Titlebook: Dynamically Reconfigurable Systems; Architectures, Desig Marco Platzner,Jürgen Teich,Norbert Wehn Book 2010 Springer Science+Business Media

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ADCe’s Law has its validity each technology step forces the developers to rethink their approaches and even more to develop new ideas to be able to keep up with current technological challenges. The main goal of this project was the exploration of existing architectures and development of new ideas and

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Akustikecute hardware modules, previously only known for software modules. In order to realize these promises, the following dilemmas had to be solved: the too often limited memory of reconfigurable architectures for many data-intensive applications, the restricted communication possibilities for partial h

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Animationdynamically change their reconfiguration potential to adapt to the current needs of a computation and therefore gauge high flexibility with high reconfiguration overhead against small flexibility with reduced overhead. Within this concept we also propose the use of multi-level reconfiguration where

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Anmutungs. This situation, which we aim to resolve with our research, is often linked to the lack of programming languages for adaptive computers that are familiar to software developers. We present a compile flow capable of translating general-purpose C programs to hybrid hardware/software applications for

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Art Décoisting design flows for DPR are either low-level and complex or lack support for automatic synthesis. In this chapter, we present a SystemC?-based modelling and synthesis flow using the OSSS+R framework for reconfigurable systems. Our approach addresses reconfiguration already on application level e

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Artefaktigins of this overhead and present a novel approach to solve this problem. We introduce the reconfiguration state graph which is used to describe dynamic reconfiguration for individual resources and to assess reconfiguration cost. We present new method to map reconfigurable modules to resources such

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AspenFor example, dynamically loading and unloading modules onto an FPGA causes fragmentation, and—in turn—may decrease performance. To counteract this effect, we use methods from algorithmics and mathematical optimization to increase the performance and present algorithms for placing, scheduling, and de