Many software applications today need to handle data from different data models; typically objects from the host programming language along with the relational and XML data models. The ROX impedance mismatch makes programs awkward to write and hard to maintain.The .NET Language-Integrated Query (LINQ) framework, proposed for the next release of the .NET framework, approaches this problem by defining a pattern of general-purpose standard query operators for traversal, filter, and projection. Based on this pattern, any .NET language can define special query comprehension syntax that is subsequently compiled into these standard operators (our code examples are in VB).Besides the general query operators, the LINQ framework also defines two domain specific APIs that work over XML (XLinq) and relational data (DLinq) respectively. The operators over XML use a lightweight and easy to use in-memory XML representation to provide XQuery-style expressiveness in the host programming language. The operators over relational data provide a simple OR mapping by leveraging remotable queries that are executed directly in the back-end relational store.

Abstract Programming environments for interactive graphics software typically have a multiplicity of tools and applications. Many of these programs contain ad hoc ‘little language’ interpreters1 that do many similar things in needlessly different ways. In particular, many little languages have, in addition to their special‐purpose constructs, vestigial support for ordinary programming, such as variables, loops and conditionals. If a single, standard programming language were the basis for all these little languages, they could have complete, coherent programming semantics; they could communicate with each other more easily; no design work for basic constructs would be needed; and interpreter implementation work would be saved. The approach of reusing and extending the same core language and interpreter for a variety of little languages is the extension language approach. Scheme is proposed as a good choice for such a core language. Scheme is a simple, elegant, high‐level programming language. Extendable implementations are readily available in C source form. Example applications in Scheme from interactive graphics are presented that would be nearly impossible to code in a typical scripting language and very tedious to code in a lower‐level implementation language such as C.

Abstract This paper analyzes the performance of a discrete‐event combat simulation executed on a parallel processor under control of the Time Warp Operating System. Time Warp is in a class of distributed simulation methods called Optimistic methods which have proven to be useful over a wide range of simulations. The combat simulation used for this performance study, called STB88, is a division‐corps model incorporating a number of different types of computations. The speed‐up for three versions of this model on the Caltech/JPL Mark III Hypercube and the BBN Butterfly parallel processors was measured relative to an efficient sequential execution of the same model on the same hardware. The results indicate that STB88 version 1 achieves a speed‐up of 28.6 on 60 Mark III processors, while STB88 version 2 achieves a speed‐up of 36.8 on 100 Butterfly processors. Version 3 of STB88 achieved a speed‐up of 38.5 on 128 Mark III processors. The versions differed only in their interface to Time Warp. On the Butterfly, the sequential execution completed in 2 hours, while the 100 processor execution completed in 3.2 minutes.

This paper describes the Time Warp Operating System, under development for three years at the Jet Propulsion Laboratory for the Caltech Mark III Hypercube multi-processor. Its primary goal is concurrent execution of large, irregular discrete event simulations at maximum speed. It also supports any other distributed applications that are synchronized by virtual time.