Designing Approximate Computing Circuits with Scalable and Systematic Data-Driven Techniques

Semiconductor feature size has been shrinking significantly in the past decades. This decreasing trend of feature size leads to faster processing speed as well as lower area and power consumption. Among these attributes, power consumption has emerged as the primary concern in the design of integrated circuits in recent years due to the rapid increasing demand of energy efficient Internet of Things (IoT) devices. As a result, low power design approaches for digital circuits have become of great attractive in the past few years. To this end, approximate computing in hardware design has emerged as a promising design technique. It provides design opportunities to improve timing and energy efficiency by relaxing computing quality. This technique is feasible because of the error-resiliency of many emerging resource-hungry computational applications such as multimedia processing and machine learning. Thus, it is reasonable to utilize this characteristic to trade an acceptable amount of computing quality for energy saving. In the literature, most prior works on approximate circuit design focus on using manual design strategies to redesign fundamental computational blocks such as adders and multipliers. However, the manual design techniques are not suitable for system level hardware due to much higher design complexity. In order to tackle this challenge, we focus on designing scalable, systematic and general design methodologies that are applicable on any circuits. In this paper, we present two novel approximate circuit design methods based on machine learning techniques. Both methods skip the complicated manual analysis steps and primarily look at the given input-error pattern to generate approximate circuits. Our first work presents a framework for designing compensation block, an essential component in many approximate circuits, based on feature selection. Our second work further extends and optimizes this framework and integrates data-driven consideration into the design. Several case studies on fixed-width multipliers and other approximate circuits are presented to demonstrate the effectiveness of the proposed design methods. The experimental results show that both of the proposed methods are able to automatically and efficiently design low-error approximate circuits

Design and Evaluation of Approximate Logarithmic Multipliers for Low Power Error-Tolerant Applications

In this work, the designs of both non-iterative and iterative approximate logarithmic multipliers (LMs) are studied to further reduce power consumption and improve performance. Non-iterative approximate LMs (ALMs) that use three inexact mantissa adders, are presented. The proposed iterative approximate logarithmic multipliers (IALMs) use a set-one adder in both mantissa adders during an iteration; they also use lower-part-or adders and approximate mirror adders for the final addition. Error analysis and simulation results are also provided; it is found that the proposed approximate LMs with an appropriate number of inexact bits achieve a higher accuracy and lower power consumption than conventional LMs using exact units. Compared with conventional LMs with exact units, the normalized mean error distance (NMED) of 16-bit approximate LMs is decreased by up to 18% and the power-delay product (PDP) has a reduction of up to 37%. The proposed approximate LMs are also compared with previous approximate multipliers; it is found that the proposed approximate LMs are best suitable for applications allowing larger errors, but requiring lower energy consumption and low power. Approximate Booth multipliers fit applications with less stringent power requirements, but also requiring smaller errors. Case studies for error-tolerant computing applications are provided

Design of Energy-Efficient Approximate Arithmetic Circuits

Energy consumption has become one of the most critical design challenges in integrated circuit design. Arithmetic computing circuits, in particular array-based arithmetic computing circuits such as adders, multipliers, squarers, have been widely used. In many cases, array-based arithmetic computing circuits consume a significant amount of energy in a chip design. Hence, reduction of energy consumption of array-based arithmetic computing circuits is an important design consideration. To this end, designing low-power arithmetic circuits by intelligently trading off processing precision for energy saving in error-resilient applications such as DSP, machine learning and neuromorphic circuits provides a promising solution to the energy dissipation challenge of such systems. To solve the chip’s energy problem, especially for those applications with inherent error resilience, array-based approximate arithmetic computing (AAAC) circuits that produce errors while having improved energy efficiency have been proposed. Specifically, a number of approximate adders, multipliers and squarers have been presented in the literature. However, the chief limitation of these designs is their un-optimized processing accuracy, which is largely due to the current lack of systemic guidance for array-based AAAC circuit design pertaining to optimal tradeoffs between error, energy and area overhead. Therefore, in this research, our first contribution is to propose a general model for approximate array-based approximate arithmetic computing to guide the minimization of processing error. As part of this model, the Error Compensation Unit (ECU) is identified as a key building block for a wide range of AAAC circuits. We develop theoretical analysis geared towards addressing two critical design problems of the ECU, namely, determination of optimal error compensation values and identification of the optimal error compensation scheme. We demonstrate how this general AAAC model can be leveraged to derive practical design insights that may lead to optimal tradeoffs between accuracy, energy dissipation and area overhead. To further minimize energy consumption, delay and area of AAAC circuits, we perform ECU logic simplification by introducing don't cares. By applying the proposed model, we propose an approximate 16x16 fixed-width Booth multiplier that consumes 44.85% and 28.33% less energy and area compared with theoretically the most accurate fixed-width Booth multiplier when implemented using a 90nm CMOS standard cell library. Furthermore, it reduces average error, max error and mean square error by 11.11%, 28.11% and 25.00%, respectively, when compared with the best reported approximate Booth multiplier and outperforms the best reported approximate design significantly by 19.10% in terms of the energy-delay-mean square error product (EDE_(ms)). Using the same approach, significant energy consumption, area and error reduction is achieved for a squarer unit, with more than 20.00% EDE_(ms) reduction over existing fixed-width squarer designs. To further reduce error and cost by utilizing extra signatures and don't cares, we demonstrate a 16-bit fixed-width squarer that improves the energy-delay-max error (EDE_(max)) by 15.81%

Multi-Valued Majority Logic Circuits Using Spin Waves

With increasing data sets for processing, there is a requirement to build faster and smaller arithmetic circuits. One of the ways to improve the performance of higher order arithmetic units is to reduce the carry propagation levels. Multi-valued logic enables this by reducing the number of digits required to represent a range of numbers. Area reduction is also obtained through fewer operations and signals required to realise a function. Though theoretically multi-valued logic has these advantages, implementation of the multi-valued logic using CMOS has not been efficient. The main reason is because multi-valued logic is emulated in CMOS using binary switches. Two main approaches are followed in CMOS in implementing multi-valued logic using CMOS. Voltage mode logic, where the logic states are encoded using the node voltages suffer from low noise margins and limitation of radix due to the power supply. Current mode logic, where the branch currents are used to represent the logic levels suffer from high power consumption due to static current flow and requirement of restoration devices. The mindset of the post-CMOS approaches explored so far for multi-valued logic circuit design has been to replace the CMOS switches with their novel nano switches. Hence they too suffer from the same issues as CMOS implementation. Our value proposition is through the use of a truly multi-state device based on electron spin. Spin waves, which are a collection of electron spins of an atom enables multi-valued logic by allowing encoding information in the amplitude and phase of the wave.Another advantage of the spin wave fabric is that the computation is through wave propagation and interference which does not involve any movement of charge. This enables building low energy,smaller and faster multi-valued circuits. In this thesis, implementation of the basic building blocks of multi-valued logic using these novel spin wave based devices is shown. Building of arithmetic circuits like adders using these building blocks have also been demonstrated. To quantify the benefits of spin wave based multi-valued circuits, they are benchmarked with CMOS. For 32-bits, our projected comparisons show a 5X increased performance, 125X area improvement and 1717X power reduction for hexa-decimal spin wave based adders compared to binary CMOS. Similarly there is a 4X increase in performance of hexa-decimal SPWF multiplier compared to CMOS for 16 bits. Finally, we have implemented the I/O circuits for smooth interface between binary CMOS and multi-valued SPWF logic

A Study on Efficient Designs of Approximate Arithmetic Circuits

Approximate computing is a popular field where accuracy is traded with energy. It can benefit applications such as multimedia, mobile computing and machine learning which are inherently error resilient. Error introduced in these applications to a certain degree is beyond human perception. This flexibility can be exploited to design area, delay and power efficient architectures. However, care must be taken on how approximation compromises the correctness of results. This research work aims to provide approximate hardware architectures with error metrics and design metrics analyzed and their effects in image processing applications. Firstly, we study and propose unsigned array multipliers based on probability statistics and with approximate 4-2 compressors, full adders and half adders. This work deals with a new design approach for approximation of multipliers. The partial products of the multiplier are altered to introduce varying probability terms. Logic complexity of approximation is varied for the accumulation of altered partial products based on their probability. The proposed approximation is utilized in two variants of 16-bit multipliers. Synthesis results reveal that two proposed multipliers achieve power savings of 72% and 38% respectively compared to an exact multiplier. They have better precision when compared to existing approximate multipliers. Mean relative error distance (MRED) figures are as low as 7.6% and 0.02% for the proposed approximate multipliers, which are better than the previous state-of-the-art works. Performance of the proposed multipliers is evaluated with geometric mean filtering application, where one of the proposed models achieves the highest peak signal to noise ratio (PSNR). Second, approximation is proposed for signed Booth multiplication. Approximation is introduced in partial product generation and partial product accumulation circuits. In this work, three multipliers (ABM-M1, ABM-M2, and ABM-M3) are proposed in which the modified Booth algorithm is approximated. In all three designs, approximate Booth partial product generators are designed with different variations of approximation. The approximations are performed by reducing the logic complexity of the Booth partial product generator, and the accumulation of partial products is slightly modified to improve circuit performance. Compared to the exact Booth multiplier, ABM-M1 achieves up to 15% reduction in power consumption with an MRED value of 7.9 × 10-4. ABM-M2 has power savings of up to 60% with an MRED of 1.1 × 10-1. ABM-M3 has power savings of up to 50% with an MRED of 3.4 × 10-3. Compared to existing approximate Booth multipliers, the proposed multipliers ABM-M1 and ABM-M3 achieve up to a 41% reduction in power consumption while exhibiting very similar error metrics. Image multiplication and matrix multiplication are used as case studies to illustrate the high performance of the proposed approximate multipliers. Third, distributed arithmetic based sum of products units approximation is analyzed. Sum of products units are key elements in many digital signal processing applications. Three approximate sum of products models which are based on distributed arithmetic are proposed. They are designed for different levels of accuracy. First model of approximate sum of products achieves an improvement up to 64% on area and 70% on power, when compared to conventional unit. Other two models provide an improvement of 32% and 48% on area and 54% and 58% on power, respectively, with a reduced error rate compared to the first model. Third model achieves MRED and normalized mean error distance (NMED) as low as 0.05% and 0.009%. Performance of approximate units is evaluated with a noisy image smoothing application, where the proposed models are capable of achieving higher PSNR than existing state of the art techniques. Fourth, approximation is applied in division architecture. Two approximation models are proposed for restoring divider. In the first design, approximation is performed at circuit level, where approximate divider cells are utilized in place of exact ones by simplifying the logic equations. In the second model, restoring divider is analyzed strategically and number of restoring divider cells are reduced by finding the portions of divisor and dividend with significant information. An approximation factor $p$ is used in both designs. In model 1, the design with p=8 has a 58% reduction in both area and power consumption compared to exact design, with a Q-MRED of 1.909 × 10-2 and Q-NMED of 0.449 × 10-2. The second model with an approximation factor p=4 has 54% area savings and 62% power savings compared to exact design. The proposed models are found to have better error metrics compared to existing designs, with better performance at similar error values. A change detection image processing application is used for real time assessment of proposed and existing approximate dividers and one of the models achieves a PSNR of 54.27 dB

Towards Verifying Nonlinear Integer Arithmetic

We eliminate a key roadblock to efficient verification of nonlinear integer arithmetic using CDCL SAT solvers, by showing how to construct short resolution proofs for many properties of the most widely used multiplier circuits. Such short proofs were conjectured not to exist. More precisely, we give n^{O(1)} size regular resolution proofs for arbitrary degree 2 identities on array, diagonal, and Booth multipliers and quasipolynomial- n^{O(\log n)} size proofs for these identities on Wallace tree multipliers.Comment: Expanded and simplified with improved result

Pipeline active filter utilizing a booth type multiplier

Multiplier units of the modified Booth decoder and carry-save adder/full adder combination are used to implement a pipeline active filter wherein pixel data is processed sequentially, and each pixel need only be accessed once and multiplied by a predetermined number of weights simultaneously, one multiplier unit for each weight. Each multiplier unit uses only one row of carry-save adders, and the results are shifted to less significant multiplier positions and one row of full adders to add the carry to the sum in order to provide the correct binary number for the product Wp. The full adder is also used to add this product Wp to the sum of products .SIGMA.Wp from preceding multiply units. If m.times.m multiplier units are pipelined, the system would be capable of processing a kernel array of m.times.m weighting factors

Investigating the VLSI Characterization of Parallel Signed Multipliers for RNS Applications Using FPGAs

Signed multiplication is a complex arithmetic operation, which is reflected in its relatively high signal propagation delay, high power dissipation, and large area requirement. High reliability applications such as Cryptography, Residue Number System (RNS) and Digital Signal Processing (DSP)2019;s effective performance is mainly depend on its arithmetic circuit's performance. Trend of using Residue Number System (RNS) instead of Constrain over-whelming Binary representation is promising technique in VLSI Systems and Multiplier is the basic building block of such systems. In this paper we have considered signed Modified Baugh Wooley Multiplier and Modified Booth Encoding (MBE) Multiplier logic for analysis and synthesized on best suited application platform. Analysis has taken account of Delay, Number of Logic Element requirements; Number of Signal Transition for particular sample input and its Power Consumption were analyzed for both Modified Baugh Wooley Multiplier and Modified Booth Encoding Multiplier. Analysis of Multiplier is described in Verilog HDL and Simulated using two different simulators namely Xilinx ISIM and Altera Quartus II. Then for comparative study, both multipliers are synthesized with Xilinx Virtex 7 XCV2000T-2FLG1925 and Altera Cyclone II EP2C35F672C6 and same parameter as discussed above are also evaluated. Booth Recoding provides overall advent of 9.691% in terms of area and approximately 43 % in terms of Delay compared to Modified Baugh Wooley Multiplier implemented using FPGA Technology

PERFORMANCE EVALUATION OF BOOTH AND WALLACE MULTIPLIER USING FIR FILTER

An area-and speed efficient multipliers is proposed in the thesis. the proposed booth and Wallace multipliers shows the tradeoff in the performance evaluation for the fir filter applications. For implementation of fir filter in this paper the adders introduced are carry save adder and carry skip adder. For evaluating the fir filter performance the tested combinations are booth carry save , booth carry skip , Wallace carry save , Wallace carry skip