Hybrid computer Monte-Carlo techniques
Hybrid analog-digital computer systems for Monte Carlo method applications
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Hybrid analog-digital computer systems for Monte Carlo method applications
Fast, efficient Fermat number transform used to compute F'(x) analogous to computation of syndrome in conventional decoding scheme. Eliminates polynomial multiplications and reduces number of multiplications in reconstruction of F'(x) to n log (n). Euclidean algorithm used to evaluate F(x) directly, without going through intermediate steps of solving error-locator and error-evaluator polynomials. Algorithm suitable for implementation in very-large-scale integrated circuits.
A system is presented which will reduce analog cardiac performance data and convert the results to digital form for direct entry into a commercial time-shared computer. Circuits are discussed which perform the measurement and digital conversion of instantaneous systolic and diastolic parameters from the analog blood pressure waveform. Digital averaging over a selected number of heart cycles is performed on these measurements, as well as those of flow and heart rate. The determination of average cardiac output and peripheral resistance, including trends, is the end result after processing by digital computer.
Analog-hybrid Monte Carlo method for solving partial differential equation on hybrid computer
An analogy between inelastic strains caused by temperature and those caused by creep is presented in terms of isotropic elasticity. It is shown how the theoretical aspects can be blended with existing finite-element computer programs to exact a piecewise linear solution. The creep effect is determined by using the thermal stress computational approach, if appropriate alterations are made to the thermal expansion of the individual elements. The overall transient solution is achieved by consecutive piecewise linear iterations. The total residue caused by creep is obtained by accumulating creep residues for each iteration and then resubmitting the total residues for each element as an equivalent input. A typical creep law is tested for incremental time convergence. The results indicate that the approach is practical, with a valid indication of the extent of creep after approximately 20 hr of incremental time. The general analogy between body forces and inelastic strain gradients is discussed with respect to how an inelastic problem can be worked as an elastic problem.
As the utility of synthetic aperture radar (SAR) systems increases in autonomous vehicles, satellites, and other power- and space-constrained edge applications, there is a growing need for processors that can form SAR images at low power. In recent years, analog in-memory compute (AIMC) has shown immense promise for accelerating neural networks and other matrix-vector multiplication (MVM) heavy workloads at the edge. Here, in this work, we examine how the polar format algorithm (PFA), a popular SAR image formation algorithm, can be mapped to these AIMC systems. The PFA maps readily onto analog MVMs because it primarily consists of two linear operations: interpolation of frequency-domain data to a Cartesian grid, followed by a 2-D Fourier transform. This work presents two approaches to map the interpolation operation onto MVMs in analog hardware: a chirp transform and a modified form of sinc interpolation. These mappings introduce algorithmic errors, and their effect on the quality of SAR image formation is examined, both quantitatively and qualitatively. In addition, the impact of errors introduced by the analog hardware is explored to determine which approach is optimal under varying assumptions about the underlying analog memory devices and circuits.
DATA CORE, integrated launch area telemetry data system using high speed digital computers and analog or digital display
Computations are carried out of the rates of surface cooling and lateral flow of lavas extruded onto the surfaces of terrestrial planets and the outer planet satellites, and the likely flow morphologies predicted by extrapolation of the laboratory analog results are determined. Results of this approach are presented for the earth, Venus, Mars, the moon, and the silicate flows on Io. The experiments, which involved the spreading of a viscous liquid under gravity in the presence of a solidifying surface crust, revealed a set of four distinct surface morphologies.
One model for computing in the future is ubiquitous, embedded computational devices analogous to embedded electrical motors. Many of these computers will control physical objects and processes. Such hidden computerized environments introduce new safety and correctness concerns whose treatment go beyond present Formal Methods. In particular, one has to begin to speak about Real Space software in analogy with Real Time software. By this we mean, computerized systems which have to meet requirements expressed in the real geometry of space. How to translate such requirements into ordinary software specifications and how to carry out proofs is a major challenge. In this talk we propose a research program based on the use of no-standard analysis. Much detail remains to be carried out. The purpose of the talk is to inform the Formal Methods community that Non-Standard Analysis provides a possible avenue to attack which we believe will be fruitful.
Values of the normal component of induced velocity throughout the entire field of a uniformly loaded r(rotor at high high speed are presented in the form of charts and tables. Many points were found by an electromagnetic analog, details of which are given. Comparisons of computed and analog values for the induced velocity indicate that the latter are sufficiently accurate for engineering purposes.
The techniques of modern optimal control theory were applied to the design of a control system for a supersonic inlet. The inlet control problem was approached as a linear stochastic optimal control problem using as the performance index the expected frequency of unstarts. The details of the formulation of the stochastic inlet control problem are presented. The computational procedures required to obtain optimal controller designs are discussed, and the analytically predicted performance of controllers designed for several different inlet conditions is tabulated. The experimental implementation of the optimal control laws is described, and the experimental results obtained in a supersonic wind tunnel are presented. The control laws were implemented with analog and digital computers. Comparisons are made between the experimental and analytically predicted performance results. Comparisons are also made between the results obtained with continuous analog computer controllers and discrete digital computer versions.
Transistorized real-time computer for transformation of vectorcardiographic data
Rate augmented digital-to-analog converter for computed time-dependent data
Bibliography and summary of methods used in error analysis of hybrid computers
The characteristics of a digital-analog hybrid system composed of a DJS-8 digital computer and a HMJ-200 analog computer are described as well as its applications to simulation research for an automatic flight control system. A hybrid computational example is included to illustrate the application.
Electrochemical random access memory (ECRAM) is an emerging three-terminal nonvolatile memory (NVM) with highly controllable channel conductance which is promising for use as an analog memory (or synapse) in analog in-memory computing (IMC) systems. Energy-efficient analog IMC computing is particularly desirable for power-constrained, high-radiation environments such as satellites. However, little is known about the suitability of ECRAM for use in a total ionizing dose (TID) environment. Here, this work investigates the effect of Co-60 gamma radiation on the channel conductance and noise—two properties critical for analog IMC systems—of a TaO x -based ECRAM up to 17.3 Mrad(SiO 2 ) for both low- and high-channel-conductance state devices. A transient increase in conductance is observed in response to radiation which consists of two elements: an immediate increase in conductivity due to photocurrent and a secondary increase in conductivity, which has a slower rise and saturation and can persist for hours after exposure. This secondary, persistent photoconductivity is attributed to charging caused by hole trapping. These transient effects would not likely occur in a space environment due to the low dose rate compared with this experiment. No permanent change is found in the low conductance state (LCS) following exposure and the minor shift in the high conductance change would be less significant than the regular retention decay in this state. A permanent increase in the random telegraph noise is observed, possibly due to increased traps created in the channel. This work demonstrates that TaO x -based ECRAM is suitable for use in spaceborne analog IMC systems that are subject to significant TID.
In psychophysical studies on human sensitivity to visual motion parallax (MP), the use of computer displays is pervasive. However, a number of potential problems are associated with such displays: cue conflicts arise when observers accommodate to the screen surface, and observer head and body movements are often not reflected in the displays. We investigated observers' sensitivity to depth information in MP (slant, depth order, relative depth) using various real-world displays and their computer-generated analogs. Angle judgments of real-world stimuli were consistently superior to judgments that were based on computer-generated stimuli. Similar results were found for perceived depth order and relative depth. Perceptual competence of observers tends to be underestimated in research that is based on computer generated displays. Such findings cannot be generalized to more realistic viewing situations.
Neural manifolds summarize the intrinsic structure of the information encoded by a population of neurons. Advances in experimental techniques have made simultaneous recordings from multiple brain regions increasingly commonplace, raising the possibility of studying how these manifolds relate across populations. However, when the manifolds are nonlinear and possibly code for multiple unknown variables, it is challenging to extract robust and falsifiable information about their relationships. We introduce a framework, called the method of analogous cycles, for matching topological features of neural manifolds using only observed dissimilarity matrices within and between neural populations. We demonstrate via analysis of simulations and in vivo experimental data that this method can be used to correctly identify multiple shared circular coordinate systems across both stimuli and inferred neural manifolds. Conversely, the method rejects matching features that are not intrinsic to one of the systems. Further, as this method is deterministic and does not rely on dimensionality reduction or optimization methods, it is amenable to direct mathematical investigation and interpretation in terms of the underlying neural activity. We thus propose the method of analogous cycles as a suitable foundation for a theory of cross-population analysis via neural manifolds.