Design automation of approximate circuits with runtime reconfigurable accuracy

Leveraging the inherent error tolerance of a vast number of application domains that are rapidly growing, approximate computing arises as a design alternative to improve the efficiency of our computing systems by trading accuracy for energy savings. However, the requirement for computational accuracy is not fixed. Controlling the applied level of approximation dynamically at runtime is a key to effectively optimize energy, while still containing and bounding the induced errors at runtime. In this paper, we propose and implement an automatic and circuit independent design framework that generates approximate circuits with dynamically reconfigurable accuracy at runtime. The generated circuits feature varying accuracy levels, supporting also accurate execution. Extensive experimental evaluation, using industry strength flow and circuits, demonstrates that our generated approximate circuits improve the energy by up to 41% for 2% error bound and by 17.5% on average under a pessimistic scenario that assumes full accuracy requirement in the 33% of the runtime. To demonstrate further the efficiency of our framework, we considered two state-of-the-art technology libraries which are a 7nm conventional FinFET and an emerging technology that boosts performance at a high cost of increased dynamic power

Comparative Examination of the Olive Mill Wastewater Biodegradation Process by Various Wood-Rot Macrofungi

Olive mill wastewater (OMW) constitutes a major cause of environmental pollution in olive-oil producing regions. Sixty wood-rot macrofungi assigned in 43 species were evaluated for their efficacy to colonize solidified OMW media at initially established optimal growth temperatures. Subsequently eight strains of the following species were qualified: Abortiporus biennis, Ganoderma carnosum, Hapalopilus croceus, Hericium erinaceus, Irpex lacteus, Phanerochaete chrysosporium, Pleurotus djamor, and P. pulmonarius. Fungal growth in OMW (25%v/v in water) resulted in marked reduction of total phenolic content, which was significantly correlated with the effluent's decolorization. A. biennis was the best performing strain (it decreased phenolics by 92% and color by 64%) followed by P. djamor and I. lacteus. Increase of plant seeds germination was less pronounced evidencing that phenolics are only partly responsible for OMW's phytotoxicity. Laccase production was highly correlated with all three biodegradation parameters for H. croceus, Ph. chrysosporium, and Pleurotus spp., and so were manganese-independent and manganese dependent peroxidases for A. biennis and I. lacteus. Monitoring of enzymes with respect to biomass production indicated that Pleurotus spp., H. croceus, and Ph. chrysosporium shared common patterns for all three activities. Moreover, generation of enzymes at the early biodegradation stages enhanced the efficiency of OMW treatment

The EU regulatory framework for green bonds

Κατά τις τελευταίες δεκαετίες, η βιωσιμότητα λαμβάνει προτεραιότητα στους πολιτικούς στόχους πολλών κρατών αλλά και διεθνών οργανισμών. Για την επίτευξη ωστόσο της πράσινης μετάβασης, κρίνεται αναγκαία η λήψη μεγάλων ποσών χρηματοδότησης. Προς το σκοπό αυτόν, η ιδιωτική οικονομία έχει αναπτύξει νέα μέσα χρηματοδότησης, συμπεριλαμβανομένων των πράσινων ομολόγων. Η παράλληλη ύπαρξη ωστόσο περισσότερων ιδιωτικών προτύπων ως προς τον χαρακτηρισμό ενός ομολόγου ως "πράσινου" εγείρει ενστάσεις αναποτελεσματικότητας ως προς τον τρόπο λειτουργίας του συστήματος. Σκοπός της παρούσας εργασίας είναι να αξιολογήσει την πρόταση Κανονισμού για τη δημιουργία "Πράσινων Ομολόγων ΕΕ" συγκρίνοντάς την και με το υφιστάμενο πλαίσιο ιδιωτικών προτύπων.Over the last decades sustainability has been prioritized by many states and international organizations as well. However, in order to achieve the green transition, it is required to raise large amounts of financing. Toward this end, the private economy has developed new instruments, including green bonds. However, the parallel existence of several private standards regarding the characterization of a bond as "green" raises objections of inefficiency in the way the system operates. The purpose of this paper is to evaluate the proposed Regulation for the creation of "EU Green Bonds" by comparing it with the existing framework of private standards

Co-Design of Approximate Multilayer Perceptron for Ultra-Resource Constrained Printed Circuits

Printed Electronics (PE) exhibits on-demand, extremely low-cost hardware due to its additive manufacturing process, enabling machine learning (ML) applications for domains that feature ultra-low cost, conformity, and non-toxicity requirements that silicon-based systems cannot deliver. Nevertheless, large feature sizes in PE prohibit the realization of complex printed ML circuits. In this work, we present, for the first time, an automated printed-aware software/hardware co-design framework that exploits approximate computing principles to enable ultra-resource constrained printed multilayer perceptrons (MLPs). Our evaluation demonstrates that, compared to the state-of-the-art baseline, our circuits feature on average 6x (5.7x) lower area (power) and less than 1% accuracy loss

Impact of NCFET on Neural Network Accelerators

This is the first work to investigate the impact that Negative Capacitance Field-Effect Transistor (NCFET) brings on the efficiency and accuracy of future Neural Networks (NN). NCFET is at the forefront of emerging technologies, especially after it has become compatible with the existing fabrication process of CMOS. Neural Network inference accelerators are becoming ubiquitous in modern SoCs and there is an ever-increasing demand for tighter and tighter throughput constraints and lower energy consumption. To explore the benefits that NCFET brings to NN inference regarding frequency, energy, and accuracy, we investigate different configurations of the multiply-add (MADD) circuit, which is the core computational unit in any NN accelerator. We demonstrate that, compared to the baseline 7nm FinFET technology, its negative capacitance counterpart reduces the energy by 55%, without any frequency reduction. In addition, it enables leveraging higher computational precision, which results to a considerable improvement in the inference accuracy. Importantly, the achieved accuracy improvement comes also together with a significant energy reduction and without any loss in frequency

Bespoke Approximation of Multiplication-Accumulation and Activation Targeting Printed Multilayer Perceptrons

Printed Electronics (PE) feature distinct and remarkable characteristics that make them a prominent technology for achieving true ubiquitous computing. This is particularly relevant in application domains that require conformal and ultra-low cost solutions, which have experienced limited penetration of computing until now. Unlike silicon-based technologies, PE offer unparalleled features such as non-recurring engineering costs, ultra-low manufacturing cost, and on-demand fabrication of conformal, flexible, non-toxic, and stretchable hardware. However, PE face certain limitations due to their large feature sizes, that impede the realization of complex circuits, such as machine learning classifiers. In this work, we address these limitations by leveraging the principles of Approximate Computing and Bespoke (fully-customized) design. We propose an automated framework for designing ultra-low power Multilayer Perceptron (MLP) classifiers which employs, for the first time, a holistic approach to approximate all functions of the MLP's neurons: multiplication, accumulation, and activation. Through comprehensive evaluation across various MLPs of varying size, our framework demonstrates the ability to enable battery-powered operation of even the most intricate MLP architecture examined, significantly surpassing the current state of the art.Comment: Accepted for publication at the 42th IEEE/ACM International Conference on Computer Aided Design (ICCAD) 2023, San Francisco, US

An analogy based approach for solving target sense verification

International audienceContextualized language models have emerged as a de facto standard in natural language processing due to the vast amount of knowledge they acquire during pretraining. Nonetheless, their ability to solve tasks that require reasoning over this knowledge is limited. Certain tasks can be improved by analogical reasoning over concepts, e.g., understanding the underlying relations in "Man is to Woman as King is to Queen". In this work, we propose a way to formulate target sense verification as an analogy detection task, by transforming the input data into quadruples. We present AB4TSV (Analogy and BERT for TSV), a model that uses BERT to represent the objects in these quadruples combined with a convolutional neural network to decide whether they constitute valid analogies. We test our system on the WiC-TSV evaluation benchmark, and show that it can outperform existing approaches. Our empirical study shows the importance of the input encoding for BERT. This dependence gets alleviated by integrating the axiomatic properties of analogies during training, while preserving performance and improving interpretability

Maximum inspiratory pressure, a surrogate parameter for the assessment of ICU-acquired weakness

<p>Abstract</p> <p>Background</p> <p>Physical examination has been advocated as a primary determinant of ICU-acquired weakness (ICU-AW). The purpose of the study is to investigate ICU-AW development by using Maximum Inspiratory Pressure (MIP) as a surrogate parameter of the standardized method to evaluate patients' peripheral muscle strength.</p> <p>Methods</p> <p>Seventy-four patients were recruited in the study and prospectively evaluated in a multidisciplinary university ICU towards the appearance of ICU-AW. APACHE II admission score was 16 ± 6 and ICU stay 26 ± 18 days. ICU-AW was diagnosed with the Medical Research Council (MRC) scale for the clinical evaluation of muscle strength. MIP was measured using the unidirectional valve method, independently of the patients' ability to cooperate.</p> <p>Results</p> <p>A significant correlation was found between MIP and MRC (r = 0.68, p < 0.001). Patients that developed ICU-AW (MRC<48) had a longer weaning period compared to non ICU-AW patients (12 ± 14 versus 2 ± 3 days, p < 0.01). A cut-off point of 36 cmH₂O for MIP was defined by ROC curve analysis for ICU-AW diagnosis (88% sensitivity,76% specificity). Patients with MIP below the cut-off point of 36 cmH₂O had a significant greater weaning period (10 ± 14 versus 3 ± 3 days, p = 0.004) also shown by Kaplan-Meier analysis (log-rank:8.2;p = 0.004).</p> <p>Conclusions</p> <p>MIP estimated using the unidirectional valve method may be a potential surrogate parameter for the assessment of muscle strength compromise, useful for the early detection of ICU-AW.</p

Tuber pulchrosporum sp. nov., a black truffle of the Aestivum clade (Tuberaceae, Pezizales) from the Balkan peninsula

Knowledge on the diversity of hypogeous sequestrate ascomycetes is still limited in the Balkan Peninsula. A new species of truffle, Tuber pulchrosporum, is described from Greece and Bulgaria. Specimens were collected from habitats dominated by various oak species (i.e. Quercus ilex, Q. coccifera, Q. robur) and other angiosperms. They are morphologically characterised by subglobose, ovoid to irregularly lobed, yellowish-brown to dark brown ascomata, usually with a shallow basal cavity and surface with fissures and small, dense, almost flat, trihedral to polyhedral warts. Ascospores are ellipsoid to subfusiform, uniquely ornamented, crested to incompletely reticulate and are produced in (1–)2–8-spored asci. Hair-like, hyaline to light yellow hyphae protrude from the peridium surface. According to the outcome of ITS rDNA sequence analysis, this species forms a distinct well-supported group in the Aestivum clade, with T. panniferum being the closest phylogenetic taxon