Designing energy-efficient computing systems using equalization and machine learning

As technology scaling slows down in the nanometer CMOS regime and mobile computing becomes more ubiquitous, designing energy-efficient hardware for mobile systems is becoming increasingly critical and challenging. Although various approaches like near-threshold computing (NTC), aggressive voltage scaling with shadow latches, etc. have been proposed to get the most out of limited battery life, there is still no “silver bullet” to increasing power-performance demands of the mobile systems. Moreover, given that a mobile system could operate in a variety of environmental conditions, like different temperatures, have varying performance requirements, etc., there is a growing need for designing tunable/reconfigurable systems in order to achieve energy-efficient operation. In this work we propose to address the energy- efficiency problem of mobile systems using two different approaches: circuit tunability and distributed adaptive algorithms. Inspired by the communication systems, we developed feedback equalization based digital logic that changes the threshold of its gates based on the input pattern. We showed that feedback equalization in static complementary CMOS logic enabled up to 20% reduction in energy dissipation while maintaining the performance metrics. We also achieved 30% reduction in energy dissipation for pass-transistor digital logic (PTL) with equalization while maintaining performance. In addition, we proposed a mechanism that leverages feedback equalization techniques to achieve near optimal operation of static complementary CMOS logic blocks over the entire voltage range from near threshold supply voltage to nominal supply voltage. Using energy-delay product (EDP) as a metric we analyzed the use of the feedback equalizer as part of various sequential computational blocks. Our analysis shows that for near-threshold voltage operation, when equalization was used, we can improve the operating frequency by up to 30%, while the energy increase was less than 15%, with an overall EDP reduction of ≈10%. We also observe an EDP reduction of close to 5% across entire above-threshold voltage range. On the distributed adaptive algorithm front, we explored energy-efficient hardware implementation of machine learning algorithms. We proposed an adaptive classifier that leverages the wide variability in data complexity to enable energy-efficient data classification operations for mobile systems. Our approach takes advantage of varying classification hardness across data to dynamically allocate resources and improve energy efficiency. On average, our adaptive classifier is ≈100× more energy efficient but has ≈1% higher error rate than a complex radial basis function classifier and is ≈10× less energy efficient but has ≈40% lower error rate than a simple linear classifier across a wide range of classification data sets. We also developed a field of groves (FoG) implementation of random forests (RF) that achieves an accuracy comparable to Convolutional Neural Networks (CNN) and Support Vector Machines (SVM) under tight energy budgets. The FoG architecture takes advantage of the fact that in random forests a small portion of the weak classifiers (decision trees) might be sufficient to achieve high statistical performance. By dividing the random forest into smaller forests (Groves), and conditionally executing the rest of the forest, FoG is able to achieve much higher energy efficiency levels for comparable error rates. We also take advantage of the distributed nature of the FoG to achieve high level of parallelism. Our evaluation shows that at maximum achievable accuracies FoG consumes ≈1.48×, ≈24×, ≈2.5×, and ≈34.7× lower energy per classification compared to conventional RF, SVM-RBF , Multi-Layer Perceptron Network (MLP), and CNN, respectively. FoG is 6.5× less energy efficient than SVM-LR, but achieves 18% higher accuracy on average across all considered datasets

Design and analysis of short word length DSP systems for mobile communication

Recently, many general purpose DSP applications such as Least Mean Squares-Like single-bit adaptive filter algorithms have been developed using the Short Word Length (SWL) technique and have been shown to achieve similar performance as multi-bit systems. A key function in SWL systems is sigma delta modulation (ΣΔM) that operates at an over sampling ratio (OSR), in contrast to the Nyquist rate sampling typically used in conventional multi-bit systems. To date, the analysis of SWL (or single-bit) DSP systems has tended to be performed using high-level tools such as MATLAB, with little work reported relating to their hardware implementation, particularly in Field Programmable Gate Arrays (FPGAs). This thesis explores the hardware implementation of single-bit systems in FPGA using the design and implementation in VHDL of a single-bit ternary FIR-like filter as an illustrative example. The impact of varying OSR and bit-width of the SWL filter has been determined, and a comparison undertaken between the area-performance-power characteristics of the SWL FIR filter compared to its equivalent multi-bit filter. In these experiments, it was found that single-bit FIR-like filter consistently outperforms the multi-bit technique in terms of its area, performance and power except at the highest filter orders analysed in this work. At higher orders, the ΣΔ approach retains its power and performance advantages but exhibits slightly higher chip area. In the second stage of thesis, three encoding techniques called canonical signed digit (CSD), 2’s complement, and Redundant Binary Signed Digit (RBSD) were designed and investigated on the basis of area-performance in FPGA at varying OSR. Simulation results show that CSD encoding technique does not offer any significant improvement as compared to 2’s complement as in multi-bit domain. Whereas, RBSD occupies double the chip area than other two techniques and has poor performance. The stability of the single-bit FIR-like filter mainly depends upon IIR remodulator due to its recursive nature. Thus, we have investigated the stability IIR remodulator and propose a new model using linear analysis and root locus approach that takes into account the widely accepted second order sigma-delta modulator state variable upper bounds. Using proposed model we have found new feedback parameters limits that is a key parameter in single-bit IIR remodulator stability analysis. Further, an analysis of single-bit adaptive channel equalization in MATLAB has been performed, which is intended to support the design and development of efficient algorithm for single-bit channel equalization. A new mathematical model has been derived with all inputs, coefficients and outputs in single-bit domain. The model was simulated using narrowband signals in MATLAB and investigated on the basis of symbol error rate (SER), signal-to-noise ratio (SNR) and minimum mean squared error (MMSE). The results indicate that single-bit adaptive channel equalization is achievable with narrowband signals but that the harsh quantization noise has great impact in the convergence

Bit-Error-Rate-Minimizing Channel Shortening Using Post-FEQ Diversity Combining and a Genetic Algorithm

In advanced wireline or wireless communication systems, i.e., DSL, IEEE 802.11a/g, HIPERLAN/2, etc., a cyclic prefix which is proportional to the channel impulse response is needed to append a multicarrier modulation (MCM) frame for operating the MCM accurately. This prefix is used to combat inter symbol interference (ISI). In some cases, the channel impulse response can be longer than the cyclic prefix (CP). One of the most useful techniques to mitigate this problem is reuse of a Channel Shortening Equalizer (CSE) as a linear preprocessor before the MCM receiver in order to shorten the effective channel length. Channel shortening filter design is a widely examined topic in the literature. Most channel shortening equalizer proposals depend on perfect channel state information (CSI). However, this information may not be available in all situations. In cases where channel state information is not needed, blind adaptive equalization techniques are appropriate. In wireline communication systems (such as DMT), the CSE design is based on maximizing the bit rate, but in wireless systems (OFDM), there is a fixed bit loading algorithm, and the performance metric is Bit Error Rate (BER) minimization. In this work, a CSE is developed for multicarrier and single-carrier cyclic prefixed (SCCP) systems which attempts to minimize the BER. To minimize the BER, a Genetic Algorithm (GA), which is an optimization method based on the principles of natural selection and genetics, is used. If the CSI is shorter than the CP, the equalization can be done by a frequency domain equalizer (FEQ), which is a bank of complex scalars. However, in the literature the adaptive FEQ design has not been well examined. The second phase of this thesis focuses on different types of algorithms for adapting the FEQ and modifying the FEQ architecture to obtain a lower BER. Simulation results show that this modified architecture yields a 20 dB improvement in BER

High-speed equalization and transmission in electrical interconnections

The relentless growth of data traffic and increasing digital signal processing capabilities of integrated circuits (IC) are demanding ever faster chip-to-chip / chip-to-module serial electrical interconnects. As data rates increase, the signal quality after transmission over printed circuit board (PCB) interconnections is severely impaired. Frequency-dependent loss and crosstalk noise lead to a reduced eye opening, a reduced signal-to-noise ratio and an increased inter-symbol interference (ISI). This, in turn, requires the use of improved signal processing or PCB materials, in order to overcome the bandwidth (BW) limitations and to improve signal integrity. By applying an optimal combination of equalizer and receiver electronics together with BW-efficient modulation schemes, the transmission rate over serial electrical interconnections can be pushed further. At the start of this research, most industrial backplane connectors, meeting the IEEE and OIF specifications such as manufactured by e.g. FCI or TE connectivity, had operational capabilities of up to 25 Gb/s. This research was mainly performed under the IWT ShortTrack project. The goal of this research was to increase the transmission speed over electrical backplanes up to 100 Gb/s per channel for next-generation telecom systems and data centers. This requirement greatly surpassed the state-ofthe-art reported in previous publications, considering e.g. 25 Gb/s duobinary and 42.8 Gb/s PAM-4 transmission over a low-loss Megtron 6 electrical backplane using off-line processing. The successful implementation of the integrated transmitter (TX) and receiver (RX) (1) , clearly shows the feasibility of single lane interconnections beyond 80 Gb/s and opens the potential of realizing industrial 100 Gb/s links using a recent IC technology process. Besides the advancement of the state-of-the-art in the field of high-speed transceivers and backplane transmission systems, which led to several academic publications, the output of this work also attracts a lot of attention from the industry, showing the potential to commercialize the developed chipset and technologies used in this research for various applications: not only in high-speed electrical transmission links, but also in high-speed opto-electronic communications such as access, active optical cables and optical backplanes. In this dissertation, the background of this research, an overview of this work and the thesis organization are illustrated in Chapter 1. In Chapter 2, a system level analysis is presented, showing that the channel losses are limiting the transmission speed over backplanes. In order to enhance the serial data rate over backplanes and to eliminate the signal degradation, several technologies are discussed, such as signal equalization and modulation techniques. First, a prototype backplane channel, from project partner FCI, implemented with improved backplane connectors is characterized. Second, an integrated transversal filter as a feed-forward equalizer (FFE) is selected to perform the signal equalization, based on a comprehensive consideration of the backplane channel performance, equalization capabilities, implementation complexity and overall power consumption. NRZ, duobinary and PAM-4 are the three most common modulation schemes for ultra-high speed electrical backplane communication. After a system-level simulation and comparison, the duobinary format is selected due to its high BW efficiency and reasonable circuit complexity. Last, different IC technology processes are compared and the ST microelectronics BiCMOS9MW process (featuring a fT value of over 200 GHz) is selected, based on a trade-off between speed and chip cost. Meanwhile it also has a benefit for providing an integrated microstrip model, which is utilized for the delay elements of the FFE. Chapter 3 illustrates the chip design of the high-speed backplane TX, consisting of a multiplexer (MUX) and a 5-tap FFE. The 4:1 MUX combines four lower rate streams into a high-speed differential NRZ signal up to 100 Gb/s as the FFE input. The 5-tap FFE is implemented with a novel topology for improved testability, such that the FFE performance can be individually characterized, in both frequency- and time-domain, which also helps to perform the coefficient optimization of the FFE. Different configurations for the gain cell in the FFE are compared. The gilbert configuration shows most advantages, in both a good high-frequency performance and an easy way to implement positive / negative amplification. The total chip, including the MUX and the FFE, consumes 750mW from a 2.5V supply and occupies an area of 4.4mm × 1.4 mm. In Chapter 4, the TX chip is demonstrated up to 84 Gb/s. First, the FFE performance is characterized in the frequency domain, showing that the FFE is able to work up to 84 Gb/s using duobinary formats. Second, the combination of the MUX and the FFE is tested. The equalized TX outputs are captured after different channels, for both NRZ and duobinary signaling at speeds from 64 Gb/s to 84 Gb/s. Then, by applying the duobinary RX 2, a serial electrical transmission link is demonstrated across a pair of 10 cm coax cables and across a 5 cm FX-2 differential stripline. The 5-tap FFE compensates a total loss between the TX and the RX chips of about 13.5 dB at the Nyquist frequency, while the RX receives the equalized signal and decodes the duobinary signal to 4 quarter rate NRZ streams. This shows a chip-to-chip data link with a bit error rate (BER) lower than 10−11. Last, the electrical data transmission between the TX and the RX over two commercial backplanes is demonstrated. An error-free, serial duobinary transmission across a commercial Megtron 6, 11.5 inch backplane is demonstrated at 48 Gb/s, which indicates that duobinary outperforms NRZ for attaining higher speed or longer reach backplane applications. Later on, using an ExaMAX® backplane demonstrator, duobinary transmission performance is verified and the maximum allowed channel loss at 40 Gb/s transmission is explored. The eye diagram and BER measurements over a backplane channel up to 26.25 inch are performed. The results show that at 40 Gb/s, a total channel loss up to 37 dB at the Nyquist frequency allows for error-free duobinary transmission, while a total channel loss of 42 dB was overcome with a BER below 10−8. An overview of the conclusions is summarized in Chapter 5, along with some suggestions for further research in this field. (1) The duobinary receiver was developed by my colleague Timothy De Keulenaer, as described in his PhD dissertation. (2) Described in the PhD dissertation of Timothy De Keulenaer

Review of Recent Trends

This work was partially supported by the European Regional Development Fund (FEDER), through the Regional Operational Programme of Centre (CENTRO 2020) of the Portugal 2020 framework, through projects SOCA (CENTRO-01-0145-FEDER-000010) and ORCIP (CENTRO-01-0145-FEDER-022141). Fernando P. Guiomar acknowledges a fellowship from “la Caixa” Foundation (ID100010434), code LCF/BQ/PR20/11770015. Houda Harkat acknowledges the financial support of the Programmatic Financing of the CTS R&D Unit (UIDP/00066/2020).MIMO-OFDM is a key technology and a strong candidate for 5G telecommunication systems. In the literature, there is no convenient survey study that rounds up all the necessary points to be investigated concerning such systems. The current deeper review paper inspects and interprets the state of the art and addresses several research axes related to MIMO-OFDM systems. Two topics have received special attention: MIMO waveforms and MIMO-OFDM channel estimation. The existing MIMO hardware and software innovations, in addition to the MIMO-OFDM equalization techniques, are discussed concisely. In the literature, only a few authors have discussed the MIMO channel estimation and modeling problems for a variety of MIMO systems. However, to the best of our knowledge, there has been until now no review paper specifically discussing the recent works concerning channel estimation and the equalization process for MIMO-OFDM systems. Hence, the current work focuses on analyzing the recently used algorithms in the field, which could be a rich reference for researchers. Moreover, some research perspectives are identified.publishersversionpublishe