A human factors methodology for real-time support applications

A general approach to the human factors (HF) analysis of new or existing projects at NASA/Goddard is delineated. Because the methodology evolved from HF evaluations of the Mission Planning Terminal (MPT) and the Earth Radiation Budget Satellite Mission Operations Room (ERBS MOR), it is directed specifically to the HF analysis of real-time support applications. Major topics included for discussion are the process of establishing a working relationship between the Human Factors Group (HFG) and the project, orientation of HF analysts to the project, human factors analysis and review, and coordination with major cycles of system development. Sub-topics include specific areas for analysis and appropriate HF tools. Management support functions are outlined. References provide a guide to sources of further information

Silicon compilation

Silicon compilation is a term used for many different purposes. In this paper we define silicon compilation as a mapping from some higher level description into layout. We define the basic issues in structural and behavioral silicon compilation and some possible solutions to those issues. Finally, we define the concept of an intelligent silicon compiler in which the compiler evaluates the quality of the generated design and attempts to improve it if it is not satisfactory

CHASSIS : a combined hardware selection and scheduling technique for performance driven synthesis

This report describes a new technique that combines the Hardware Scheduling and Component Selection phases for High Level Synthesis. Our technique simultaneously selects components from a given library while it schedules the operations into different control steps. The algoríthm improves previous work in scheduling because component costs and performance are considered during the scheduling process, enlarging the design search space and resulting in better optimized desígns

Limits on Fundamental Limits to Computation

An indispensable part of our lives, computing has also become essential to industries and governments. Steady improvements in computer hardware have been supported by periodic doubling of transistor densities in integrated circuits over the last fifty years. Such Moore scaling now requires increasingly heroic efforts, stimulating research in alternative hardware and stirring controversy. To help evaluate emerging technologies and enrich our understanding of integrated-circuit scaling, we review fundamental limits to computation: in manufacturing, energy, physical space, design and verification effort, and algorithms. To outline what is achievable in principle and in practice, we recall how some limits were circumvented, compare loose and tight limits. We also point out that engineering difficulties encountered by emerging technologies may indicate yet-unknown limits.Comment: 15 pages, 4 figures, 1 tabl

Digital implementation of the cellular sensor-computers

Two different kinds of cellular sensor-processor architectures are used nowadays in various applications. The first is the traditional sensor-processor architecture, where the sensor and the processor arrays are mapped into each other. The second is the foveal architecture, in which a small active fovea is navigating in a large sensor array. This second architecture is introduced and compared here. Both of these architectures can be implemented with analog and digital processor arrays. The efficiency of the different implementation types, depending on the used CMOS technology, is analyzed. It turned out, that the finer the technology is, the better to use digital implementation rather than analog

Learning from the Success of MPI

The Message Passing Interface (MPI) has been extremely successful as a portable way to program high-performance parallel computers. This success has occurred in spite of the view of many that message passing is difficult and that other approaches, including automatic parallelization and directive-based parallelism, are easier to use. This paper argues that MPI has succeeded because it addresses all of the important issues in providing a parallel programming model.Comment: 12 pages, 1 figur