Motion estimation and CABAC VLSI co-processors for real-time high-quality H.264/AVC video coding

Real-time and high-quality video coding is gaining a wide interest in the research and industrial community for different applications. H.264/AVC, a recent standard for high performance video coding, can be successfully exploited in several scenarios including digital video broadcasting, high-definition TV and DVD-based systems, which require to sustain up to tens of Mbits/s. To that purpose this paper proposes optimized architectures for H.264/AVC most critical tasks, Motion estimation and context adaptive binary arithmetic coding. Post synthesis results on sub-micron CMOS standard-cells technologies show that the proposed architectures can actually process in real-time 720 × 480 video sequences at 30 frames/s and grant more than 50 Mbits/s. The achieved circuit complexity and power consumption budgets are suitable for their integration in complex VLSI multimedia systems based either on AHB bus centric on-chip communication system or on novel Network-on-Chip (NoC) infrastructures for MPSoC (Multi-Processor System on Chip

Asynchronous Early Output Dual-Bit Full Adders Based on Homogeneous and Heterogeneous Delay-Insensitive Data Encoding

This paper presents the designs of asynchronous early output dual-bit full adders without and with redundant logic (implicit) corresponding to homogeneous and heterogeneous delay-insensitive data encoding. For homogeneous delay-insensitive data encoding only dual-rail i.e. 1-of-2 code is used, and for heterogeneous delay-insensitive data encoding 1-of-2 and 1-of-4 codes are used. The 4-phase return-to-zero protocol is used for handshaking. To demonstrate the merits of the proposed dual-bit full adder designs, 32-bit ripple carry adders (RCAs) are constructed comprising dual-bit full adders. The proposed dual-bit full adders based 32-bit RCAs incorporating redundant logic feature reduced latency and area compared to their non-redundant counterparts with no accompanying power penalty. In comparison with the weakly indicating 32-bit RCA constructed using homogeneously encoded dual-bit full adders containing redundant logic, the early output 32-bit RCA comprising the proposed homogeneously encoded dual-bit full adders with redundant logic reports corresponding reductions in latency and area by 22.2% and 15.1% with no associated power penalty. On the other hand, the early output 32-bit RCA constructed using the proposed heterogeneously encoded dual-bit full adder which incorporates redundant logic reports respective decreases in latency and area than the weakly indicating 32-bit RCA that consists of heterogeneously encoded dual-bit full adders with redundant logic by 21.5% and 21.3% with nil power overhead. The simulation results obtained are based on a 32/28nm CMOS process technology

Latency Optimized Asynchronous Early Output Ripple Carry Adder based on Delay-Insensitive Dual-Rail Data Encoding

Asynchronous circuits employing delay-insensitive codes for data representation i.e. encoding and following a 4-phase return-to-zero protocol for handshaking are generally robust. Depending upon whether a single delay-insensitive code or multiple delay-insensitive code(s) are used for data encoding, the encoding scheme is called homogeneous or heterogeneous delay-insensitive data encoding. This article proposes a new latency optimized early output asynchronous ripple carry adder (RCA) that utilizes single-bit asynchronous full adders (SAFAs) and dual-bit asynchronous full adders (DAFAs) which incorporate redundant logic and are based on the delay-insensitive dual-rail code i.e. homogeneous data encoding, and follow a 4-phase return-to-zero handshaking. Amongst various RCA, carry lookahead adder (CLA), and carry select adder (CSLA) designs, which are based on homogeneous or heterogeneous delay-insensitive data encodings which correspond to the weak-indication or the early output timing model, the proposed early output asynchronous RCA that incorporates SAFAs and DAFAs with redundant logic is found to result in reduced latency for a dual-operand addition operation. In particular, for a 32-bit asynchronous RCA, utilizing 15 stages of DAFAs and 2 stages of SAFAs leads to reduced latency. The theoretical worst-case latencies of the different asynchronous adders were calculated by taking into account the typical gate delays of a 32/28nm CMOS digital cell library, and a comparison is made with their practical worst-case latencies estimated. The theoretical and practical worst-case latencies show a close correlation....Comment: arXiv admin note: text overlap with arXiv:1704.0761

Synthesizing cognition in neuromorphic electronic systems

The quest to implement intelligent processing in electronic neuromorphic systems lacks methods for achieving reliable behavioral dynamics on substrates of inherently imprecise and noisy neurons. Here we report a solution to this problem that involves first mapping an unreliable hardware layer of spiking silicon neurons into an abstract computational layer composed of generic reliable subnetworks of model neurons and then composing the target behavioral dynamics as a “soft state machine” running on these reliable subnets. In the first step, the neural networks of the abstract layer are realized on the hardware substrate by mapping the neuron circuit bias voltages to the model parameters. This mapping is obtained by an automatic method in which the electronic circuit biases are calibrated against the model parameters by a series of population activity measurements. The abstract computational layer is formed by configuring neural networks as generic soft winner-take-all subnetworks that provide reliable processing by virtue of their active gain, signal restoration, and multistability. The necessary states and transitions of the desired high-level behavior are then easily embedded in the computational layer by introducing only sparse connections between some neurons of the various subnets. We demonstrate this synthesis method for a neuromorphic sensory agent that performs real-time context-dependent classification of motion patterns observed by a silicon retina

Exploration and Design of High Performance Variation Tolerant On-Chip Interconnects

Siirretty Doriast

Design Techniques for Energy-Quality Scalable Digital Systems

Energy efficiency is one of the key design goals in modern computing. Increasingly complex tasks are being executed in mobile devices and Internet of Things end-nodes, which are expected to operate for long time intervals, in the orders of months or years, with the limited energy budgets provided by small form-factor batteries. Fortunately, many of such tasks are error resilient, meaning that they can toler- ate some relaxation in the accuracy, precision or reliability of internal operations, without a significant impact on the overall output quality. The error resilience of an application may derive from a number of factors. The processing of analog sensor inputs measuring quantities from the physical world may not always require maximum precision, as the amount of information that can be extracted is limited by the presence of external noise. Outputs destined for human consumption may also contain small or occasional errors, thanks to the limited capabilities of our vision and hearing systems. Finally, some computational patterns commonly found in domains such as statistics, machine learning and operational research, naturally tend to reduce or eliminate errors. Energy-Quality (EQ) scalable digital systems systematically trade off the quality of computations with energy efficiency, by relaxing the precision, the accuracy, or the reliability of internal software and hardware components in exchange for energy reductions. This design paradigm is believed to offer one of the most promising solutions to the impelling need for low-energy computing. Despite these high expectations, the current state-of-the-art in EQ scalable design suffers from important shortcomings. First, the great majority of techniques proposed in literature focus only on processing hardware and software components. Nonetheless, for many real devices, processing contributes only to a small portion of the total energy consumption, which is dominated by other components (e.g. I/O, memory or data transfers). Second, in order to fulfill its promises and become diffused in commercial devices, EQ scalable design needs to achieve industrial level maturity. This involves moving from purely academic research based on high-level models and theoretical assumptions to engineered flows compatible with existing industry standards. Third, the time-varying nature of error tolerance, both among different applications and within a single task, should become more central in the proposed design methods. This involves designing “dynamic” systems in which the precision or reliability of operations (and consequently their energy consumption) can be dynamically tuned at runtime, rather than “static” solutions, in which the output quality is fixed at design-time. This thesis introduces several new EQ scalable design techniques for digital systems that take the previous observations into account. Besides processing, the proposed methods apply the principles of EQ scalable design also to interconnects and peripherals, which are often relevant contributors to the total energy in sensor nodes and mobile systems respectively. Regardless of the target component, the presented techniques pay special attention to the accurate evaluation of benefits and overheads deriving from EQ scalability, using industrial-level models, and on the integration with existing standard tools and protocols. Moreover, all the works presented in this thesis allow the dynamic reconfiguration of output quality and energy consumption. More specifically, the contribution of this thesis is divided in three parts. In a first body of work, the design of EQ scalable modules for processing hardware data paths is considered. Three design flows are presented, targeting different technologies and exploiting different ways to achieve EQ scalability, i.e. timing-induced errors and precision reduction. These works are inspired by previous approaches from the literature, namely Reduced-Precision Redundancy and Dynamic Accuracy Scaling, which are re-thought to make them compatible with standard Electronic Design Automation (EDA) tools and flows, providing solutions to overcome their main limitations. The second part of the thesis investigates the application of EQ scalable design to serial interconnects, which are the de facto standard for data exchanges between processing hardware and sensors. In this context, two novel bus encodings are proposed, called Approximate Differential Encoding and Serial-T0, that exploit the statistical characteristics of data produced by sensors to reduce the energy consumption on the bus at the cost of controlled data approximations. The two techniques achieve different results for data of different origins, but share the common features of allowing runtime reconfiguration of the allowed error and being compatible with standard serial bus protocols. Finally, the last part of the manuscript is devoted to the application of EQ scalable design principles to displays, which are often among the most energy- hungry components in mobile systems. The two proposals in this context leverage the emissive nature of Organic Light-Emitting Diode (OLED) displays to save energy by altering the displayed image, thus inducing an output quality reduction that depends on the amount of such alteration. The first technique implements an image-adaptive form of brightness scaling, whose outputs are optimized in terms of balance between power consumption and similarity with the input. The second approach achieves concurrent power reduction and image enhancement, by means of an adaptive polynomial transformation. Both solutions focus on minimizing the overheads associated with a real-time implementation of the transformations in software or hardware, so that these do not offset the savings in the display. For each of these three topics, results show that the aforementioned goal of building EQ scalable systems compatible with existing best practices and mature for being integrated in commercial devices can be effectively achieved. Moreover, they also show that very simple and similar principles can be applied to design EQ scalable versions of different system components (processing, peripherals and I/O), and to equip these components with knobs for the runtime reconfiguration of the energy versus quality tradeoff