The scaling of microchip technologies has enabled large scale systems-on-chip (SoC). Network-on-chip (NoC) research addresses global communication in SoC, involving (i) a move from computation-centric to communication-centric design and (ii) the implementation of scalable communication structures. This survey presents a perspective on existing NoC research. We define the following abstractions: system, network adapter, network, and link to explain and structure the fundamental concepts. First, research relating to the actual network design is reviewed. Then system level design and modeling are discussed. We also evaluate performance analysis techniques. The research shows that NoC constitutes a unification of current trends of intrachip communication rather than an explicit new alternative.

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A survey of research and practices of Network-on-chip

Approximate computing has emerged as a new design paradigm that exploits the inherent error resilience of a wide range of application domains by allowing hardware implementations to forsake exact Boolean equivalence with algorithmic specifications. A slew of manual design techniques for approximate computing have been proposed in recent years, but very little effort has been devoted to design automation. We propose SALSA, a Systematic methodology for Automatic Logic Synthesis of Approximate circuits. Given a golden RTL specification of a circuit and a quality constraint that defines the amount of error that may be introduced in the implementation, SALSA synthesizes an approximate version of the circuit that adheres to the pre-specified quality bounds. We make two key contributions: (i) the rigorous formulation of the problem of approximate logic synthesis, enabling the generation of circuits that are correct by construction, and (ii) mapping the problem of approximate synthesis into an equivalent traditional logic synthesis problem, thereby allowing the capabilities of existing synthesis tools to be fully utilized for approximate logic synthesis. In order to achieve these benefits, SALSA encodes the quality constraints using logic functions called Q-functions, and captures the flexibility that they engender as Approximation Don't Cares (ADCs), which are used for circuit simplification using traditional don't care based optimization techniques. We have implemented SALSA using two off-the-shelf logic synthesis tools — SIS and Synopsys Design Compiler. We automatically synthesize approximate circuits ranging from arithmetic building blocks (adders, multipliers, MAC) to entire datapaths (DCT, FIR, IIR, SAD, FFT Butterfly, Euclidean distance), demonstrating scalability and significant improvements in area (1.1X to 1.85X for tight error constraints, and 1.2X to 4.75X for relaxed error constraints) and power (1.15X to 1.75X for tight error constraints, and 1.3X to 5.25X for relaxed error constraints).

SALSA: systematic logic synthesis of approximate circuits

There is a growing concern about the increasing vulnerability of future computing systems to errors in the underlying hardware. Traditional redundancy techniques are expensive for designing energy-efficient systems that are resilient to high error rates. We present Error Resilient System Architecture (ERSA), a robust system architecture which targets emerging killer applications such as recognition, mining, and synthesis (RMS) with inherent error resilience, and ensures high degrees of resilience at low cost. Using the concept of configurable reliability, ERSA may also be adapted for general-purpose applications that are less resilient to errors (but at higher costs). While resilience of RMS applications to errors in low-order bits of data is well-known, execution of such applications on error-prone hardware significantly degrades output quality (due to high-order bit errors and crashes). ERSA achieves high error resilience to high-order bit errors and control flow errors (in addition to low-order bit errors) using a judicious combination of the following key ideas: 1) asymmetric reliability in many-core architectures; 2) error-resilient algorithms at the core of probabilistic applications; and 3) intelligent software optimizations. Error injection experiments on a multicore ERSA hardware prototype demonstrate that, even at very high error rates of 20 errors/flip-flop/108 cycles (equivalent to 25000 errors/core/s), ERSA maintains 90% or better accuracy of output results, together with minimal impact on execution time, for probabilistic applications such as K-Means clustering, LDPC decoding, and Bayesian network inference. In addition, we demonstrate the effectiveness of ERSA in tolerating high rates of static memory errors that are characteristic of emerging challenges related to SRAM Vccmin problems and erratic bit errors.

ERSA: Error Resilient System Architecture for Probabilistic Applications

Emerging Artificial Synaptic Devices for Neuromorphic Computing

Many applications are inherently resilient to inexactness or approximations in their underlying computations. Approximate circuit design is an emerging paradigm that exploits this inherent resilience to realize hardware implementations that are highly efficient in energy or performance. In this work, we propose Substitute-And-SIMplIfy (SASIMI), a new systematic approach to the design and synthesis of approximate circuits. The key insight behind SASIMI is to identify signal pairs in the circuit that assume the same value with high probability, and substitute one for the other. While these substitutions introduce functional approximations, if performed judiciously, they result in some logic to be eliminated from the circuit while also enabling downsizing of gates on critical paths (simplification), resulting in significant power savings. We propose an automatic synthesis framework that performs substitution and simplification iteratively, while ensuring that a user-specified quality constraint is satisfied. We extend the proposed framework to perform automatic synthesis of quality configurable circuits that can dynamically operate at different accuracy levels depending on application requirements. We used SASIMI to automatically synthesize approximate and quality configurable implementations of a wide range of arithmetic units (Adders, Multipliers, MAC), complex data paths (SAD, FFT butterfly, Euclidean distance) and ISCAS85 benchmarks, using various error metrics such as error rate and average error magnitude. The synthesized approximate circuits demonstrate power improvements of 10%–28% for tight error constraints, and 30%–60% for relaxed error constraints. The quality configurable circuits obtain between 14%–40% improvement in energy in the approximate mode, while incurring no energy overheads in the accurate mode.

Substitute-and-simplify: a unified design paradigm for approximate and quality configurable circuits

Inexact Circuits or circuits in which the accuracy of the output can be traded for energy or delay savings, have been receiving increasing attention of late due to invariable inaccuracies in designs as Moore's law approaches the low nanometer range, and a concomitant growing desire for ultra low energy systems. In this paper, we present a novel design-level technique called probabilistic pruning to realize inexact circuits. Unlike the previous techniques in literature which relied mostly on some form of scaling of operational parameters such as the supply voltage (Vdd) to achieve energy and accuracy tradeoffs, our technique uses pruning of portions of circuits having a lower probability of being active, as the basis for performing architectural modifications resulting in significant savings in energy, delay and area. Our approach yields more savings when compared to any of the conventional voltage scaling schemes, for similar error values. Extensive simulations using this pruning technique in a novel logic synthesis based CAD framework on various architectures of 64-bit adders demonstrate that normalized gains as great as 2×–7.5× in the Energy-Delay-Area product can be obtained, with a relative error percentage as low as 10−6% up to 10%, when compared to corresponding conventionally correct designs.

Energy parsimonious circuit design through probabilistic pruning

Owing to a growing desire to reduce energy consumption and widely anticipated hurdles to the continued technology scaling promised by Moore's law, techniques and technologies such as inexact circuits and probabilistic CMOS (PCMOS) have gained prominence. These radical approaches trade accuracy at the hardware level for significant gains in energy consumption, area, and speed. While holding great promise, their ability to influence the broader milieu of computing is limited due to two shortcomings. First, they were mostly based on ad-hoc hand designs and did not consider algorithmically well-characterized automated design methodologies. Also, existing design approaches were limited to particular layers of abstraction such as physical, architectural and algorithmic or more broadly software. However, it is well-known that significant gains can be achieved by optimizing across the layers. To respond to this need, in this paper, we present an algorithmically well-founded cross-layer co-design framework (CCF) for automatically designing inexact hardware in the form of datapath elements. Specifically adders and multipliers, and show that significant associated gains can be achieved in terms of energy, area, and delay or speed. Our algorithms can achieve these gains with adding any additional hardware overhead. The proposed CCF framework embodies a symbiotic relationship between architecture and logic-layer design through the technique of probabilistic pruning combined with the novel confined voltage scaling technique introduced in this paper, applied at the physical layer. A second drawback of the state of the art with inexact design is the lack of physical evidence established through measuring fabricated ICs that the gains and other benefits that can be achieved are valid. Again, in this paper, we have addressed this shortcoming by using CCF to fabricate a prototype chip implementing inexact data-path elements; a range of 64-bit integer adders whose outputs can be erroneous. Through physical measurements of our prototype chip wherein the inexact adders admit expected relative error magnitudes of 10% or less, we have found that cumulative gains over comparable and fully accurate chips, quantified through the area-delay-energy product, can be a multiplicative factor of 15 or more. As evidence of the utility of these results, we demonstrate that despite admitting error while achieving gains, images processed using the FFT algorithm implemented using our inexact adders are visually discernible.

Algorithmic methodologies for ultra-efficient inexact architectures for sustaining technology scaling

The domain of inexact circuit design, in which accuracy of the circuit can be exchanged for substantial cost (energy, delay, and/or area) savings, has been gathering increasing prominence of late owing to a growing desire for reducing energy consumption of the systems, particularly in the domain of embedded and (portable) multimedia applications. Most of the previous approaches to realizing inexact circuits relied on scaling of circuit parameters (such as supply voltage) taking advantage of an application’s error tolerance to achieve the cost and accuracy trade-offs, thus suffering from acute drawbacks of considerable implementation overheads that significantly reduced the gains. In this article, two novel design approaches called Probabilistic Pruning and Probabilistic Logic Minimization are proposed to realize inexact circuits with zero hardware overhead.Extensive simulations on various architectures of critical datapath elements demonstrate that each of the techniques can independently achieve normalized gains as large as 2x--9.5x in energy-delay-area product for relative error magnitude as low as 10 − 4p--8p compared to corresponding conventional correct circuits.

Synthesizing Parsimonious Inexact Circuits through Probabilistic Design Techniques

Design technology to address the new and vast problem of heterogeneous embedded systems design while remaining compatible with standard More Moore flows, i.e. capable of simultaneously handling both silicon complexity and system complexity, represents one of the most important challenges facing the semiconductor industry today and will be for several years to come. While the micro-electronics industry, over the years and with its spectacular and unique evolution, has built its own specific design methods to focus mainly on the management of complexity through the establishment of abstraction levels, the emergence of device heterogeneity requires new approaches enabling the satisfactory design of physically heterogeneous embedded systems for the widespread deployment of such systems. Heterogeneous Embedded Systems, compiled largely from a set of contributions from participants of past editions of the Winter School on Heterogeneous Embedded Systems Design Technology (FETCH), proposes a necessarily broad and holistic overview of design techniques used to tackle the various facets of heterogeneity in terms of technology and opportunities at the physical level, signal representations and different abstraction levels, architectures and components based on hardware and software, in all the main phases of design (modeling, validation with multiple models of computation, synthesis and optimization). It concentrates on the specific issues at the interfaces, and is divided into two main parts. The first part examines mainly theoretical issues and focuses on the modeling, validation and design techniques themselves. The second part illustrates the use of these methods in various design contexts at the forefront of new technology and architectural developments.

Design Technology for Heterogeneous Embedded Systems

For extremely low-power logic, three very new and promising techniques will be described. The first are methods on circuit and system level for reduced supply voltages. In large logic blocks, interconnect becomes a main issue, that could be solved by on-chip optical interconnect. Nano-devices will also be presented, as a possibility to compute with nearly zero power, and compared to future 10 nanometers transistors.

Christian Piguet

Papers

Energy parsimonious circuit design through probabilistic pruning

Algorithmic methodologies for ultra-efficient inexact architectures for sustaining technology scaling

Synthesizing Parsimonious Inexact Circuits through Probabilistic Design Techniques

Design Technology for Heterogeneous Embedded Systems

Extremely low-power logic