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We present a massively parallel FPGA-based coprocessor for Support Vector Machines (SVMs), a machine learning algorithm whose applications include recognition tasks such as learning scenes, situations and concepts, and reasoning tasks such as analyzing the recognized scenes and semantics. The coprocessor architecture, targeted at both SVM training and classification, is based on clusters of vector...
The functionality of mobile devices, such as cell phones and personal digital assistants (PDAs), has evolved to include various applications where security is a critical concern (secure web transactions, mobile commerce, download and playback of protected audio/video content, connection to corporate private networks, etc.). Security mechanisms (e.g., secure communication protocols) involve cryptographic...
We present a systematic methodology for exploring the security processing software architecture for a commercial heterogeneous multiprocessor system-on-chip (SoC) for mobile devices. The SoC contains multiple host processors executing applications and a dedicated programmable security processing engine. We developed an exploration methodology to map the code and data of security software libraries...
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