SEMI-AUTOMATIC GENERATION OF LINEAR EVENT EXTRACTION PATTERNS FOR FREE TEXTS // Ученые записки КФУ. Физико-математические науки 2013 том155 N4

В статье описывается автоматизированный подход к построению линейных правил для извлечения событий из неаннотированных текстов. Алгоритм состоит из четырех шагов: автоматическое извлечение потенциальных событий из корпуса неаннотированных документов, кластеризация их с использованием путей в дереве зависимостей, проверка случайно выбранных примеров из каждого кластера и построение линейных правил на основе кластеров, получивших положительную оценку. Проводится сравнение полученных правил с системой, использующей правила, построенные экспертом вручную

X-TIME: An in-memory engine for accelerating machine learning on tabular data with CAMs

Structured, or tabular, data is the most common format in data science. While deep learning models have proven formidable in learning from unstructured data such as images or speech, they are less accurate than simpler approaches when learning from tabular data. In contrast, modern tree-based Machine Learning (ML) models shine in extracting relevant information from structured data. An essential requirement in data science is to reduce model inference latency in cases where, for example, models are used in a closed loop with simulation to accelerate scientific discovery. However, the hardware acceleration community has mostly focused on deep neural networks and largely ignored other forms of machine learning. Previous work has described the use of an analog content addressable memory (CAM) component for efficiently mapping random forests. In this work, we focus on an overall analog-digital architecture implementing a novel increased precision analog CAM and a programmable network on chip allowing the inference of state-of-the-art tree-based ML models, such as XGBoost and CatBoost. Results evaluated in a single chip at 16nm technology show 119x lower latency at 9740x higher throughput compared with a state-of-the-art GPU, with a 19W peak power consumption

SEMI-AUTOMATIC GENERATION OF LINEAR EVENT EXTRACTION PATTERNS FOR FREE TEXTS // Ученые записки КФУ. Физико-математические науки 2013 том155 N4

В статье описывается автоматизированный подход к построению линейных правил для извлечения событий из неаннотированных текстов. Алгоритм состоит из четырех шагов: автоматическое извлечение потенциальных событий из корпуса неаннотированных документов, кластеризация их с использованием путей в дереве зависимостей, проверка случайно выбранных примеров из каждого кластера и построение линейных правил на основе кластеров, получивших положительную оценку. Проводится сравнение полученных правил с системой, использующей правила, построенные экспертом вручную

Tree-based machine learning performed in-memory with memristive analog CAM

Tree-based machine learning techniques, such as Decision Trees and Random Forests, are top performers in several domains as they do well with limited training datasets and offer improved interpretability compared to Deep Neural Networks (DNN). However, while easier to train, they are difficult to optimize for fast inference without accuracy loss in von Neumann architectures due to non-uniform memory access patterns. Recently, we proposed a novel analog, or multi-bit, content addressable memory(CAM) for fast look-up table operations. Here, we propose a design utilizing this as a computational primitive for rapid tree-based inference. Large random forest models are mapped to arrays of analog CAMs coupled to traditional analog random access memory (RAM), and the unique features of the analog CAM enable compression and high performance. An optimized architecture is compared with previously proposed tree-based model accelerators, showing improvements in energy to decision by orders of magnitude for common image classification tasks. The results demonstrate the potential for non-volatile analog CAM hardware in accelerating large tree-based machine learning models

Heterogeneous Distribution of Phospholipid Molecular Species in the Surface Culture of <i>Flammulina velutipes</i>: New Facts about Lipids Containing α-Linolenic Fatty Acid

Mycelial fungi grow as colonies consisting of polar growing hyphae, developing radially from spore or inoculum. Over time, the colony develops, hyphae are subject to various exogenous or endogenous stimuli, and mycelium becomes heterogeneous in growth, gene expression, biosynthesis, and secretion of proteins and metabolites. Although the biochemical and molecular mechanisms of mycelium heterogeneity have been the subject of many studies, the role of lipids in colony development and zonality is still not understood. This work was undertaken to extend our knowledge of mycelium heterogeneity and to answer the question of how different lipid molecular species are distributed in the surface colony of the basidial fungus Flammulina velutipes and how this distribution correlates with its morphology. The heterogeneity in the lipid metabolism and lipid composition of the fungal mycelium was demonstrated. According to the real-time PCR and LC-MS/MS results, the expression of genes of PC metabolism, accumulation of phospholipid classes, and degree of unsaturation of PC and PE increased in the direction from the center to the periphery of the colony. The peripheral zone of the colony was characterized by a higher value of the PC/PE ratio and a higher level of phospholipids esterified by linolenic acid. Considering that the synthesis of phospholipids in fungi occurs in different ways, we also conducted experiments with deuterium-labeled phospholipid precursors and found out that the Kennedy pathway is the predominant route for PC biosynthesis in F. velutipes. The zonal differences in gene expression and lipid composition can be explained by the participation of membrane lipids in polar growth maintenance and regulation

Differentiable Content Addressable Memory with Memristors

Memristors, Flash, and related nonvolatile analog device technologies offer in-memory computing structures operating in the analog domain, such as accelerating linear matrix operations in array structures. These take advantage of analog tunability and large dynamic range. At the other side, content addressable memories (CAM) are fast digital lookup tables which effectively perform nonlinear Boolean logic and return a digital match/mismatch value. Recently, nonvolatile analog CAMs have been presented merging analog storage and analog search operations with digital match/mismatch output. However, CAM blocks cannot easily be inserted within a larger adaptive system due to the challenges of training and learning with binary outputs. Here, a missing link between analog crossbar arrays and CAMs, namely a differentiable content addressable memory (dCAM), is presented. Utilizing nonvolatile memories that act as a “soft” memory with analog outputs, dCAM enables learning and fine-tuning of the memory operation and performance. Four applications are quantitatively evaluated to highlight the capabilities: improved data pattern storage, improved robustness to noise and variability, reduced energy and latency performance, and an application to solving Boolean satisfiability optimization problems. The use of dCAM is envisioned as a core building block of fully differentiable computing systems employing multiple types of analog compute operations and memories

Fluorene functionalised sexithiophenes - utilising intramolecular charge transfer to extend the photocurrent spectrum in organic solar cells

A new series of oligothiophenes bearing electron deficient fluorene units have been prepared and characterised. The materials are functionalised by C8/C11 alkyl chains or triethylene glycol side groups, yet the higher oligomers remain poorly soluble. The absorption characteristics of a sexithiophene analogue (compound 3) have been studied by UV-vis and photoinduced absorption spectroscopy. Photovoltaic cells have been fabricated from blends of 3 and fullerene derivative [6,6]-phenyl-C61 butyric acid methyl ester (PCBM). The photocurrent spectrum of the device matches the absorption spectrum of the sexithiophene system which incorporates an intramolecular charge transfer band arising from the 1,3-dithiole-fluorene units. A modest power conversion efficiency of 0.1% was achieved