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This paper presents a novel reconfigurable framework for training Convolutional Neural Networks (CNNs). The proposed framework is based on reconfiguring a streaming datapath at runtime to cover the training cycle for the various layers in a CNN. The streaming datapath can support various parameterized modules which can be customized to produce implementations with different trade-offs in performance...
The performance gap between processor and storage device has continuously increased during the past few decades. The gap is further exacerbated recently because applications are becoming more data-intensive in both industry and academia. Traditional storage devices, such as hard disk drives (HDD), fail to keep up with the paces of this growth. A known solution is to use solid state drives (SSD) as...
We present a DEVS and Cell-DEVS simulation system based on Microsoftpsilas .NET Remoting, an execution framework for Windows programs. Remoting is the process of programs interacting across different processes or machines. The numerous remoting services in .NET provide the ability to invoke objects that exist anywhere on the network. We modified PCD++ (a parallel DEVS and Cell-DEVS simulation tool...
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