Initial MAC exploration for graphene-enabled wireless networks-on-chip
Document typeConference report
PublisherAssociation for Computing Machinery (ACM)
Rights accessRestricted access - publisher's policy
In the upcoming many-core era, chip multiprocessor architectures will be composed of hundreds or even thousands of processor cores, which interact among them through an on-chip communication platform for synchronization and data coherency/consistency purposes. As the traffic generated within the chip becomes more multicast-intensive, it is necessary to conceive novel communication platforms that go beyond conventional schemes and guarantee multicast support with high throughput, low latency, and low power. Nanotechnology provides an opportunity within this context by virtue of terahertz graphene antennas, which could allow the integration of one antenna per core in a Graphene-enabled Wireless Network-on-Chip (GWNoC). However, it is essential to design an appropriate MAC protocol in order to fully benefit from this novel approach. To provide a first contribution in this direction, in this paper we design two baseline MAC protocols based on the well-known ALOHA and carrier sensing techniques. Their functionalities have been properly conceived by taking into account characteristics and requirements of future chip multiprocessors systems. Moreover, their performances have been evaluated by means of computer simulations under different chip configurations. Obtained results demonstrate the pros and cons of these simple contention-based MAC protocols and pave the way for the future exploration of the MAC design space.
CitationPiro, G., Abadal, S., Mestres, A., Alarcon, E., Solé-Pareta, J., Grieco, L., Boggia, G. Initial MAC exploration for graphene-enabled wireless networks-on-chip. A: ACM International Conference on Nanoscale Computing and Communication. "NANOCOM'14: proceedings of the 1st ACM International Conference on Nanoscale Computing and Communication: Atlanta, Georgia, USA: May 13-14, 2014". New York: Association for Computing Machinery (ACM), 2014.
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