Please use this identifier to cite or link to this item: http://idr.nitk.ac.in/jspui/handle/123456789/13604
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dc.contributor.authorParane, K.
dc.contributor.authorPrabhu, Prasad, B.M.
dc.contributor.authorTalawar, B.
dc.date.accessioned2020-03-31T08:48:14Z-
dc.date.available2020-03-31T08:48:14Z-
dc.date.issued2019
dc.identifier.citationJournal of Circuits, Systems and Computers, 2019, Vol.28, 12, pp.-en_US
dc.identifier.uri10.1142/S0218126619502025
dc.identifier.urihttp://idr.nitk.ac.in/jspui/handle/123456789/13604-
dc.description.abstractMany-core systems employ the Network on Chip (NoC) as the underlying communication architecture. To achieve an optimized design for an application under consideration, there is a need for fast and flexible NoC simulator. This paper presents an FPGA-based NoC simulation acceleration framework supporting design space exploration of standard and custom NoC topologies considering a full set of microarchitectural parameters. The framework is capable of designing custom routing algorithms, various traffic patterns such as uniform random, transpose, bit complement and random permutation are supported. For conventional NoCs, the standard minimal routing algorithms are supported. For designing the custom topologies, the table-based routing has been implemented. A custom topology called diagonal mesh has been evaluated using table-based and novel shortest path routing algorithm. A congestion-aware adaptive routing has been proposed to route the packets along the minimally congested path. The congestion-aware adaptive routing algorithm has negligible FPGA area overhead compared to the conventional XY routing. Employing the congestion-aware adaptive routing, network latency is reduced by 55% compared to the XY routing algorithm. The microarchitectural parameters such as buffer depth, traffic pattern and flit width have been varied to observe the effect on NoC behavior. For the 6�6 mesh topology, the LUT and FF usages will be increased from 32.23% to 34.45% and from 12.62% to 15% considering the buffer depth of 4 and flit widths of 16 bits, and 32 bits, respectively. Similar behavior has been observed for other configurations of buffer depth and flit width. The torus topology consumes 24% more resources than the mesh topology. The 56-node fat tree topology consumes 27% and 2.2% more FPGA resources than the 6�6 mesh and torus topologies. The 56-node fat tree topology with buffer depth of 8 and 16 flits saturates at the injection rates of 40% and 45%, respectively. � 2019 World Scientific Publishing Company.en_US
dc.titleYaNoC: Yet Another Network-on-Chip Simulation Acceleration Engine Supporting Congestion-Aware Adaptive Routing Using FPGASen_US
dc.typeArticleen_US
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