On the Implementation of Computation-in-Memory Parallel Adder
In: IEEE Transactions on Very Large Scale Integration (VLSI) Systems, Jg. 25 (2017-08-01), S. 2206-2219
Online
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Zugriff:
Today’s computer architectures suffer from many challenges, such as the near end of CMOS downscaling, the memory/communication bottleneck, the power wall, and the programming complexity. As a consequence, these architectures become inefficient in solving big data problems or general data intensive applications. Computation-in-memory (CIM) is a novel architecture that tries to solve/alleviate the impact of these challenges using the same device (i.e., the memristor) to implement the processor and memory in the same physical crossbar. In order to analyze its feasibility in depth, this paper proposes two memristor implementations of a data intensive arithmetic application (i.e., parallel addition). To the best of our knowledge, this is the first paper that considers the cost of the entire architecture including both crossbar and its CMOS controller. The results show that CIM architecture in general and the CIM parallel adder in particular have a high scalability. CIM parallel adder achieves at least two orders of magnitude improvement in energy and area in comparison with a multicore-based parallel adder. Moreover, due to a wide variety of memristor design methods (such as Boolean logic), tradeoffs can be made between the area, delay, and energy consumption.
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On the Implementation of Computation-in-Memory Parallel Adder
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Autor/in / Beteiligte Person: | Xie, Lei ; Hamdioui, Said ; Taouil, Mottaqiallah ; Hoang Anh Du Nguyen ; Bertels, Koen ; Nane, Razvan |
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Zeitschrift: | IEEE Transactions on Very Large Scale Integration (VLSI) Systems, Jg. 25 (2017-08-01), S. 2206-2219 |
Veröffentlichung: | Institute of Electrical and Electronics Engineers (IEEE), 2017 |
Medientyp: | unknown |
ISSN: | 1557-9999 (print) ; 1063-8210 (print) |
DOI: | 10.1109/tvlsi.2017.2690571 |
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