Efficient Connection Allocator in Network-on-Chip

As semiconductor technologies develop, a System-on-Chip (SoC) that integrates all semiconductor intellectual property (IP) cores is suggested and widely used for various applications. A traditional bus interconnection does not support transmitting data between IP cores for high performance. Because of this reason, a Network-on-Chip (NoC) has been suggested to provide an efficient and scalable solution to interconnect among all IP cores. High throughput and low latency have recently become the main important factors of NoC for achieving hard guaranteed real-time systems. In order to guarantee these factors and provide real-time service (i.e., Guaranteed Service, GS), the circuit switching (CS) approach has been widely utilized. The CS approach allocates mutually exclusive paths to transmitting data between different sources and destinations using dedicated NoC resources. However, the exclusive occupancy of the allocated path reduces the efficiency of the overall use of NoC resources. In order to solve this problem, Space-Division-Multiplexing (SDM) and Time-Division-Multiplexing (TDM) techniques have been suggested. SDM implements a circuit switching technique by assigning physically different NoC-links between different connections. Path connections of the SDM technique based on spatial resources assignment do not provide high scalability. In contrast to this, using virtual time slots for a path connection, the TDM technique can share physical links between exclusively established connections, thereby improving NoC path diversity. For all of these mentioned techniques, the factor that significantly impacts the system efficiency or performance scaling is how the path is allocated. In recent years, a dynamic connection allocation approach that can cope with highly dynamic workloads has been gaining attention due to the sudden and diverse demands of applications in real-time systems. There are two groups in the dynamic connection allocation approach. One is a distributed allocation technique, and the other is a centralized allocation technique. While distributed allocation exploits additional logic integrated into the NoC-routers for path search and allocation, the centralized approach makes use of a central unit to manage the path allocation problem. There are several algorithms for the centralized allocation technique. Trellis search-based allocation approach shows the best performance among them. Many algorithms related to centralized connection allocators have been studied extensively during the past decade. However, relatively little attention was paid to methodology in analyzing and evaluating the centralized connection allocation algorithms. In order to further develop the algorithms, it is necessary to understand and evaluate the centralized connection allocator by establishing a new analysis methodology. Thus, this thesis presents a performance analysis methodology for the trellis search-based allocation approach. Firstly, this thesis proposes a system model for analysis. Secondly, performance metrics are defined. Finally, the analysis results of each performance metric related to the trellis search-based allocation approach are presented. Through this analysis, the performance of the trellis search-based allocation approach can be accurately analyzed. Although a simulation is not performed, the upper limit of performance of the trellis search-based allocation approach can also be predicted through the analysis metrics. Additionally, we introduce the general formulation of the trellis search-based path allocation algorithm. The weight values among available paths through the branch metric and path metric are proposed to enable higher performance path connection. Furthermore, according to network size, topology, TDM, interface load delivery, and router internal storage, the performance of trellis search-based path allocation algorithms is also described. In the end, the Application Specific Instruction Processor (ASIP) hardware platform customized for the trellis search-based path allocation algorithm is presented. The shortest available and lowest-cost (SALC) path search algorithm is proposed to improve the success rate of path connection in the ASIP hardware platform. We evaluate the algorithm performance and implementation synthesis results. In order to realize the dynamic connection approach, a short execution cycle of ASIP time is essential. We develop several algorithms to achieve this short execution cycle. The first one is a rectangular region of search algorithm that allows adapting the size and form of path search region according to the particular source-destination positions and considers actual operational constraints. The average execution cycles for searching an optimum path are decreased because the unnecessary region for path-search is excluded. The second one is a path-spreading search algorithm that separates between involved routers and uninvolved routers in path search. The involved routers are selected and spread out from source to destination at each intermediate trellis-search process. The path-search overhead is considerably reduced due to the router involvements. The third one is a three-directional path-spreading search algorithm that eliminates one direction movement among four spreading movements. Because of this reason, the trellis search-based path connection algorithm, which omits the back-tracing process, can be implemented in the ASIP platform. Thus, the whole algorithm execution time can be halved. The last one is a moving regional path search algorithm that significantly reduces computation complexity by selecting a constant dimensional path-search region that affects performance and moving the region from source to destination. The moving regional path search algorithm achieves a considerable decrement of computational complexity.:1 Introduction 1 1.1 NoC-interconnect . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1.2 Thesis outline . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 2 Connection allocation in a Network-on-Chip 7 2.1 Circuit Switching NoCs . . . . . . . . . . . . . . . . . . . . . . . . . . 7 2.1.1 Guaranteed Service in NoCs . . . . . . . . . . . . . . . . . . . 7 2.1.2 Spatial-Division-Multiplexing technique . . . . . . . . . . . . 8 2.1.3 Time-Division-Multiplexing technique . . . . . . . . . . . . . 10 2.2 System architectures employing circuit switching NoCs . . . . . . . . 11 2.2.1 Static and dynamic connection allocation . . . . . . . . . . . 12 2.2.2 Distributed connection allocation technique . . . . . . . . . . 14 2.2.3 Centralized connection allocation technique . . . . . . . . . . 16 2.2.4 Algorithms for centralized connection allocation . . . . . . . . 17 2.2.4.1 Software based run-time path allocation approach . 18 2.2.4.2 Trellis search-based allocation approach . . . . . . . 19 3 Performance analysis methodology for a centralized connection allocator 23 3.1 System model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23 3.2 Performance metrics and analysis methodology . . . . . . . . . . . . 25 3.3 System simulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33 4 Trellis search-based path allocation algorithm 45 4.1 General formulation . . . . . . . . . . . . . . . . . . . . . . . . . . . 45 4.1.1 Trellis graph structure . . . . . . . . . . . . . . . . . . . . . . 45 4.1.2 Survivor path selection criterion . . . . . . . . . . . . . . . . . 52 ix 4.1.2.1 Branch metric and path metric . . . . . . . . . . . . 52 4.1.2.2 The shortest-available and lowest-cost path selection criterion . . . . . . . . . . . . . . . . . . . . . . . . . 53 4.2 Algorithm Properties . . . . . . . . . . . . . . . . . . . . . . . . . . . 55 4.2.1 Network topology . . . . . . . . . . . . . . . . . . . . . . . . 55 4.2.2 Network size . . . . . . . . . . . . . . . . . . . . . . . . . . . 58 4.2.3 Time-Division-Multiplexing . . . . . . . . . . . . . . . . . . . 61 4.2.4 NoC interface load diversity . . . . . . . . . . . . . . . . . . . 63 4.2.5 The internal storage of the router . . . . . . . . . . . . . . . . 66 5 ASIP approach for Trellis search-based connection allocation 73 5.1 System model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73 5.1.1 Trellis search-based ASIP platform architecture . . . . . . . . 74 5.2 Algorithm for improving success rates of path connection . . . . . . . 81 5.2.1 SALC algorithm for Trellis search-based ASIP platform . . . . 81 5.2.2 Performance evaluation of the SALC algorithm . . . . . . . . 88 5.2.2.1 Simulation results . . . . . . . . . . . . . . . . . . . 88 5.2.2.2 Synthesis results . . . . . . . . . . . . . . . . . . . . 91 5.3 Algorithm for reducing path-search time . . . . . . . . . . . . . . . . 93 5.3.1 Rectangular regional path search algorithm . . . . . . . . . . 93 5.3.2 Path-spreading search algorithm . . . . . . . . . . . . . . . . 99 5.3.3 Three directional path-spreading search algorithm . . . . . . 108 5.3.4 Moving regional path search algorithm . . . . . . . . . . . . . 114 5.3.5 Performance evaluation . . . . . . . . . . . . . . . . . . . . . 123 5.3.5.1 Simulation results . . . . . . . . . . . . . . . . . . . 123 5.3.5.2 Synthesis results . . . . . . . . . . . . . . . . . . . . 126 6 Conclusion and Future work 131 6.1 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 131 6.2 Future work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 132 Bibliography 13

Convenient Multiple Directions of Stratification

This paper investigates the use of multiple directions of stratification as a variance reduction technique for Monte Carlo simulations of path-dependent options driven by Gaussian vectors. The precision of the method depends on the choice of the directions of stratification and the allocation rule within each strata. Several choices have been proposed but, even if they provide variance reduction, their implementation is computationally intensive and not applicable to realistic payoffs, in particular not to Asian options with barrier. Moreover, all these previously published methods employ orthogonal directions for multiple stratification. In this work we investigate the use of algorithms producing convenient directions, generally non-orthogonal, combining a lower computational cost with a comparable variance reduction. In addition, we study the accuracy of optimal allocation in terms of variance reduction compared to the Latin Hypercube Sampling. We consider the directions obtained by the Linear Transformation and the Principal Component Analysis. We introduce a new procedure based on the Linear Approximation of the explained variance of the payoff using the law of total variance. In addition, we exhibit a novel algorithm that permits to correctly generate normal vectors stratified along non-orthogonal directions. Finally, we illustrate the efficiency of these algorithms in the computation of the price of different path-dependent options with and without barriers in the Black-Scholes and in the Cox-Ingersoll-Ross markets.Comment: 21 pages, 11 table

Power allocation in multi-hop OFDM transmission systems with amplify-and-forward relaying: A unified approach

In this paper, a unified approach for power allocation (PA) in multi-hop orthogonal frequency division multiplexing (OFDM) amplify-and-forward (AF) relaying systems is presented. In the proposed approach, we consider short and long term individual and total power constraints at the source and relays, and devise low complexity PA algorithms when wireless links are subject to channel path-loss and small-scale Rayleigh fading. To manage the complexity, in the proposed formulations, we adopt a two-stage iterative approach consisting of a power distribution phase among distinct subcarriers, and a power allocation phase among different relays. In particular, aiming at improving the instantaneous rate of multi-hop transmission systems with AF relaying, we develop (i) a near-optimal iterative PA algorithm based on the exact analysis of the received SNR at the destination; (ii) a low complexity suboptimal iterative PA algorithm based on an approximate expression of the received SNR at high-SNR regime; and (iii) a low complexity non-iterative PA scheme with limited performance loss. Simulation results show the superior performance of the proposed power allocation algorithms

Navigation, Path Planning, and Task Allocation Framework For Mobile Co-Robotic Service Applications in Indoor Building Environments

Recent advances in computing and robotics offer significant potential for improved autonomy in the operation and utilization of today’s buildings. Examples of such building environment functions that could be improved through automation include: a) building performance monitoring for real-time system control and long-term asset management; and b) assisted indoor navigation for improved accessibility and wayfinding. To enable such autonomy, algorithms related to task allocation, path planning, and navigation are required as fundamental technical capabilities. Existing algorithms in these domains have primarily been developed for outdoor environments. However, key technical challenges that prevent the adoption of such algorithms to indoor environments include: a) the inability of the widely adopted outdoor positioning method (Global Positioning System - GPS) to work indoors; and b) the incompleteness of graph networks formed based on indoor environments due to physical access constraints not encountered outdoors. The objective of this dissertation is to develop general and scalable task allocation, path planning, and navigation algorithms for indoor mobile co-robots that are immune to the aforementioned challenges. The primary contributions of this research are: a) route planning and task allocation algorithms for centrally-located mobile co-robots charged with spatiotemporal tasks in arbitrary built environments; b) path planning algorithms that take preferential and pragmatic constraints (e.g., wheelchair ramps) into consideration to determine optimal accessible paths in building environments; and c) navigation and drift correction algorithms for autonomous mobile robotic data collection in buildings. The developed methods and the resulting computational framework have been validated through several simulated experiments and physical deployments in real building environments. Specifically, a scenario analysis is conducted to compare the performance of existing outdoor methods with the developed approach for indoor multi-robotic task allocation and route planning. A simulated case study is performed along with a pilot experiment in an indoor built environment to test the efficiency of the path planning algorithm and the performance of the assisted navigation interface developed considering people with physical disabilities (i.e., wheelchair users) as building occupants and visitors. Furthermore, a case study is performed to demonstrate the informed retrofit decision-making process with the help of data collected by an intelligent multi-sensor fused robot that is subsequently used in an EnergyPlus simulation. The results demonstrate the feasibility of the proposed methods in a range of applications involving constraints on both the environment (e.g., path obstructions) and robot capabilities (e.g., maximum travel distance on a single charge). By focusing on the technical capabilities required for safe and efficient indoor robot operation, this dissertation contributes to the fundamental science that will make mobile co-robots ubiquitous in building environments in the near future.PHDCivil EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/143969/1/baddu_1.pd

Computer architecture for efficient algorithmic executions in real-time systems: New technology for avionics systems and advanced space vehicles

Improvements and advances in the development of computer architecture now provide innovative technology for the recasting of traditional sequential solutions into high-performance, low-cost, parallel system to increase system performance. Research conducted in development of specialized computer architecture for the algorithmic execution of an avionics system, guidance and control problem in real time is described. A comprehensive treatment of both the hardware and software structures of a customized computer which performs real-time computation of guidance commands with updated estimates of target motion and time-to-go is presented. An optimal, real-time allocation algorithm was developed which maps the algorithmic tasks onto the processing elements. This allocation is based on the critical path analysis. The final stage is the design and development of the hardware structures suitable for the efficient execution of the allocated task graph. The processing element is designed for rapid execution of the allocated tasks. Fault tolerance is a key feature of the overall architecture. Parallel numerical integration techniques, tasks definitions, and allocation algorithms are discussed. The parallel implementation is analytically verified and the experimental results are presented. The design of the data-driven computer architecture, customized for the execution of the particular algorithm, is discussed

Joint Energy Efficient and QoS-aware Path Allocation and VNF Placement for Service Function Chaining

Service Function Chaining (SFC) allows the forwarding of a traffic flow along a chain of Virtual Network Functions (VNFs, e.g., IDS, firewall, and NAT). Software Defined Networking (SDN) solutions can be used to support SFC reducing the management complexity and the operational costs. One of the most critical issues for the service and network providers is the reduction of energy consumption, which should be achieved without impact to the quality of services. In this paper, we propose a novel resource (re)allocation architecture which enables energy-aware SFC for SDN-based networks. To this end, we model the problems of VNF placement, allocation of VNFs to flows, and flow routing as optimization problems. Thereafter, heuristic algorithms are proposed for the different optimization problems, in order find near-optimal solutions in acceptable times. The performance of the proposed algorithms are numerically evaluated over a real-world topology and various network traffic patterns. The results confirm that the proposed heuristic algorithms provide near optimal solutions while their execution time is applicable for real-life networks.Comment: Extended version of submitted paper - v7 - July 201