899 research outputs found

    Ant-Inspired Density Estimation via Random Walks

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    Many ant species employ distributed population density estimation in applications ranging from quorum sensing [Pra05], to task allocation [Gor99], to appraisal of enemy colony strength [Ada90]. It has been shown that ants estimate density by tracking encounter rates -- the higher the population density, the more often the ants bump into each other [Pra05,GPT93]. We study distributed density estimation from a theoretical perspective. We prove that a group of anonymous agents randomly walking on a grid are able to estimate their density within a small multiplicative error in few steps by measuring their rates of encounter with other agents. Despite dependencies inherent in the fact that nearby agents may collide repeatedly (and, worse, cannot recognize when this happens), our bound nearly matches what would be required to estimate density by independently sampling grid locations. From a biological perspective, our work helps shed light on how ants and other social insects can obtain relatively accurate density estimates via encounter rates. From a technical perspective, our analysis provides new tools for understanding complex dependencies in the collision probabilities of multiple random walks. We bound the strength of these dependencies using local mixing propertieslocal\ mixing\ properties of the underlying graph. Our results extend beyond the grid to more general graphs and we discuss applications to size estimation for social networks and density estimation for robot swarms

    FDMA Enabled Phase-based Wireless Network-on-Chip using Graphene-based THz-band Antennas

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    The future growth in System-on-chip design is moving in the direction of multicore systems. Design of efficient interconnects between cores are crucial for improving the performance of a multicore processor. Such trends are seen due to the benefits the multicore systems provide in terms of power reduction and scalability. Network-on-chips (NoC) are viewed as an emerging solution in the design of interconnects in multicore systems. However, Traditional Network-on-chip architectures are no longer able to satisfy the performance requirements due to long distance communication over multi-hop wireline paths. Multi-hop communication leads to higher energy consumption, increase in latency and reduction in bandwidth. Research in recent years has explored emerging technologies such as 3D integration, photonic and radio frequency based Network-on-chips. The use of wireless interconnects using mm-wave antennas are able to alleviate the performance issues in a wireline interconnect system. However, to satisfy the increasing demand for higher bandwidth and lower energy consumption, Wireless Network-on-Chip enabled with high speed direct links operating in THz band between distant cores is desired. Recent research has brought to light highly efficient graphene-based antennas operating in THz band. These antennas can provide high data rate and are found to consume less power with low area overheads. In this thesis, an innovative approach using novel devices based on graphene structures is proposed to provide a high-performance on-chip interconnection. This novel approach combines the regular NoC structure with the proposed wireless infrastructure to exploit the performance benefits. An architecture with wireless interfaces on every core is explored in this work. Simultaneous multiple communications in a network can be achieved by adopting Frequency Division Multiple access (FDMA). However, in a system where all cores are equipped with a wireless interface, FDMA requires more number of frequency bands. This becomes difficult to achieve as the system scales and the number of cores increase. Therefore, a FDMA protocol along with a 4-phased repetitive multi-band architecture is envisioned in this work. The phase-based protocol allows multiple wireless links to be active at a time, the phase-based protocol along with the FDMA protocol provides a reliable data transfer between cores with lesser number of frequency bands. In this thesis, an architecture with a combination of FDMA and phase-based protocol using point-to-point graphene-based wireless links is proposed. The proposed architecture is also extended for a multichip system. With cycle accurate system-level simulations, it is shown that the proposed architecture provides huge gains in performance and energy-efficiency in data transfer both in NoC based multicore and multichip systems

    A Scalable & Energy Efficient Graphene-Based Interconnection Framework for Intra and Inter-Chip Wireless Communication in Terahertz Band

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    Network-on-Chips (NoCs) have emerged as a communication infrastructure for the multi-core System-on-Chips (SoCs). Despite its advantages, due to the multi-hop communication over the metal interconnects, traditional Mesh based NoC architectures are not scalable in terms of performance and energy consumption. Folded architectures such as Torus and Folded Torus were proposed to improve the performance of NoCs while retaining the regular tile-based structure for ease of manufacturing. Ultra-low-latency and low-power express channels between communicating cores have also been proposed to improve the performance of conventional NoCs. However, the performance gain of these approaches is limited due to metal/dielectric based interconnection. Many emerging interconnect technologies such as 3D integration, photonic, Radio Frequency (RF), and wireless interconnects have been envisioned to alleviate the issues of a metal/dielectric interconnect system. However, photonic and RF interconnects need the additional physically overlaid optical waveguides or micro-strip transmission lines to enable data transmission across the NoC. Several on-chip antennas have shown to improve energy efficiency and bandwidth of on-chip data communications. However, the date rates of the mm-wave wireless channels are limited by the state-of-the-art power-efficient transceiver design. Recent research has brought to light novel graphene based antennas operating at THz frequencies. Due to the higher operating frequencies compared to mm-wave transceivers, the data rate that can be supported by these antennas are significantly higher. Higher operating frequencies imply that graphene based antennas are just hundred micrometers in size compared to dimensions in the range of a millimeter of mm-wave antennas. Such reduced dimensions are suitable for integration of several such transceivers in a single NoC for relatively low overheads. In this work, to exploit the benefits of a regular NoC structure in conjunction with emerging Graphene-based wireless interconnect. We propose a toroidal folding based NoC architecture. The novelty of this folding based approach is that we are using low power, high bandwidth, single hop direct point to point wireless links instead of multihop communication that happens through metallic wires. We also propose a novel phased based communication protocol through which multiple wireless links can be made active at a time without having any interference among the transceiver. This offers huge gain in terms of performance as compared to token based mechanism where only a single wireless link can be made active at a time. We also propose to extend Graphene-based wireless links to enable energy-efficient, phase-based chip-to-chip communication to create a seamless, wireless interconnection fabric for multichip systems as well. Through cycle-accurate system-level simulations, we demonstrate that such designs with torus like folding based on THz links instead of global wires along with the proposed phase based multichip systems. We provide estimates that they are able to provide significant gains (about 3 to 4 times better in terms of achievable bandwidth, packet latency and average packet energy when compared to wired system) in performance and energy efficiency in data transfer in a NoC as well as multichip system. Thus, realization of these kind of interconnection framework that could support high data rate links in Tera-bits-per-second that will alleviate the capacity limitations of current interconnection framework

    Discrete Load Balancing in Heterogeneous Networks with a Focus on Second-Order Diffusion

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    In this paper we consider a wide class of discrete diffusion load balancing algorithms. The problem is defined as follows. We are given an interconnection network and a number of load items, which are arbitrarily distributed among the nodes of the network. The goal is to redistribute the load in iterative discrete steps such that at the end each node has (almost) the same number of items. In diffusion load balancing nodes are only allowed to balance their load with their direct neighbors. We show three main results. Firstly, we present a general framework for randomly rounding the flow generated by continuous diffusion schemes over the edges of a graph in order to obtain corresponding discrete schemes. Compared to the results of Rabani, Sinclair, and Wanka, FOCS'98, which are only valid w.r.t. the class of homogeneous first order schemes, our framework can be used to analyze a larger class of diffusion algorithms, such as algorithms for heterogeneous networks and second order schemes. Secondly, we bound the deviation between randomized second order schemes and their continuous counterparts. Finally, we provide a bound for the minimum initial load in a network that is sufficient to prevent the occurrence of negative load at a node during the execution of second order diffusion schemes. Our theoretical results are complemented with extensive simulations on different graph classes. We show empirically that second order schemes, which are usually much faster than first order schemes, will not balance the load completely on a number of networks within reasonable time. However, the maximum load difference at the end seems to be bounded by a constant value, which can be further decreased if first order scheme is applied once this value is achieved by second order scheme.Comment: Full version of paper submitted to ICDCS 201

    Visual data flow programming languages challenges and opportunities

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