Montana is an open, extensible integrated programming environment for C++ that supports incremental compilation and linking, a persistent code cache called a CodeStore, and a set of programming interfaces to the CodeStore for tool writers. CodeStore serves as a central source of information for compiling, browsing, and debugging. CodeStore contains information about both the static and dynamic structure of the compiled program. This information spans files, macros, declarations, function bodies, templates and their instantiations, program fragment dependencies, linker relocation information, and debugging information.Montana allows the compilation process to be extended and modified [11]. Montana has been used as the basis of a number of tools [1,7], and is also used as the infrastructure of a production compiler, IBM's Visual Age C++ 4.0 [8].

Solid modeling underlies many technologies that are key to modern manufacturing. These range from CAD systems to robot simulators, from finite-element analysis to integrated circuit process modeling. The accuracy, and hence the utility, of these models is often constrained by the amount of computer time required to perform the desired operations. In this paper we present, in detail, an efficient algorithm for parallel intersections of solids using the Connection Machine, a massively parallel SIMD processor. We describe the data structure for representing the solid models and detail the intersection algorithm, giving special attention to implementation issues. We provide performance results, comparing the parallel algorithm to a serial intersection algorithm.

This work describes the Semiconductor Wafer Representation (SWR) for representing and manipulating wafer state during process and device simulation. The goal of the SWR is to provide an object-oriented interface to a collection of functions designed for developing and integrating Technology CAD (TCAD) applications. By providing functions which can be common across many applications, we aim to greatly reduce tool development and integration time. Corporate, vendor, and university TCAD developers have worked together under the auspices of the CAD Framework Initiative to create an architecture and C++ programming interface for an SWR 1.0 draft standard. Here we describe this architecture and the results of creating and using a prototype implementation of the standard both to integrate existing TCAD tools and to develop simple new tools.>

Many fundamental tests performed by geometric algorithms can be formulated in terms of finding the sign of a determinant. When these tests are implemented using fixed precision arithmetic such as floating point, they can produce incorrect answers; when they are implemented using arbitrary-precision arithmetic, they are expensive to compute. We present adaptive-precision algorithms for finding the signs of determinants of matrices with integer and rational elements. These algorithms were developed and tested by integrating them into the Guibas-Stolfi Delaunay triangulation algorithm. Through a combination of algorithm design and careful engineering of the implementation, the resulting program can triangulate a set of random rational points in the unit circle only four to five times slower than can a floating-point implementation of the algorithm. The algorithms, engineering process, and software tools developed are described.