Demand of adaptive hard-constrained devices is continuing to increase. Developing efficient implementations of such systems means to address trade-offs among different specifications, i.e. real-time processing, low power consumption and partial context switching at runtime. In this PhD Plan, we will focus on the hardware perspective presenting how we intend to study and experience with adaptive co-processing architectures, considering software as a supporting element.

Adaptive software-augmented hardware reconfiguration with dataflow design automation

Rubattu, Claudio;Palumbo, Francesca;
2018-01-01

Abstract

Demand of adaptive hard-constrained devices is continuing to increase. Developing efficient implementations of such systems means to address trade-offs among different specifications, i.e. real-time processing, low power consumption and partial context switching at runtime. In this PhD Plan, we will focus on the hardware perspective presenting how we intend to study and experience with adaptive co-processing architectures, considering software as a supporting element.
2018
9781538637975
Software
Computer Networks and Communications
Computer Science Applications1707 Computer Vision and Pattern Recognition
Hardware and Architecture
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11584/399503
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