Marius Joldos

Technical University of Cluj-Napoca, Computer Science, Faculty Member

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Papers by Marius Joldos

Perpendicular Magnetic Anisotropy Electric Field Modulation in Magnetron-Sputtered Pt/Co/X/MgO Ultrathin Structures With Chemically Tailored Top Interface

IEEE Transactions on Magnetics, 2021

<italic>Ab initio</italic> calculations of voltage-controlled perpendicular magnetic ... more <italic>Ab initio</italic> calculations of voltage-controlled perpendicular magnetic anisotropy predict that the adjunction of Pt at the top of Co/MgO interface in Pt/Co/MgO ultrathin structures would enhance the perpendicular anisotropy and its electric field (<inline-formula> <tex-math notation="LaTeX">$E$ </tex-math></inline-formula>-field) variation rate. Following these theoretical expectations, using the magnetron-sputtering technique, we first designed and elaborated magnetic multilayered samples which have subsequently been patterned by UV lithography in magnetotransport devices. The as-deposited samples show perpendicular magnetization configuration whose <inline-formula> <tex-math notation="LaTeX">$E$ </tex-math></inline-formula>-field modulation has been studied by anomalous Hall effect magnetometry experiments under applied <inline-formula> <tex-math notation="LaTeX">$E$ </tex-math></inline-formula>-field in patterned devices. The measured voltage anisotropy modulation effect is found to be asymmetric with respect to the <inline-formula> <tex-math notation="LaTeX">$E$ </tex-math></inline-formula>-field polarity, in qualitative agreement with theoretical predictions.

Grid Framework for Parallel Investigations of Spiking Neural Microcircuits

2012 11th International Symposium on Parallel and Distributed Computing, 2012

ABSTRACT Simulation of spiking neural networks is computationally expensive and the employment of... more ABSTRACT Simulation of spiking neural networks is computationally expensive and the employment of multicore processors can boost the performance of such simulations. Designing parallelization strategies that work well for different characteristics of the microcircuits entails expensive computations, leading to increased development times. To speed up the design of multicore software for computational neuroscience, we have developed a framework that exploits multicore systems available in grid computing environments. Due to the use of Grid SFEA plugins, common operations such as evaluation of parallelization strategies can be undertaken with very little effort. We evaluated the plugins for the development of a synchronous multicore spiking neural simulator. This uses the spike response model combined with the phenomenological model of spike time dependent synapse plasticity. The parallelization uses OpenMP, the microcircuits have small world topologies and count up to 104 neurons and 107 synapses with biological details. With this novel framework more complex investigations in computational neuroscience such as analysis of the dynamics of neural microcircuits could be tackled.

Simulation of Biological Neural Microcircuits on Multi-core Systems

2012 Sixth International Conference on Complex, Intelligent, and Software Intensive Systems, 2012

ABSTRACT Our research focuses on the identification and quantification of the impact that multi-c... more ABSTRACT Our research focuses on the identification and quantification of the impact that multi-core parallelization strategies have on the stability of the result of spiking neural networks simulations. We investigated Open MP-based implementations of the Spike Response Model and Spike Time-Dependent Plasticity for studying behaviors of biological neurons and synapses. The underlying neural microcircuits have small-world topologies. The simulation strategy is a synchronous one. The software development methodology we follow makes use of systematic unit testing and continuous integration, giving us a way to verify various perturbations of simulation results. We carried out investigations on systems having different multi-core processors. The processing speed (spikes/second) of our simulator scales well with the number of cores, but the parallel efficiency is moderate when all cores of the system are used in the simulation (0.57 for 12 cores e.g.). The primary outcomes of this work are twofold: One the one hand, the proposed parallel simulation strategies show a dynamic behavior unaltered by the use of multi-core specific technologies. On the other hand, we analyze issues met in our approach to multi-core simulations.

Distributed dynamics analysis of spiking neural network simulations

ABSTRACT In order increase the chance of the adoption of new parallelization strategies and algor... more ABSTRACT In order increase the chance of the adoption of new parallelization strategies and algorithms in the computational neuroscience community, one needs first to quantify qualitatively and quantitatively their impact on the almost chaotic dynamic behavior of neural microcircuit simulations. The analysis of this dynamics behavior is computationally expensive, as a large number of simulation scenarios need to be considered and high-dimensional data sets have to be analyzed. In this work, we proposed an improvement of the dimensionality reduction approach considered in the dynamics analysis methodology. Furthermore, by adding support for distributed processing with MPI to the existing OpenMP-based spiking neural network simulator, we enable the processing of such scenarios on high-performance computing resources. The preliminary results are presented in the paper. They have been obtained at the simulation of small-world neural microcircuits with hybrid parallelization on a Linux cluster with 64 cores. As such, the approach undertaken here provides partial solutions to both challenges outlined above.

Dynamics Analysis of Parallel Simulations of the Spike Response Model

2012 14th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing, 2012

ABSTRACT The impact of parallel simulation strategies on the almost chaotic nature of the behavio... more ABSTRACT The impact of parallel simulation strategies on the almost chaotic nature of the behavior of brain microcircuit simulations is of increasing importance to neuroscience. The challenge here is to design parallel simulation strategies (implementations of biological neural models and simulation loops) that preserve the dynamic behavior of neural microcircuits. In this paper, we present an approach to dynamics analysis based on strong dimensionality reduction and on the Lyapunov exponent method. The parallel implementation of the Spike Response Model relies on OpenMP and scales well when the number of threads matches the number of physical cores. The analysis performed on reduced data sets confirms the dynamic behavior observed in the high dimensional simulation data. As such, this approach is potentially of interest to computational neuroscience research.

MPI-Based Asynchronous Simulation of Spiking Neural Networks on the Grid

2013 15th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing, 2013

ABSTRACT Brain microcircuits exhibit an almost chaotic behavior. This is of high interest in deve... more ABSTRACT Brain microcircuits exhibit an almost chaotic behavior. This is of high interest in developing new computational models or designing high capacity storage systems. Therefore, the simulation of such microcircuits must preserve the brain dynamic behavior. But investigating the dynamics analysis of such systems is a complex computational task due to the large number of neurons and synapses in the network, the large number of simulation scenarios that need to be computed, and to their model representation. To address the first challenge, we propose in this paper an MPI-based parallelization scheme of the asynchronous spiking neural network simulation algorithm. Due to the partitioning method, we can compute scenarios with more than 50.000 neurons and 300 millions synapses. The proposed solution has been evaluated on production HPC systems, employing up to 512 parallel processes. We contribute to the second challenge by extending the fACIBiNET framework with client-side capabilities for the Globus Online service. As such, scenarios with both high-throughput and high-performance computing requirements are managed in an efficient manner from within the framework, using grid technologies.

Host Oriented Factor Normalizing Authentication Resource: More Secure Authentication for Legacy Systems

2019 IEEE 15th International Conference on Intelligent Computer Communication and Processing (ICCP), 2019

Whenever one accesses a computer system there are three essential security issues involved: ident... more Whenever one accesses a computer system there are three essential security issues involved: identification, authentication and authorization. The identification process enables recognition of an entity, which may be either a human, a machine, or another asset – e.g. software program. Two complementary mechanisms are used for determining who can access those systems: authentication and authorization. To address the authentication process, various solutions have been proposed in the literature, from a simple password to newer technologies based on biometrics or RFID (Radio Frequency Identification). This paper presents a novel scalable multi-factor authentication method, applicable to computer systems with no need of any hardware/software changes.

Route Towards Efficient Magnetization Reversal Driven by Voltage Control of Magnetic Anisotropy

The voltage controlled magnetic anisotropy (VCMA) becomes a subject of major interest for spintro... more The voltage controlled magnetic anisotropy (VCMA) becomes a subject of major interest for spintronics due to its promising potential outcome: fast magnetization manipulation in magnetoresistive random access memories with enhanced storage density and very low power consumption. Using a macrospin approach, we carried out a thorough analysis of the role of the VCMA on the magnetization dynamics of nanostructures with out-of-plane magnetic anisotropy. Diagrams of the magnetization switching have been computed depending on the material and experiment parameters (surface anisotropy, Gilbert damping, duration/amplitude of electric and magnetic field pulses) thus allowing predictive sets of parameters for optimum switching experiments. Two characteristic times of the trajectory of the magnetization were analyzed analytically and numerically setting a lower limit for the duration of the pulses. An interesting switching regime has been identified where the precessional reversal of magnetizat...

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