An Energy and Performance Exploration of Network-on-Chip Architectures

In this paper, we explore the designs of a circuit-switched router, a wormhole router, a quality-of-service (QoS) supporting virtual channel router and a speculative virtual channel router and accurately evaluate the energy-performance tradeoffs they offer. Power results from the designs placed and routed in a 90-nm CMOS process show that all the architectures dissipate significant idle state power. The additional energy required to route a packet through the router is then shown to be dominated by the data path. This leads to the key result that, if this trend continues, the use of more elaborate control can be justified and will not be immediately limited by the energy budget. A performance analysis also shows that dynamic resource allocation leads to the lowest network latencies, while static allocation may be used to meet QoS goals. Combining the power and performance figures then allows an energy-latency product to be calculated to judge the efficiency of each of the networks. The speculative virtual channel router was shown to have a very similar efficiency to the wormhole router, while providing a better performance, supporting its use for general purpose designs. Finally, area metrics are also presented to allow a comparison of implementation costs

A scalable multi-core architecture with heterogeneous memory structures for Dynamic Neuromorphic Asynchronous Processors (DYNAPs)

Neuromorphic computing systems comprise networks of neurons that use asynchronous events for both computation and communication. This type of representation offers several advantages in terms of bandwidth and power consumption in neuromorphic electronic systems. However, managing the traffic of asynchronous events in large scale systems is a daunting task, both in terms of circuit complexity and memory requirements. Here we present a novel routing methodology that employs both hierarchical and mesh routing strategies and combines heterogeneous memory structures for minimizing both memory requirements and latency, while maximizing programming flexibility to support a wide range of event-based neural network architectures, through parameter configuration. We validated the proposed scheme in a prototype multi-core neuromorphic processor chip that employs hybrid analog/digital circuits for emulating synapse and neuron dynamics together with asynchronous digital circuits for managing the address-event traffic. We present a theoretical analysis of the proposed connectivity scheme, describe the methods and circuits used to implement such scheme, and characterize the prototype chip. Finally, we demonstrate the use of the neuromorphic processor with a convolutional neural network for the real-time classification of visual symbols being flashed to a dynamic vision sensor (DVS) at high speed.Comment: 17 pages, 14 figure

Using an FPGA for Fast Bit Accurate SoC Simulation

In this paper we describe a sequential simulation method to simulate large parallel homo- and heterogeneous systems on a single FPGA. The method is applicable for parallel systems were lengthy cycle and bit accurate simulations are required. It is particularly designed for systems that do not fit completely on the simulation platform (i.e. FPGA). As a case study, we use a Network-on-Chip (NoC) that is simulated in SystemC and on the described FPGA simulator. This enables us to observe the NoC behavior under a large variety of traffic patterns. Compared with the SystemC simulation we achieved a factor 80-300 of speed improvement, without compromising the cycle and bit level accuracy

Design and implementation of the Quarc network on-chip

Networks-on-Chip (NoC) have emerged as alternative to buses to provide a packet-switched communication medium for modular development of large Systems-on-Chip. However, to successfully replace its predecessor, the NoC has to be able to efficiently exchange all types of traffic including collective communications. The latter is especially important for e.g. cache updates in multicore systems. The Quarc NoC architecture has been introduced as a Networks-on-Chip which is highly efficient in exchanging all types of traffic including broadcast and multicast. In this paper we present the hardware implementation of the switch architecture and the network adapter (transceiver) of the Quarc NoC. Moreover, the paper presents an analysis and comparison of the cost and performance between the Quarc and the Spidergon NoCs implemented in Verilog targeting the Xilinx Virtex FPGA family. We demonstrate a dramatic improvement in performance over the Spidergon especially for broadcast traffic, at no additional hardware cost

Fast, Accurate and Detailed NoC Simulations

Network-on-Chip (NoC) architectures have a wide variety of parameters that can be adapted to the designer's requirements. Fast exploration of this parameter space is only possible at a high-level and several methods have been proposed. Cycle and bit accurate simulation is necessary when the actual router's RTL description needs to be evaluated and verified. However, extensive simulation of the NoC architecture with cycle and bit accuracy is prohibitively time consuming. In this paper we describe a simulation method to simulate large parallel homogeneous and heterogeneous network-on-chips on a single FPGA. The method is especially suitable for parallel systems where lengthy cycle and bit accurate simulations are required. As a case study, we use a NoC that was modelled and simulated in SystemC. We simulate the same NoC on the described FPGA simulator. This enables us to observe the NoC behavior under a large variety of traffic patterns. Compared with the SystemC simulation we achieved a speed-up of 80-300, without compromising the cycle and bit level accuracy