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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/10761/3640

Data: 6-mar-2017
Autori: Mineo, Andrea
Titolo: Low Power Techniques for Future Network-on-Chip Architectures
Abstract: In a multi-many/core system, the Network-on-Chip (NoC) based communication backbone is responsible for a relevant fraction of the overall energy budget. In fact, the I/O buffers, the crossbars of the routers and the inter-router links are the main contributors of the NoC s energy dissipation. Specifically, electrical links will soon represent a bottleneck both in terms of energy dissipation and delay. For these reasons, several short and long terms solutions have been proposed from the NoCs research community. In particular, several techniques are based on reducing the voltage swing in links resulting in significant energy saving. We propose techniques and architectures for runtime tuning of the voltage swing of inter-router links. The proposed technique, is compared with the state of the art in link energy reduction through data encoding under both synthetic and real traffic scenarios. We found that the proposed techniques allow to significantly reduce the energy consumption of the NoC fabric without degrading the performance metrics. Energy savings ranging from 20% to 43% have been observed without any relevant impact on the performance metrics. Wireless networks-on-chip (WiNoCs), have been recently proposed as candidate solutions for addressing the scalability limitations of conventional multi-hop NoC architectures. In a WiNoC, a subset of network nodes, namely, radio hubs, are equipped with a wireless interface that allows them to wire lessly communicate with other radio hubs. Thus, long-range communications, which would involve multiple hops in a conventional wireline NoC, can be realized by a single hop through the radio medium. Unfortunately, the energy consumed by the RF transceiver into the radio hub (i.e., the main building block in a WiNoC), and in particular by its transmitter, accounts for a significant fraction of the overall communication energy. In order to alleviate such contribution, two techniques have been proposed in this thesis. A first solution consists in a runtime tunable transmitting power technique for improving the energy efficiency of the transceiver. The basic idea is tuning the transmitting power based on the physical location of the recipient of the current communication. Specifically, based on the destination address of the incoming packet, the radio hub tunes its transmitting power to a minimum level, but high enough to reach the destination antenna without exceeding a certain bit error ratio. The proposed technique applied on different representative WiNoC architectures results in an average transmitter energy reduction up to 50% without any impact on performance and with a negligible overhead in terms of silicon area. A second solution focuses on the impact of antennas orientation on energy figures and performs a design space exploration for determining the optimal orientation of the antennas in such a way to minimize the communication energy consumption. When the antennas are optimally oriented, up to 80% transmitter energy saving has been observed. Unfortunately, energy consumed by WiNoC transceiver does not depend by the transmitter but also by other modules including the receiver. In this sense, in order to obtain a further energy reduction in this thesis we propose a technique based on selectively turning off, for the appropriate number of cycles, all the radio-hubs that are not involved in the current wireless communication. The proposed energy managing technique is assessed on several network configurations under different traffic scenarios both synthetic and extracted from the execution of real applications. The obtained results show that, the application of the proposed technique allows up to 25% total communication energy saving without any impact on performance and with a negligible impact on the silicon area of the radio-hub.
InArea 09 - Ingegneria industriale e dell'informazione

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