The digital divide of computing

Abstract

This presentation urges for creating more awareness of the impact of configware engineering onto embedded system development and examines the requirements of overdue CSE curricular upgrades. Because of the impact of reconfigurable computing, configware engineering has proceeded from niche to mainstream. Morphware has become an essential and indispensable ingredient in SoC (System on a Chip) design and beyond. It turns embedded system design from hardware / software co-design into configware / software co-design [1] [2] [3] [4]. This hot development, supported by the fastest growing segment of the semiconductor market [5], provides morphware [6] [7] as an alternative RAMbased "programmable" (more precisely called: "reconfigurable") platform for parallelism avoiding the limitations of classical high performance computation [8] [9] [10] caused by the von Neumann paradigm [11] [12] [13]. The digital divide of computing determines who is qualified to take off toward new horizons in high performance computing, and, who is not. Currently the typical CS graduate is not.

Design of Embedded Augmented Reality Systems

“…With their re-configurability characteristics and the introduction of new special-purpose resources blocks, FPGAs offer a number of advantages over classical design methodologies based on general purpose processors or even the more specialized Digital Signal Processors (DSP), such as unmatched parallelism, versatility, and short time to market. Moreover, Rewww.intechopen.com configurable Computing has been presented as a promising paradigm that will compete against the traditional von Newmann architecture and its parallel enhancements (Hartenstein, 2002), (Hartenstein, 2004). Augmented Reality applications and, particularly, embedded ones, can take huge benefits from these emerging so called config-ware technologies.…”

Performance optimization with scalable reconfigurable computing systems

“…Attention has also been drawn towards the significance of a reconfigurable coprocessor coupled with a GPP [3], [4]. In just over a decade, such designs have proceeded from niche to mainstream [5]. In the earliest models of reconfigurable computing architectures, fine grain reconfigurable devices, like FPGAs, were connected as a cluster of computing elements controlled by a GPP.…”

New challenges in computer science education

“…Such systems will integrate hardware and software components and require developers with skills in both subjects [30]. Based on current trends we believe that by the year 2010 90% of the software developed will be for embedded systems [1,11]. Therefore it is necessary to adapt current computer science courses to deal with the issues of developing those systems.…”