Macro-Driven Circuit Design Methodology for High-Performance Datapaths

Datapath design is one of the most critical elements in the design of a high performance microprocessor. However datapath design is typically done manually, and is often custom style. This adversely impacts the overall productivity of the design team, as well as the quality of the design. In spite of this, very little automation has been available to the designers of high performance datapaths. In this paper we present a new "macrodriven " approach to the design of datapath circuits. Our approach, referred to as SMART (Smart Macro Design Advisor), is based on automatic generation of regular datapath components such as muxes, comparators, adders etc., which we refer to as datapath macros. The generated solution is based on designer provided constraints such as delay, load and slope, and is optimized for a designer provided cost metric such as power, area. Results on datapath circuits of a high-performance microprocessor show that this approach is very effective for both designer productivity as well as design quality

Synthesis Of Self-resetting Stage Logic Pipelines

As designers began to pack multi-million transistors onto a single chip, their reliance on a global clocking signal to orchestrate the operations of the chip has started to face almost insurmountable difficulties. As a result, designers started to explore clockless circuits to avoid the global clocking problem. Recently, self-resetting circuits implemented in dynamic logic families have been proposed as viable clockless alternatives. While these circuits can produce excellent performances, they display serious limitations in terms of area cost and power consumption. A middle-of-the-road alternative, which can provide a good performance and avoid the limitations seen in dynamic self-resetting circuits, would be to implement self-resetting behavior in static circuits. This alternative has been introduced recently as Self-Resetting Stage Logic and used to propose three types of clockless pipelines. Experimental studies show that these pipelines have the potential to produce high throughputs with a minimum area overhead if a suitable synthesis methodology is available. This thesis proposes a novel synthesis methodology to design and verify clockless pipelines implemented in SRSL by taking advantage of the maturity of current CAD tools. This methodology formulates the synthesis problem as a combinatorial analytical problem for which a run-time efficient exact solution is difficult to derive. Consequently, a two-phase algorithm is proposed to synthesize these pipelines from gate netlists subject to user-specified constraints. The first phase is a heuristic based on the as-soon-as-possible scheduling strategy in which each gate of the netlist is assigned to a single pipeline stage without violating the period constraint of each pipeline stage. On the other hand, the second phase consists of a heuristic, based on the Kernighan-Lin partitioning strategy, to minimize the number of nets crossing each pair of adjacent pipeline stages. The objective of this optimization is to reduce the number of latches separating pipeline stages since these latches tend to occupy large areas. Experiments conducted on a prototype of the synthesis algorithm reveal that these self-resetting stage logic pipelines can easily reach throughputs higher than 1 GHz. Furthermore, these experiments reveal that the area overhead needed to implement the self-resetting circuitry of these pipelines can be easily amortized over the area of the logic embedded in the pipeline stages. In the overall, the synthesis methods developed for SRSL produce low area overhead pipelines for wide and deep gate netlists while it tends to produce high throughput pipelines for wide and shallow gate netlists. This shows that these pipelines are mostly suitable for coarse-grain datapaths

FUNCTIONING ELEVATED POWER COMPETENCE AND FLEXIBLE CHARGE RECYCLING USING DYNAMIC CIRCUIT TECHNIQUE

In computer circuit style, dynamic logic could be a style methodology in combinatory logic circuits, particularly those enforced in MOS technology. Dynamic circuits square measure wide employed in order to unravel the problems occurred within the information path and therefore the essential components of the microchip. The power consumption is considerably in dynamic circuits thanks to their shift activity. So as to get high-performance dynamic circuits square measure employed in microprocessors as a result of their special options such as speed and space. during this paper, we have a tendency to planned versatile charge utilization style methodology and dynamic circuit choice rule so as to attain high efficiency within the information path. Per the planned methodology the simulation results of the planning show the consumption of the ALU (Arithmetic and Logic Unit) with planned technique is reduced considerably compared to the standard ALU

IMPLEMENTATION HIGH POWER EFFICIENCY AND FLEXIBLE CHARGE RECYCLING USING DYNAMIC CIRCUIT TECHNIQUE

In computer circuit style, dynamic logic could be a style methodology in combinatory logic circuits, particularly those enforced in MOS technology. Dynamic circuits square measure wide employed in order to unravel the problems occurred within the information path and therefore the essential components of the microchip. The power consumption is considerably in dynamic circuits thanks to their shift activity. So as to get high-performance dynamic circuits square measure employed in microprocessors as a result of their special options such as speed and space. during this paper, we have a tendency to planned versatile charge utilization style methodology and dynamic circuit choice rule so as to attain high efficiency within the information path. Per the planned methodology the simulation results of the planning show the consumption of the ALU (Arithmetic and Logic Unit) with planned technique is reduced considerably compared to the standard ALU

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

Dataflow development of medium-grained parallel software

PhD ThesisIn the 1980s, multiple-processor computers (multiprocessors) based on conven- tional processing elements emerged as a popular solution to the continuing demand for ever-greater computing power. These machines offer a general-purpose parallel processing platform on which the size of program units which can be efficiently executed in parallel - the "grain size" - is smaller than that offered by distributed computing environments, though greater than that of some more specialised architectures. However, programming to exploit this medium-grained parallelism remains difficult. Concurrent execution is inherently complex, yet there is a lack of programming tools to support parallel programming activities such as program design, implementation, debugging, performance tuning and so on. In helping to manage complexity in sequential programming, visual tools have often been used to great effect, which suggests one approach towards the goal of making parallel programming less difficult. This thesis examines the possibilities which the dataflow paradigm has to offer as the basis for a set of visual parallel programming tools, and presents a dataflow notation designed as a framework for medium-grained parallel programming. The implementation of this notation as a programming language is discussed, and its suitability for the medium-grained level is examinedScience and Engineering Research Council of Great Britain EC ERASMUS schem

Timing-Error Tolerance Techniques for Low-Power DSP: Filters and Transforms

Low-power Digital Signal Processing (DSP) circuits are critical to commercial System-on-Chip design for battery powered devices. Dynamic Voltage Scaling (DVS) of digital circuits can reclaim worst-case supply voltage margins for delay variation, reducing power consumption. However, removing static margins without compromising robustness is tremendously challenging, especially in an era of escalating reliability concerns due to continued process scaling. The Razor DVS scheme addresses these concerns, by ensuring robustness using explicit timing-error detection and correction circuits. Nonetheless, the design of low-complexity and low-power error correction is often challenging. In this thesis, the Razor framework is applied to fixed-precision DSP filters and transforms. The inherent error tolerance of many DSP algorithms is exploited to achieve very low-overhead error correction. Novel error correction schemes for DSP datapaths are proposed, with very low-overhead circuit realisations. Two new approximate error correction approaches are proposed. The first is based on an adapted sum-of-products form that prevents errors in intermediate results reaching the output, while the second approach forces errors to occur only in less significant bits of each result by shaping the critical path distribution. A third approach is described that achieves exact error correction using time borrowing techniques on critical paths. Unlike previously published approaches, all three proposed are suitable for high clock frequency implementations, as demonstrated with fully placed and routed FIR, FFT and DCT implementations in 90nm and 32nm CMOS. Design issues and theoretical modelling are presented for each approach, along with SPICE simulation results demonstrating power savings of 21 – 29%. Finally, the design of a baseband transmitter in 32nm CMOS for the Spectrally Efficient FDM (SEFDM) system is presented. SEFDM systems offer bandwidth savings compared to Orthogonal FDM (OFDM), at the cost of increased complexity and power consumption, which is quantified with the first VLSI architecture