAL NUMERICS, INC., MAKES NO WARRANTY OF ANY KIND WITH REGARD TO THIS MATERIAL, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE. Visual Numerics, Inc., shall not be liable for errors contained herein or for incidental, consequential, or other indirect damages in connection with the furnishing, performance, or use of this material. All rights are reserved.No part of this document may be photocopied or reproduced without the prior written consent of Visual Numerics, Inc.

A variety of approaches are available for using computational models to help understand neural processes over many levels of description, from sub-cellular processes to behavior. Alongside purely deductive bottom-up or top-down modeling, a systems design strategy has the advantage of providing a clear goal for the behavior of a complex model. The order in which biological details are added is dictated by functional requirements in terms of the tasks the model should perform.

Abstract. Selecting the right numerical solver or the most appropriate numerical package for a particular simulation problem it is increasingly difficult for users without an extensive mathematical background and deeper knowledge in numerical analysis. In this paper we present the design of an extensible simulation and decision framework for selecting numerical solvers, called ModSimPack. Starting from a declarative description of the equation system that need to be solved, our system is able to detect the nature of the equations, perform symbolic manipulations of the equation, automatically select a numerical solver, and emit procedural simulation code that calls the selected solver. We describe the motivation for such a system, its main features, and a prototype environment together with several usage examples. 1.

GOBANCHO HIKARI BLDG. 4 TH Floor