Present-day Machines Research Articles

A Generalized Block-Matrix Circuit for Closed-Loop Analog In-Memory Computing

Matrix-based computing is ubiquitous in an increasing number of present-day machine learning applications such as neural networks, regression and 5G communications. Conventional systems based on von-Neumann architecture are limited by the energy and latency bottleneck induced by the physical separation of the processing and memory units. Inmemory computing (IMC) is a novel paradigm where computation is performed directly within the memory, thus eliminating the need for constant data transfer. IMC has shown exceptional throughput and energy efficiency when coupled with crosspoint arrays of resistive memory devices in open-loop matrix-vector-multiplication and closed-loop inverse-matrix-vector multiplication (IMVM) accelerators. However, each application result in a different circuit topology, thus complicating the development of reconfigurable, general-purpose IMC systems. In this paper, we present a generalized closed-loop IMVM circuit capable of performing any linear matrix operation by proper memory remapping. We derive closed-form equations for the ideal input/ output transfer functions, static error, and dynamic behavior, introducing a novel continuous-time analytical model allowing for orders-of-magnitude simulation speedup with respect to SPICE-based solvers. The proposed circuit represents an ideal candidate for general-purpose accelerators of machine learning.

Evaluating Social Determinants of Health Variables in Advanced Analytic and Artificial Intelligence Models for Cardiovascular Disease Risk and Outcomes: A Targeted Review

Introduction/PurposePredictive models incorporating relevant clinical and social features can provide meaningful insights into complex interrelated mechanisms of cardiovascular disease (CVD) risk and progression and the influence of environmental exposures on adverse outcomes. The purpose of this targeted review (2018–2019) was to examine the extent to which present-day advanced analytics, artificial intelligence, and machine learning models include relevant variables to address potential biases that inform care, treatment, resource allocation, and management of patients with CVD.MethodsPubMed literature was searched using the prespecified inclusion and exclusion criteria to identify and critically evaluate primary studies published in English that reported on predictive models for CVD, associated risks, progression, and outcomes in the general adult population in North America. Studies were then assessed for inclusion of relevant social variables in the model construction. Two independent reviewers screened articles for eligibility. Primary and secondary independent reviewers extracted information from each full-text article for analysis. Disagreements were resolved with a third reviewer and iterative screening rounds to establish consensus. Cohen's kappa was used to determine interrater reliability.ResultsThe review yielded 533 unique records where 35 met the inclusion criteria. Studies used advanced statistical and machine learning methods to predict CVD risk (10, 29%), mortality (19, 54%), survival (7, 20%), complication (10, 29%), disease progression (6, 17%), functional outcomes (4, 11%), and disposition (2, 6%). Most studies incorporated age (34, 97%), sex (34, 97%), comorbid conditions (32, 91%), and behavioral risk factor (28, 80%) variables. Race or ethnicity (23, 66%) and social variables, such as education (3, 9%) were less frequently observed.ConclusionsPredictive models should adjust for race and social predictor variables, where relevant, to improve model accuracy and to inform more equitable interventions and decision making.

The Williams Advanced Pinball Programming Logic Executive Operating System

Pinball has its roots in tabletop games from the late 1800s and early 1900s, although the 1930s marked the true start of pinball as we know it today. Early pinball was an electromechanical game, with points tallied by hand or through the movements of gears. For a while, it looked pretty far from what one would expect based on present-day pinball machines, which are known for their spring-loaded plungers, pair of flippers, bumpers, and drop targets. It was not until 1947 that the first pinball machine with flippers debuted (DeLeon, 2012) and set the precedent for decades to follow.

Turbulence-driven flow dynamics in general axisymmetric toroidal geometry

This work gives the equations governing the generation of toroidally axisymmetric flows by turbulent Reynolds and Maxwell stresses in finite aspect ratio, general cross section tokamak plasmas. Inclusion of the divergence-free flow constraint in the lowest order changes the timescale for evolution of the poloidal flows driven by turbulence by substantial factors. In the pedestal region for the present-day machines, as compared to earlier cylindrical models, the timescale evaluated using a large aspect ratio circular cross section model can be two orders of magnitude longer, while the present, general geometry result can be about one order of magnitude longer. Inclusion of gyroviscosity in the calculation shows that the only lowest order radial velocity fluctuations that enter the problem are those due to fluctuating E ×B flows. Toroidal and poloidal flow effects on the toroidally axisymmetric flows are inextricably coupled due to the neoclassical poloidal viscosity. Accordingly, the physics is inherently three dimensional and measurements of all three-velocity components are required to obtain the information needed to quantitatively test the theory. The parallel and angular momentum equations for the lowest order, toroidally axisymmetric flows look like radial transport equations when the turbulence is included. The turbulence terms provide the radial transport fluxes. In standard neoclassical theory, the parallel flow equation is local on each flux surface; there is no radial derivative term. However, adding turbulence gives a way, in principle, for radial transport to lead to poloidal flows that deviate from the neoclassical prediction. The inclusion of the Maxwell stress provides a mechanism for MHD fluctuations to alter the toroidally axisymmetric flows.

Perceptron Learning and Classification in a Modeled Cortical Pyramidal Cell.

The perceptron learning algorithm and its multiple-layer extension, the backpropagation algorithm, are the foundations of the present-day machine learning revolution. However, these algorithms utilize a highly simplified mathematical abstraction of a neuron; it is not clear to what extent real biophysical neurons with morphologically-extended non-linear dendritic trees and conductance-based synapses can realize perceptron-like learning. Here we implemented the perceptron learning algorithm in a realistic biophysical model of a layer 5 cortical pyramidal cell with a full complement of non-linear dendritic channels. We tested this biophysical perceptron (BP) on a classification task, where it needed to correctly binarily classify 100, 1,000, or 2,000 patterns, and a generalization task, where it was required to discriminate between two “noisy” patterns. We show that the BP performs these tasks with an accuracy comparable to that of the original perceptron, though the classification capacity of the apical tuft is somewhat limited. We concluded that cortical pyramidal neurons can act as powerful classification devices.

Using AI to solve business problems in scholarly publishing

Artificial intelligence (AI) tools are widely used today in many areas, and are now being introduced into scholarly publishing. This article provides a brief overview of present-day AI and machine learning as used for text-based resources such as journal articles and book chapters, and provides an example of its application to identify suitable peer reviewers for manuscript submissions. It describes how one company, UNSILO, has created a tool for this purpose, and the underlying technology used to deliver it. The article also offers a glimpse into a future where AI will profoundly change the way that academic publishing will work.

Studying the effect of the combined technology on durability of the shaft­type parts

Restoration of shaft parts with extending their service life is an important reserve of development and growth of repair efficiency. Improvement of wear resistance and durability of parts of agricultural machinery is a priority trend in the present-day machine building. For this purpose, analysis was carried out and the process of electro-contact strengthening of sprayed wear resistant coatings on shaft parts was considered. Experimental studies of physical and mechanical properties of wear resistant coatings obtained by the combined technology have been carried out. Dependence of the bond strength, porosity of the sprayed wear resistant coatings on current and pressure of the electro-contact strengthening process was established. With an increase in strengthening pressure up to 30‒40 MPa and current up to 14‒16 kA, there was an increase in the bond strength of the sprayed coating up to 180...220 MPa and a decrease in porosity to 2...5 %. Wear resistance of the coatings obtained by the combined technology in the range of the studied loads and speeds was higher than that of the coatings obtained separately by classical technologies of flame and electric arc spraying. The highest wear resistance indicators were found in the coating of FMI-2 material applied by the combined technology. Fatigue strength tests of the strengthened parts have shown that the coatings obtained by the combined technology increased the fatigue limit of the parts recovered by spraying by 20 %, and that of the parts without coatings by 50 %. A comparative estimation of physical-mechanical and operational properties of the coatings obtained by electric arc and flame spraying and the combined technology was made. It was established that the use of electro-contact strengthening of the sprayed wear resistant coatings at a pressure of 20...40 MPa, current strength of 11...16 kA, duration of current pulses and pauses of 0.02...0.04 s significantly increased their physical and mechanical properties and performance.

The Limits of Machine Ethics

Machine Ethics has established itself as a new discipline that studies how to endow autonomous devices with ethical behavior. This paper provides a general framework for classifying the different approaches that are currently being explored in the field of machine ethics and introduces considerations that are missing from the current debate. In particular, law-based codes implemented as external filters for action—which we have named filtered decision making—are proposed as the basis for future developments. The emergence of values as guides for action is discussed, and personal language –together with subjectivity- are indicated as necessary conditions for this development. Last, utilitarian approaches are studied and the importance of objective expression as a requisite for their implementation is stressed. Only values expressed by the programmer in a public language—that is, separate of subjective considerations—can be evolved in a learning machine, therefore establishing the limits of present-day machine ethics.

English

Living organisms like present-day computers and mechatronic machines have two distinct parts; hardware and software. Hardware is the physical part and the software is the programme that has been fed in the hardware to operate it. Limiting the focus of this pioneering research to humans and to animals, it can be shown through physics that a new-born of humans and animals have the instinctive ability to sense danger and comfort and have inbuilt system of identifying friends and foes. Realising any danger, they can raise the alarm to attract attention. All this can be proved through wave theory principles. The time is ripe to show that a super race human beings and a utopian society is possible through application of waves in matchmaking, selecting the right person for the right job, and possibly treating people using waves as medicine. Wave therapy can help improving cultures, societies and attitudes. The author has observed his mother treating patients with different coloured lights. Can the claims of treating illness with the help of ‘medicine waves’ possible? The author developed this theory about 25 years earlier and now publishing it after sufficient research has taken place and possibly this theory can be proved.

Use of machine learning techniques for modeling of snow depth

Snow exerts significant regulating effect on the land hydrological cycle since it controls intensity of heat and water exchange between the soil-vegetative cover and the atmosphere. Estimating of a spring flood runoff or a rain-flood on mountainous rivers requires understanding of the snow cover dynamics on a watershed. In our work, solving a problem of the snow cover depth modeling is based on both available databases of hydro-meteorological observations and easily accessible scientific software that allows complete reproduction of investigation results and further development of this theme by scientific community. In this research we used the daily observational data on the snow cover and surface meteorological parameters, obtained at three stations situated in different geographical regions: Col de Porte (France), Sodankyla (Finland), and Snoquamie Pass (USA). Statistical modeling of the snow cover depth is based on a complex of freely distributed the present-day machine learning models: Decision Trees, Adaptive Boosting, Gradient Boosting. It is demonstrated that use of combination of modern machine learning methods with available meteorological data provides the good accuracy of the snow cover modeling. The best results of snow cover depth modeling for every investigated site were obtained by the ensemble method of gradient boosting above decision trees – this model reproduces well both, the periods of snow cover accumulation and its melting. The purposeful character of learning process for models of the gradient boosting type, their ensemble character, and use of combined redundancy of a test sample in learning procedure makes this type of models a good and sustainable research tool. The results obtained can be used for estimating the snow cover characteristics for river basins where hydro-meteorological information is absent or insufficient.

Performance and power for highly parallel systems

This special issue is the result of an open call for papers initiated after the minisymposium ‘Analysis and Modeling: Techniques and Tools’, conducted at the Society for Industrial and Applied Mathematics (SIAM) Conference on Parallel Processing in Scientific Computing in Savannah, GA, in February 2012. The minisymposium brought together tool developers, performance and power modeling experts, and application analysts to present the state of the art on performance analysis and modeling techniques. This unique combination of expertise is highly needed in a time where complex, hierarchical architectures are the standard for all highly parallel computer systems. Without a good grip on relevant performance limitations, any ptimization attempt is just a shot in the dark. Hence, it is crucial to fully understand the performance properties and bottlenecks that come about with clustered multicore/many-core, multisocket nodes. Another aspect of modern systems is the complicated interplay between power constraints and the need for compute performance, which leads to complicated trade-offs. The challenges ahead are many-fold as systems scale in size. While parallelism is increasing, memory systems, interconnection networks, storage, and uncertainties in programming models all add to the complexities. More rapid realization of energy savings will require significant increases in measurement resolution and optimization techniques. This special issue is focused on how performance and power properties of modern highly parallel systems can be analyzed using state-of-the-art modeling and analysis techniques and real-world applications and tools. G. Hager, J. Treibig, J. Habich, and G. Wellein 1 introduce simple but insightful analytic models for execution performance and energy consumption of multicore CPUs. Automatic dynamic voltage and frequency scaling is leveraged by the “Green Queue” framework presented by J. Peraza, A. Tiwari, M. Laurenzano, L. Carrington, and A. E. Snavely 2 in their article. They show that significant energy savings at low performance loss are in reach if dynamic voltage and frequency scaling is used in an application-aware manner. A. D. Breslow, L. Porter, A. Tiwari, M. Laurenzano, L. Carrington, D. M. Tullsen, and A. E. Snavely 3 investigate the potential of job striping, a technique for co-locating HPC workloads with different characteristics on the same CPU chip, and demonstrate increased throughput and energy efficiency for a mix of typical simulation codes on a production cluster. The problem of how to deal with coarse-grained power measurements is tackled in the paper by H. Servat, G. Llort, J. Giménez, and J. Labarta 4. They present a tool that can derive fine-grained power and performance data for code with quickly alternating phases. The power usage and power variability of workloads on production supercomputers at Los Alamos National Laboratory are studied by S. Pakin, C. Storlie, M. Lang, R. E. Fields, E. E. Romero, C. Idler, S. Michalak, H. Greenberg, J. Loncaric, R. Rheinheimer, G. Grider, and J. Wendelberger in their paper 5. One of their central findings is that real power dissipation under real-world workloads is significantly lower than what the power infrastructure can handle, which opens interesting possibilities for saving cost via power capping. We think that this selection of papers is unique in providing several very different views on the problem of performance and power efficiency on present-day parallel machines from the core to the computing center level.

First disruption studies and simulations in view of the development of the DEMO Physics Basis

In the development of the DEMO Physics Basis an important role is played by the prediction of the plasma disruption features and by the evaluation of the electro-magnetic (EM) and thermal loads associated with these events. Indeed, the kind and number of foreseen plasma disruptions drive the development of the DEMO operation scenarios and the design of vessel and in-vessel components.To characterize a plausible macroscopic plasma dynamics during these events, we will carry out an extrapolation from present-day machines of the main parameters characterizing the disruptions: thermal and current quench time, evolution of plasma current, β and li, safety factor limits, halo current fraction and width, radiated heat fraction. In particular, we will focus on extrapolations for the thermal and current quench characteristic times, due to their importance for the subsequent simulations aimed at the evaluation of the EM and thermal loads. The different options for DEMO design will be taken into account and the possible range of variation of the parameters will be estimated.The 2D axysimmetric MAXFEA and the 3D CarMa0NL codes will be used to evaluate the effects of the induced currents and the EM loads during a disruptive event and to analyze the various design options obtained by the PROCESS code. The results of these simulations, modeled as worst expected events, will be used as input for the system level analysis and design of the vessel and relevant in-vessel components. First simulations with CarMa0NL code including 3D structures are here presented to show the significant effects due to the large access ports.

Memcomputing NP-complete problems in polynomial time using polynomial resources and collective states.

Memcomputing is a novel non-Turing paradigm of computation that uses interacting memory cells (memprocessors for short) to store and process information on the same physical platform. It was recently proven mathematically that memcomputing machines have the same computational power of nondeterministic Turing machines. Therefore, they can solve NP-complete problems in polynomial time and, using the appropriate architecture, with resources that only grow polynomially with the input size. The reason for this computational power stems from properties inspired by the brain and shared by any universal memcomputing machine, in particular intrinsic parallelism and information overhead, namely, the capability of compressing information in the collective state of the memprocessor network. We show an experimental demonstration of an actual memcomputing architecture that solves the NP-complete version of the subset sum problem in only one step and is composed of a number of memprocessors that scales linearly with the size of the problem. We have fabricated this architecture using standard microelectronic technology so that it can be easily realized in any laboratory setting. Although the particular machine presented here is eventually limited by noise-and will thus require error-correcting codes to scale to an arbitrary number of memprocessors-it represents the first proof of concept of a machine capable of working with the collective state of interacting memory cells, unlike the present-day single-state machines built using the von Neumann architecture.

Reflections on the 1951 Fitts List: Do Humans Believe Now that Machines Surpass them?

In 1951, Paul Fitts “surveyed the kinds of things men can do better than present-day machines, and vice versa” and introduced a list of statements, now commonly known as the Fitts list. A criticism sometimes raised with respect to the Fitts list is that it is outdated. Hence, it is important to address the issue of modernity, especially in light of the increasing rate of technological advance. A total of 249 engineering MSc students were asked to indicate whether humans surpass machines or whether machines surpass humans, for each of the 11 statements of the Fitts list, using an electronic voting system. 2,948 respondents from 103 countries did the same via a crowdsourcing facility. The results indicated that present-day machines are considered to surpass humans in respect to detection, perception, and long-term memory while Fitts argued that the opposite held true. However, a closer reading of the 1951 report reveals that some of the supposed disagreements were already anticipated at that time.

Three-dimensional distortions of the tokamak plasma boundary: boundary displacements in the presence of resonant magnetic perturbations

The three-dimensional plasma boundary displacements induced by applied non-axisymmetric magnetic perturbations have been measured in ASDEX Upgrade, DIII-D, JET, MAST and NSTX. The displacements arising from applied resonant magnetic perturbations (RMPs) are measured up to ±5% of the minor radius in present-day machines. Good agreement can be found between different experimental measurements and a range of models—be it vacuum field line tracing, ideal three-dimensional MHD equilibrium modelling, or nonlinear plasma amplification. The agreement of the various experimental measurements with the different predictions from these models is presented, and the regions of applicability of each discussed. The measured displacement of the outboard boundary from various machines is found to correlate approximately linearly with the applied resonant field predicted by vacuum modelling (though it should be emphasized that one should not infer that vacuum modelling accurately predicts the displacement inside the plasma). The RMP-induced displacements foreseen in ITER are expected to lie within the range of those predicted by the different models, meaning less than ±1.75% (±3.5 cm) of the minor radius in the H-mode baseline and less than ±2.5% (±5 cm) in a 9 MA plasma. Whilst a displacement of 7 cm peak-to-peak in the baseline scenario is marginally acceptable from both a plasma control and heat loading perspective, it is important that ITER adopts a plasma control system which can account for a three-dimensional boundary corrugation to avoid an n = 0 correction which would otherwise locally exacerbate the displacement caused by the applied fields.

Towards the conceptual design of the ITER real-time plasma control system

ITER will be the world's largest magnetic confinement tokamak fusion device and is currently under construction in southern France. The ITER Plasma Control System (PCS) is a fundamental component of the ITER Control, Data Access and Communication system (CODAC). It will control the evolution of all plasma parameters that are necessary to operate ITER throughout all phases of the discharge. The design and implementation of the PCS poses a number of unique challenges. The timescales of phenomena to be controlled spans three orders of magnitude, ranging from a few milliseconds to seconds. Novel control schemes, which have not been implemented at present-day machines need to be developed, and control schemes that are only done as demonstration experiments today will have to become routine. In addition, advances in computing technology and available physics models make the implementation of real-time or faster-than-real-time predictive calculations to forecast and subsequently to avoid disruptions or undesired plasma regimes feasible. This requires the PCS design to be adaptable in real-time to the results of these forecasting algorithms. A further novel feature is a sophisticated event handling system, which provides a means to deal with plasma related events (such as MHD instabilities or L-H transitions) or component failure. Finally, the schedule for design and implementation poses another challenge. The beginning of ITER operation will be in late 2020, but the conceptual design activity of the PCS has already commenced as required by the on-going development of diagnostics and actuators in the domestic agencies and the need for integration and testing. This activity is presently underway as a collaboration of international experts and the results will be published as a subsequent publication. In this paper, an overview about the main areas of intervention of the plasma control system will be given as well as a summary of the interfaces and the integration into ITER CODAC (networks, other applications, etc.). The limited amount of commissioning time foreseen for plasma control will make extensive testing and validation necessary. This should be done in an environment that is as close to the PCS version running the machine as possible. Furthermore, the integration with an Integrated Modeling Framework will lead to a versatile tool that can also be employed for pulse validation, control system development and testing as well as the development and validation of physics models. An overview of the requirements and possible structure of such an environment will also be presented.

THE EXPRESSIVE STANCE: INTENTIONALITY, EXPRESSION, AND MACHINE ART

This paper proposes a new interpretive stance for interpreting artistic works and performances that is relevant to artificial intelligence research but also has broader implications. Termed the expressive stance, this stance makes intelligible a critical distinction between present-day machine art and human art, but allows for the possibility that future machine art could find a place alongside our own. The expressive stance is elaborated as a response to Daniel Dennett's notion of the intentional stance, which is critically examined with respect to his specialized concept of rationality. The paper also shows that temporal scale implicitly serves to select between different modes of explanation in prominent theories of intentionality. It also considers the implications of the phenomenological background for systems that produce art.

Energetic particle instabilities in fusion plasmas

Remarkable progress has been made in diagnosing energetic particle instabilities on present-day machines and in establishing a theoretical framework for describing them. This overview describes the much improved diagnostics of Alfvén instabilities and modelling tools developed world-wide, and discusses progress in interpreting the observed phenomena. A multi-machine comparison is presented giving information on the performance of both diagnostics and modelling tools for different plasma conditions outlining expectations for ITER based on our present knowledge.

Avaliação do efeito da granulometria no processo de flotação

A flotação é um dos principais processos de concentração, sendo empregado para diversas classes de minerais (sulfetos, óxidos, silicatos, fosfatos, etc.), como também para uma variedade de tamanhos de partículas. Estudos anteriores mostraram que a flotação pode ser empregada com sucesso para faixas granulométricas entre 10 e 300µm. A seletividade do processo de flotação torna-se muito baixa fora desses limites granulométricos, porque as condições hidrodinâmicas do sistema são incapazes de manter o nível de flotabilidade ideal das partículas. Diferentes tamanhos de partículas são encontrados nos atuais sistemas de flotação, que podem reduzir a seletividade do processo, devido às diferenças de comportamento. Esse trabalho avaliou a flotação em bancada das frações -150+45µm e -45µm em comparação com a fração global -150µm de um minério de ferro itabirítico, sob diferentes condições de pH, dosagens de reagentes e rotação de condicionamento. Os resultados obtidos mostram que essas frações apresentam diferentes comportamentos no processo de flotação, indicando que é possível aumentar a recuperação em massa e a seletividade, quando essas frações são flotadas separadamente.

The ideal home hemodialysis machine

Daily home hemodialysis (HD) patients have a much superior survival rate than patients on regular, 3 times a week in-center HD or on peritoneal dialysis. Present-day HD machines are unsuitable for use at home by patients. We present our concept of the ideal home HD machine that allows daily short and long HD, does all the work preparing for and cleaning up after dialysis, has an intravenous infusion system controlled by the patient, needs no systemic anticoagulation, and teaches and interacts with the patient during dialysis. To fulfill these functionalities, the dialyzer and blood tubing must be integrated with the machine and replaced less often than monthly, the machine must be capable of at least 200 L/week of hemodiafiltration, prepare all fluids necessary between and during dialyses, and all the components and fluids must be much beyond ultrapure.