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MapReduce is a very popular programming model to support parallel and distributed large-scale data processing. There have been a lot of efforts to implement this model on commodity GPU-based systems. However, most of these implementations can only work on a single GPU. And they can not be used to process large-scale datasets. In this paper, we present a new approach to design the MapReduce framework...
Distributed computing offers many advantages for all types of computational applications. Realizing heterogeneous simulation platforms may benefit from many facilities of distributed computing. However, distributing simulation components over a network raises many challenges concerning communications, data exchange, numerical stabilities and others. A well-known solution that addresses some of these...
UML is widely applied for the specification and modeling of software and some studies have demonstrated that it is applicable for HW/SW codesign. However, in this area there is still a big gap from UML modeling to SystemC-based verification and synthesis environments. This paper presents an efficient approach to bridge this gap in the context of Systems-on-a-Chip (SoC) design. We propose a framework...
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