Self-Learning Hot Data Prediction: Where Echo State Network Meets NAND Flash Memories

© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Well understanding the access behavior of hot data is significant for NAND flash memory due to its crucial impact on the efficiency of garbage collection (GC) and wear leveling (WL), which respectively dominate the performance and life span of SSD. Generally, both GC and WL rely greatly on the recognition accuracy of hot data identification (HDI). However, in this paper, the first time we propose a novel concept of hot data prediction (HDP), where the conventional HDI becomes unnecessary. First, we develop a hybrid optimized echo state network (HOESN), where sufficiently unbiased and continuously shrunk output weights are learnt by a sparse regression based on L2 and L1/2 regularization. Second, quantum-behaved particle swarm optimization (QPSO) is employed to compute reservoir parameters (i.e., global scaling factor, reservoir size, scaling coefficient and sparsity degree) for further improving prediction accuracy and reliability. Third, in the test on a chaotic benchmark (Rossler), the HOESN performs better than those of six recent state-of-the-art methods. Finally, simulation results about six typical metrics tested on five real disk workloads and on-chip experiment outcomes verified from an actual SSD prototype indicate that our HOESN-based HDP can reliably promote the access performance and endurance of NAND flash memories.Peer reviewe

Bifurcations and synchronization using an integrated programmable chaotic circuit

This paper presents a CMOS chip which can act as an autonomous stand-alone unit to generate different real-time chaotic behaviors by changing a few external bias currents. In particular, by changing one of these bias currents, the chip provides different examples of a period-doubling route to chaos. We present experimental orbits and attractors, time waveforms and power spectra measured from the chip. By using two chip units, experiments on synchronization can be carried out as well in real-time. Measurements are presented for the following synchronization schemes: linear coupling, drive-response and inverse system. Experimental statistical characterizations associated to these schemes are also presented. We also outline the possible use of the chip for chaotic encryption of audio signals. Finally, for completeness, the paper includes also a brief description of the chip design procedure and its internal circuitry

Non-Linear Dynamics of a Once-Through Steam Generator

This dissertation presents a new analytical model for the Once-Through Steam Generator (OTSG) which is a component responsible for the primary coolant heat removal and the generation and supply of superheated steam to the turbine of the Pressurized Water Reactor (PWR) manufactured by Babcock & Wilcox (B&W) Co. This new analytical model provides the explanation of the oscillatory phenomenon observed in all PWRs manufactured by B&W that uses the OTSG as part of the steam supply system. It was found that the oscillatory behavior is related to the friction pressure drop caused by the reduction in flow area due to the presence of the metal tube holders. The linear analysis performed has shown a pair of complex conjugate eigenvalues with real negative parts, indicating that the OTSG is stable for small perturbations. The global stability was investigated by the construction of the bifurcation diagram whereby the amplitude of the pressure oscillation was plotted against the friction corrector factor. The bifurcation diagram indicates that the limit cycle is stable within the range of physical values of the friction corrector factor. Power spectral density of the plant data revealed two marked features: a resonance at the frequency of oscillation of the limit cycle and a broadband region preceding the location of the resonance peak. The present model does not reproduce the broadband region. A detailed simulation study of the modulation of the amplitude of a limit cycle both with band limited white noise and chaotic noise has shown that the broadband generated by band limited white noise exhibits a power-law dependence on the frequency whereas the chaotic broadband decreases exponentially with frequency. The broadband obtained in the power spectral density of power plant data presented the latter behavior leading to the conclusion that the OTSG limit cycle is modulated by a chaotic component. Furthermore, the calculation of the Lyapunov exponents using the plant data results in positive values reinforcing the above conclusion. It is also demonstrated in this work that undersampling effects seriously hinder the chaotic signatures. This study has shown that the best criterion to determine the chaotic signature in experimental time series is the frequency dependence of the broadband structure in the signal power spectral density. The originality of this work is two fold. First is the model development that leads to the identification of the causative mechanism for the observed OTSG limit cycle. Second is the novel use of otherwise well established tests in the simulation studies of degraded signals for the identification of chaotic components. The recommendations for future work are the extension of the model to allow for motion of all nodal boundaries rather than just the uppermost nodal limits, study of the interaction between the two steam generators in the plant, study of the dependency of the OTSG model eigenvalues with reactor power, and availability of better quality plant data is stressed

A RECIPE FOR JUMP-LIKE PROGRESS IN SCIENCE – ILLUSTRATED BY 6 EXAMPLES

Does there exist a method to boost scientific and humanitarian progress? Six cases in point are offered. The featured protagonists are: Zwicky, Einstein, Conrad, Reichardt, Szilard and Everett. The six breakthroughs offered are: (1) stationary cosmology (combined with a promising terrestrial fusion technology); (2) global-cgeneral relativity; (3) well-stirred life; (4) Pandaka-pygmaea based brain science; (5) an interactively reared wiser biological intelligence; (6) an experiment proving personalized assignment of the physical world

Persistent Homology of Coarse Grained State Space Networks

This work is dedicated to the topological analysis of complex transitional networks for dynamic state detection. Transitional networks are formed from time series data and they leverage graph theory tools to reveal information about the underlying dynamic system. However, traditional tools can fail to summarize the complex topology present in such graphs. In this work, we leverage persistent homology from topological data analysis to study the structure of these networks. We contrast dynamic state detection from time series using CGSSN and TDA to two state of the art approaches: Ordinal Partition Networks (OPNs) combined with TDA, and the standard application of persistent homology to the time-delay embedding of the signal. We show that the CGSSN captures rich information about the dynamic state of the underlying dynamical system as evidenced by a significant improvement in dynamic state detection and noise robustness in comparison to OPNs. We also show that because the computational time of CGSSN is not linearly dependent on the signal's length, it is more computationally efficient than applying TDA to the time-delay embedding of the time series

Strange nonchaotic attractors in noise driven systems

Strange nonchaotic attractors (SNAs) in noise driven systems are investigated. Before the transition to chaos, due to the effect of noise, a typical trajectory will wander between the periodic attractor and its nearby chaotic saddle in an intermittent way, forms a strange attractor gradually. The existence of SNAs is confirmed by simulation results of various critera both in map and continuous systems. Dimension transition is found and intermittent behavior is studied by peoperties of local Lyapunov exponent. The universality and generalization of this kind of SNAs are discussed and common features are concluded