Computer hardware researchers have perennially focussed on improving the performance of computers while stipulating the energy consumption under a strict budget. While several innovations over the years have led to high performance and energy efficient computers, more challenges have also emerged as a fallout. For example, smaller transistor devices in modern multi-core systems are afflicted with several reliability and security concerns, which were inconceivable even a decade ago. Tackling these bottlenecks happens to negatively impact the power and performance of the computers. This dissertation explores novel techniques to gracefully solve some of the pressing challenges of the modern computer design. Specifically, the proposed techniques improve the reliability of on-chip communication fabric under a high power supply noise, increase the energy-efficiency of low-power graphics processing units, and demonstrate an unprecedented security loophole of the low-power computing paradigm through rigorous hardware-based experiments.

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Rapid scaling of transistor gate sizes has increased the density of on-chip integration and paved the way for heterogeneous many-core systems-on-chip, significantly improving the speed of on-chip processing. The design of the interconnection network of these complex systems is a challenging one and the network-on-chip (NoC) is now the accepted scalable and bandwidth efficient interconnect for multi-processor systems on-chip (MPSoCs). However, the performance enhancements of technology scaling come at the cost of reliability as on-chip components particularly the network-on-chip become increasingly prone to faults. In this thesis, we focus on approaches to deal with the errors caused by such faults. The results of these approaches are obtained not only via time-consuming cycle-accurate simulations but also by analytical approaches, allowing for faster and accurate evaluations, especially for larger networks. Redundancy is the general approach to deal with faults, the mode of which varies according to the type of fault. For the NoC, there exists a classification of faults into transient, intermittent and permanent faults. Transient faults appear randomly for a few cycles and may be caused by the radiation of particles. Intermittent faults are similar to transient faults, however, differing in the fact that they occur repeatedly at the same location, eventually leading to a permanent fault. Permanent faults by definition are caused by wires and transistors being permanently short or open. Generally, spatial redundancy or the use of redundant components is used for dealing with permanent faults. Temporal redundancy deals with failures by re-execution or by retransmission of data while information redundancy adds redundant information to the data packets allowing for error detection and correction. Temporal and information redundancy methods are useful when dealing with transient and intermittent faults. In this dissertation, we begin with permanent faults in NoC in the form of faulty links and routers. Our approach for spatial redundancy adds redundant links in the diagonal direction to the standard rectangular mesh topology resulting in the hexagonal and octagonal NoCs. In addition to redundant links, adaptive routing must be used to bypass faulty components. We develop novel fault-tolerant deadlock-free adaptive routing algorithms for these topologies based on the turn model without the use of virtual channels. Our results show that the hexagonal and octagonal NoCs can tolerate all 2-router and 3-router faults, respectively, while the mesh has been shown to tolerate all 1-router faults. To simplify the restricted-turn selection process for achieving deadlock freedom, we devised an approach based on the channel dependency matrix instead of the state-of-the-art Duato's method of observing the channel dependency graph for cycles. The approach is general and can be used for the turn selection process for any regular topology. We further use algebraic manipulations of the channel dependency matrix to analytically assess the fault resilience of the adaptive routing algorithms when affected by permanent faults. We present and validate this method for the 2D mesh and hexagonal NoC topologies achieving very high accuracy with a maximum error of 1%. The approach is very general and allows for faster evaluations as compared to the generally used cycle-accurate simulations. In comparison, existing works usually assume a limited number of faults to be able to analytically assess the network reliability. We apply the approach to evaluate the fault resilience of larger NoCs demonstrating the usefulness of the approach especially compared to cycle-accurate simulations. Finally, we concentrate on temporal and information redundancy techniques to deal with transient and intermittent faults in the router resulting in the dropping and hence loss of packets. Temporal redundancy is applied in the form of ARQ and retransmission of lost packets. Information redundancy is applied by the generation and transmission of redundant linear combinations of packets known as random linear network coding. We develop an analytic model for flexible evaluation of these approaches to determine the network performance parameters such as residual error rates and increased network load. The analytic model allows to evaluate larger NoCs and different topologies and to investigate the advantage of network coding compared to uncoded transmissions. We further extend the work with a small insight to the problem of secure communication over the NoC. Assuming large heterogeneous MPSoCs with components from third parties, the communication is subject to active attacks in the form of packet modification and drops in the NoC routers. Devising approaches to resolve these issues, we again formulate analytic models for their flexible and accurate evaluations, with a maximum estimation error of 7%.

No / This paper presents a framework for high-level exploration, Register Transfer-Level (RTL) design and rapid prototyping of Network-on-Chip (NoC) architectures. From the high-level exploration, a selected NoC topology is derived, which is then implemented in RTL using an automated design flow. Furthermore, for verification purposes, appropriate self-checking testbenches for the verification of the RTL and architecture files for the semi-automatic implementation of the system in Xilinx EDK are also generated, significantly reducing design and verification time, and therefore Non-Recurring Engineering (NRE) cost. Simulation and FPGA implementation results are given for four case studies multimedia applications, proving the validity of the proposed approach.

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<p>As the number of transistors that are integrated onto a silicon die continues to in- crease, the compute power is becoming a commodity. This has enabled a whole host of new applications that rely on high-throughput computations. Recently, the need for faster and cost-effective applications in form-factor constrained environments has driven an interest in on-chip acceleration of algorithms based on Monte Carlo simula- tions. Though Field Programmable Gate Arrays (FPGAs), with hundreds of on-chip arithmetic units, show significant promise for accelerating these embarrassingly paral- lel simulations, a challenge exists in sharing access to simulation data amongst many concurrent experiments. This thesis presents a compute architecture for accelerating Monte Carlo simulations based on the Network-on-Chip (NoC) paradigm for on-chip communication. We demonstrate through the complete implementation of a Monte Carlo-based image reconstruction algorithm for Single-Photon Emission Computed Tomography (SPECT) imaging that this complex problem can be accelerated by two orders of magnitude on even a modestly-sized FPGA over a 2GHz Intel Core 2 Duo Processor. Futhermore, we have created a framework for further increasing paral- lelism by scaling our architecture across multiple compute devices and by extending our original design to a multi-FPGA system nearly linear increase in acceleration with logic resources was achieved.</p> / Master of Applied Science (MASc)

<p>Accurate analytic models for the area, delay and power of NoC routers realized in FPGA technology are presented. Several router designs are explored, including the demultiplexer-multiplexer design, the broadcast-and-select design, a RAM-based design, and pipelined designs with arbitrary amounts of buffering. The analytic models are compared with extensive experimental results, and shown to be very accurate. Using these router models, accurate analytic models for the area, delay and power of graph-based and hypergraph-based NoC topologies realized in FPGAs are presented, including 2D Mesh, Torus, Binary Hypercube (BHC), Generalized Hypercube (GHC), and Hypermesh. Three traffic patterns are considered, (a) Random-Uniform traffic patterns, (b) traffic patterns in Bitonic sorting algorithm, and (c) traffic patterns in FFT parallel algorithm.</p> <p>The analytic models for NoCs are compared to extensive experimental results and shown to be very accurate, typically within 10%. Using these analytical models, architectural choices such as NoC topology, buffer sizing, crossbar switch design, and degree of pipelining can be explored analytically early in the design-space exploration process. It has been observed that an efficient and accurate early design process results in lower system costs, and in order to come up with feasible designs, early design-space exploration tools are essential.</p> <p>Early design-space exploration tools using analytic models are ideal, as they do not require the generation of detailed logic design in a hardware description language such as VHDL or Verilog. However, to date there are no analytic models for NoCs in FPGAs. This thesis addresses this problem. According to our analytic power models, in an FPGA environment with equal bisection bandwidth the 2D BHC outperforms the 2D Mesh and Torus significantly. For example under equivalent bisection bandwidth, when performing FFT computations in an FPGA environment the 2D BHC consumes 8% of the power of a 2D Mesh, and 15% of the power of a 2D Torus.</p> <p>Hypermeshes are based on the concept of hypergraphs, which consist of a set of nodes and a set of hyperedges, where the hyperedges represent low-latency switches. Under equivalent bisection bandwidth, 2D Hypermesh NoCs outperform the 2D Mesh and Torus significantly. To improve the performance of the Hypermesh, two new hyperedge designs are proposed. We propose the energy-area product as a design metric to compare the NoCs. The energy-area product reflects both the cost and performance design metrics. Our analysis indicates that the 2D Hypermesh NoCs generally have considerably lower area, energy, and energy-area product compared to the 2D Hypercubes. Under equal bisection bandwidth, the area usage of the 2D Hypermesh using the broadcast-and-select designs as the hyperedges uses 30% of the area of the GHC and 42% of the area of the BHC. The energy-area product of the 2D Hypermesh under the FFT algorithm is 9% of the GHC, and 29% of the BHC.</p> / Doctor of Philosophy (PhD)

Network-On-Chip (NoC) architecture forms the new design framework in extending single processor to multiprocessor SoC. Similar to other SoCs and systems, NoCs are also susceptible to Denial of Service (DoS) attacks which degrade the performance by limiting the availability of resources to the processing cores. The stability of NoC is maintained by employing hardware monitors to detect illegal/abnormal activity or by congestion aware arbitration to obfuscate and balance the network load. Typical DoS attack model selects a random target resource and injects multiple flooding flits to reduce its functionality. The random DoS attack will not be practically effective on congestion aware NoC as the flooding path flow changes dynamically based on the congestion in network and the same victim node selection will not be effectual on different traffic profiles. Thus this paper proposes an effective DoS attack model to dynamically synthesize the selection of target node in NoC, arbitrating on congestion information. We describe the design and implementation of the proposed attack model and compare the performance degradation for different synthetic traffic profiles against random target selection. We also put forth a novel design of an effective offline congestion aware routing algorithm by exploiting the advantages of deterministic and adaptive routing. The proposed routing technique showed better latency saturation compared to adaptive (DyAD) and deterministic (OE) protocol.

Multiprocessor system on chip (MPSOC) have strongly emerged in the past decade in communication, multimedia, networking and other embedded domains. MPSOC became a new paradigm of high performance embedded application design. This thesis addresses the design and the physical implementation of a Network on Chip (NoC) based Multiprocessor System on Chip. We studied several aspects at different design stages: high level synthesis, architecture design, FPGA implementation, application evaluation and ASIC physical implementation. We try to analysis and find the impacts of these aspects for the MPSOC's final performance, power consumption and area cost. We implemented a NoC based 16 processors embedded system on FPGA prototyping. Three NoCs provide different functionalities for sixteen PE tiles. We also demonstrated the use of our performance monitoring system for software debugging and tuning. With the bi-synchronous FIFO method, our GALS architecture successfully solves the long clock signal distribution problem and allows that each clock domain can run at its own clock frequency. On the other hand we successfully implemented AES and TDES block cipher cryptographic algorithms on this platform and results show linear speedup in computation time. The network part of our architecture has been implemented on ASIC technology and has been explored with different timing constraints and different library categories of STmicroelectronics' 65nm/45nm technologies. The experimental results of ASIC and FPGA are compared, and we inducted the discussion of technology change impact on parallel programming.