Fat-Tree-Based Optical Interconnection Networks Under Crosstalk Noise Constraint

Fat-Tree-Based Optical Interconnection Networks Under Crosstalk Noise Constraint

Abstract— Fat-Tree-Based Optical Interconnection Networks Under Crosstalk Noise Constraint. Optical networks-on-chip < Final Year Projects 2016 > ONoCs have shown the potential to be substituted for electronic networks-on-chip (NoCs) to bring substantially higher bandwidth and more efficient power consumption in both on- and off-chip communication. However, basic optical devices, which are the key components in constructing ONoCs, experience inevitable crosstalk noise and power loss; the crosstalk noise from the basic devices accumulates in large-scale ONoCs and considerably hurts the signal-to-noise ratio (SNR) as well as restricts the network scalability. For the first time, this paper presents a formal system-level analytical approach to analyze the worst-case crosstalk noise and SNR in arbitrary fat-tree-based ONoCs. The analyses are performed hierarchically at the basic optical device level, then at the optical router level, and finally at the network level. A general 4 × 4 optical router model is considered to enable the proposed method to be adaptable to fat-tree-based ONoCs using an arbitrary 4 × 4 optical router. Utilizing the proposed general router model, the worst-case SNR link candidates in the network are determined. Moreover, we apply the proposed analyses to a case study of fat-tree-based ONoCs using an optical turnaround router (OTAR). Quantitative simulation results indicate low values of SNR and scalability constraints in large scale fat-tree-based ONoCs, which is due to the high power of crosstalk noise and power loss. For instance, in fat-tree-based ONoCs using the OTAR, when the injection laser power equals 0 dBm, the crosstalk noise power is higher than the signal power when the number of processor cores exceeds 128; when it is equal to 256, the signal power, crosstalk noise power, and SNR are −17.3, −11.9, and−5.5 dB, respectively.