Design and Implementation of High QoS 3D-NoC using Modified Double Particle Swarm Optimization on FPGA

One technique to overcome the exponential growth bottleneck is to increase the number of cores on a processor, although having too many cores might cause issues including chip overheating and communication blockage. The problem of the communication bottleneck on the chip is presently effectively resolved by networks-on-chip (NoC). A 3D stack of chips is now possible, thanks to recent developments in IC manufacturing techniques, enabling to reduce of chip area while increasing chip throughput and reducing power consumption. The automated process associated with mapping applications to form three-dimensional NoC architectures is a significant new path in 3D NoC research. This work proposes a 3D NoC partitioning approach that can identify the 3D NoC region that has to be mapped. A double particle swarm optimization (DPSO) inspired algorithmic technique, which may combine the characteristics having neighbourhood search and genetic architectures, also addresses the challenge of a particle swarm algorithm descending into local optimal solutions. Experimental evidence supports the claim that this hybrid optimization algorithm based on Double Particle Swarm Optimisation outperforms the conventional heuristic technique in terms of output rate and loss in energy. The findings demonstrate that in a network of the same size, the newly introduced router delivers the lowest loss on the longest path.  Three factors, namely energy, latency or delay, and throughput, are compared between the suggested 3D mesh ONoC and its 2D version. When comparing power consumption between 3D ONoC and its electronic and 2D equivalents, which both have 512 IP cores, it may save roughly 79.9% of the energy used by the electronic counterpart and 24.3% of the energy used by the latter. The network efficiency of the 3D mesh ONoC is simulated by DPSO in a variety of configurations. The outcomes also demonstrate an increase in performance over the 2D ONoC. As a flexible communication solution, Network-On-Chips (NoCs) have been frequently employed in the development of multiprocessor system-on-chips (MPSoCs). By outsourcing their communication activities, NoCs permit on-chip Intellectual Property (IP) cores to communicate with one another and function at a better level. The important components in assigning application duties, distributing the work to the IPs, and coordinating communication among them are mapping and scheduling methods. This study aims to present an entirely advanced form of research in the area of 3D NoC mapping and scheduling applications, grouping the results according to various parameters and offering several suggestions for further research

Exploiting generalized de-Bruijn/Kautz topologies for flexible iterative channel code decoder architectures

Modern iterative channel code decoder architectures have tight constrains on the throughput but require flexibility to support different modes and standards. Unfortunately, flexibility often comes at the expense of increasing the number of clock cycles required to complete the decoding of a data-frame, thus reducing the sustained throughput. The Network- on-Chip (NoC) paradigm is an interesting option to achieve flexibility, but several design choices, including the topology and the routing algorithm, can affect the decoder throughput. In this work logarithmic diameter topologies, in particular generalized de-Bruijn and Kautz topologies, are addressed as possible solutions to achieve both flexible and high throughput architectures for iterative channel code decoding. In particular, this work shows that the optimal shortest-path routing algorithm for these topologies, that is still available in the open literature, can be efficiently implemented resorting to a very simple circuit. Experimental results show that the proposed architecture features a reduction of about 14% and 10% for area and power consumption respectively, with respect to a previous shortest-path routing-table-based desig

Exploiting generalized de-Bruijn/Kautz topologies for flexible iterative channel code decoder architectures

Modern iterative channel code decoder architectures have tight constrains on the throughput but require flexibility to support different modes and standards. Unfortunately, flexibility often comes at the expense of increasing the number of clock cycles required to complete the decoding of a data-frame, thus reducing the sustained throughput. The Network- on-Chip (NoC) paradigm is an interesting option to achieve flexibility, but several design choices, including the topology and the routing algorithm, can affect the decoder throughput. In this work logarithmic diameter topologies, in particular generalized de-Bruijn and Kautz topologies, are addressed as possible solutions to achieve both flexible and high throughput architectures for iterative channel code decoding. In particular, this work shows that the optimal shortest-path routing algorithm for these topologies, that is still available in the open literature, can be efficiently implemented resorting to a very simple circuit. Experimental results show that the proposed architecture features a reduction of about 14% and 10% for area and power consumption respectively, with respect to a previous shortest-path routing-table-based design

Energy and performance-aware application mapping for inhomogeneous 3D networks-on-chip

Three dimensional Networks-on-Chip (3D NoCs) have evolved as an ideal solution to the communication demands and complexity of future high density many core architectures. However, the design practicality of 3D NoCs faces several challenges such as thermal issues, high power consumption and area overhead of 3D routers as well as high complexity and cost of vertical link implementation. To mitigate the performance and manufacturing cost of 3D NoCs, inhomogeneous architectures have emerged to combine 2D and 3D routers in 3D NoCs producing lower area and energy consumption while maintaining the performance of homogeneous 3D NoCs. Due to the limited number of vertical links, application mapping on inhomogeneous 3D NoCs can be complex. However, application mapping has a great impact on the performance and energy consumption of NoCs. This paper presents an energy and performance aware application mapping algorithm for inhomogeneous 3D NoCs. The algorithm has been evaluated with various realistic traffic patterns and compared with existing mapping algorithms. Experimental results show NoCs mapped with the proposed algorithm have lower energy consumption and significant reduction in packet delays compared to the existing algorithms and comparable average packet latency with Branch-and-Bound