User Cooperation Network Coding Approach for NoC Performance Improvement

Abstract

The astonishing rate of sensing modalities and data generation poses a tremendous impact on computing platforms for providing real-time mining and prediction capabilities. We are capable of monitoring thousands of genes and their interactions, but we lack efficient computing platforms for large-scale (exa-scale) data processing. Towards this end, we propose a novel hierarchical Network-on-Chip (NoC) architecture that exploits user-cooperated network coding (NC) concepts for improving system throughput. Our proposed architecture relies on a light-weighted subnet of cooperation unit routers (CUR) for multicast traffic. Coding network interface (CNI) performs encoding/decoding of NC symbols and shares the data flows among cooperation units(CUs). We endow our proposed NC-based NoC architecture with: (i) a corridor routing algorithm (CRA) for maximizing network throughput and (ii) an adaptive flit dropping (AFD) scheme to mitigate congestion, branch-blocking and deadlock at run-time. The experimental results demonstrate that our proposed platform offers up to 127X multicast throughput improvement over multiple-unicast and XY tree-based multicast under synthetic collective traffic scenario. We have evaluated the proposed platform with different realworld benchmarks under network sizes of 4x4 to 32x32. Simulation results show 21%−91% latency improvement and up to 25X runtime reduction over conventional mesh NoC performing genetic-algorithm based protein folding analysis. FPGA implementation results show minimal overhead.

A Resilient 2-D Waveguide Communication Fabric for Hybrid Wired-Wireless NoC Design

“…We compare with conventional channel model where signals are transmitted over pure air with no MAA (e.g. two-ray channel model in [20]) 8 . The simulation is implemented in MATLAB and the parameters of various gas compositions are obtained from the HITRAN database [18].…”

“…15(b), where the total path loss of the proposed and the conventional channel models is plotted against the system electronic noise 8. In our model, the medium compositions consist of water vapour (which could also an effect of emerging liquid cooling technology), carbon dioxide, oxygen, nitrogen, ozone, molecular hydrogen, nitrous oxide, methane, dioxygen, nitrogen oxide, sulfur dioxide, acetylene, ethane, ethylene, methanol, hydrogen cyanide, chloromethane, hydroxyl radical, hydrogen chloride, chlorine monoxide, carbonyl sulfide, formaldehyde, hypochlorous acid, hydrogen peroxide, phosphine, carbonyl fluoride, sulfur hexafluoride, hydrogen sulfide, formic acid, hydroperoxyl radical, chlorine nitrate, nitrosonium ion, hypobromous acid, bromomethane, acetonitrile, carbon tetrafluoride, diacetylene, cyanoacetylene, carbon monosulfide, sulfur trioxide.…”

Weighted Round Robin Configuration for Worst-Case Delay Optimization in Network-on-Chip

“…The frameworks can account and exploit the nonstationary and multi-fractal characteristics of computation and communication workloads. To address the problem of distant and large volume data exchange, Xue and Bogdan [14] present a user-cooperation network coding strategy for NoCs.…”

“…1) Delay Optimization: As mentioned before, decision variables in the proposed optimization problems are the weights on shared channels. Due to shared channels in VOPD application, 20 weights are formulated in the optimizations as a weight vector W defined as follows: W = w (6,3,0,4) , w (10,2,0,0) , w (14,0,0,2) , w (13,3,0,2) , w (12,0,0,2) , w (9,4,0,0) , w (4,3,0,4) , w (4,0,0,2) , w (8,2,0,0) , w (8,4,0,2) , w (6,2,0,4) , w (10,4,0,0) , w (14,3,0,2) , w (13,1,0,2) , w (12,3,0,2) , w (9,3,0,0) , w (4,0,0,4) , w (4,4,0,2) , w (8,…”

“…Due to shared channels in the MMS application, weight vector W consisting of 37 weights is defined as below: W = w (16,1,0,0) , w (15,3,0,2) , w (15,0,0,2) , w (5,3,0,0) , w (14,4,0,2) , w (19,1,0,2) , w (18,4,0,2) , w (18,3,0,2) , w (13,2,0,4) , w (23,3,0,0) , w (14,1,0,4) , w (10,2,0,4) , w (1,0,0,4) , w (1,3,0,…”