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Jean-Michel Portal

Bio: Jean-Michel Portal is an academic researcher from Centre national de la recherche scientifique. The author has contributed to research in topics: Resistive random-access memory & Artificial neural network. The author has an hindex of 25, co-authored 136 publications receiving 2047 citations. Previous affiliations of Jean-Michel Portal include Alternatives & Aix-Marseille University.


Papers
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Proceedings ArticleDOI
19 May 2013
TL;DR: This paper proposes a solution to improve the performance and reduce the power consumption of LUT in FPGA using CBRAM-based structures and shows significant improvement compared to the traditional SRAM-based FPGa in terms of critical delay and power gain.
Abstract: At most advanced technology nodes, Field Programmable Gate Arrays (FPGA) present great advantages compared to more conventional processor architectures; their natural regularity, modularity and inherent reliability due to duplicated identical tiles provide a solution to overcome new technologies with increasing variability. However, FPGA market is still limited by power efficiency issue, due to two coordinated factors like interconnection-dominated design and large usage of memories, computation being performed thanks to Look-Up-Table (LUT). In this paper, we propose a solution to improve the performance and reduce the power consumption of LUT in FPGA using CBRAM-based structures. Our proposed design shows significant improvement compared to the traditional SRAM-based FPGA in: critical delay is reduced by ~23% due to compact structure (1T-2R) and power gain by reduction in static power consumption by ~18%.

6 citations

Journal ArticleDOI
TL;DR: In this paper, a built-in structure allows collecting statistical data related to the OxRRAM memory array (ON/OFF resistance distributions) for reliability assessment of the technology, which is a key parameter to determine the overall performance.
Abstract: Resistive Random Access Memory (RRAM) is a form of nonvolatile storage that operates by changing the resistance of a specially formulated solid dielectric material [1] . Among RRAMs, oxide-based Resistive RAMs (so-called OxRRAMs) are promising candidates due their compatibility with CMOS processes and high ON/OFF resistance ratio. Common problems with OxRRAM are related to high variability in operating conditions and low yield. OxRRAM variability mainly impact ON/OFF resistance ratio. This ratio is a key parameter to determine the overall performance of an OxRRAM memory. In this context, the presented built-in structure allows collecting statistical data related to the OxRRAM memory array (ON/OFF resistance distributions) for reliability assessment of the technology.

6 citations

Proceedings ArticleDOI
17 Jul 2019
TL;DR: For BNNs, ST-MRAMs can be programmed with weak (low-energy) programming conditions, without error correcting codes, and it is shown that this result can allow the use of low energy and low area ST- MRAM cells, and the energy savings at the system level can reach a factor two.
Abstract: One of the most exciting applications of Spin Torque Magnetoresistive Random Access Memory (ST-MRAM) is the in-memory implementation of deep neural networks, which could allow improving the energy efficiency of Artificial Intelligence by orders of magnitude with regards to its implementation on computers and graphics cards. In particular, ST-MRAM could be ideal for implementing Binarized Neural Networks (BNNs), a type of deep neural networks discovered in 2016, which can achieve state-of-the-art performance with a highly reduced memory footprint with regards to conventional artificial intelligence approaches. The challenge of ST-MRAM, however, is that it is prone to write errors and usually requires the use of error correction. In this work, we show that these bit errors can be tolerated by BNNs to an outstanding level, based on examples of image recognition tasks (MNIST, CIFAR-10 and ImageNet): bit error rates of ST-MRAM up to 0.1% have little impact on recognition accuracy. The requirements for ST-MRAM are therefore considerably relaxed for BNNs with regards to traditional applications. By consequence, we show that for BNNs, ST-MRAMs can be programmed with weak (low-energy) programming conditions, without error correcting codes. We show that this result can allow the use of low energy and low area ST-MRAM cells, and show that the energy savings at the system level can reach a factor two.

6 citations

Journal ArticleDOI
TL;DR: This work proposes an industrially-ready WT circuit that was simulated with a RRAM model calibrated on real measurements, and performs extensive CMOS and RRAM variability simulations to extract the actual performances of the proposed WT circuit.
Abstract: While Resistive Random Access Memories (RRAM) are perceived nowadays as a promising solution for the future of computing, these technologies suffer from intrinsic variability regarding programming voltage, switching speed and achieved resistance values. Write Termination (WT) circuits are a potential solution to solve these issues. However, previously reported WT circuits do not demonstrate sufficient reliability. In this work, we propose an industrially-ready WT circuit that was simulated with a RRAM model calibrated on real measurements. We perform extensive CMOS and RRAM variability simulations to extract the actual performances of the proposed WT circuit. Finally, we simulate the effects of the proposed WT circuit with memory traces extracted from real Edge-level data-intensive applications. Overall, we demonstrate 2× to 40× of energy gains at bit level. Moreover, we show from 1.9× to 16.2× energy gains with real applications running depending on the application memory access pattern thanks to the proposed WT circuit.

6 citations

Proceedings ArticleDOI
17 May 2020
TL;DR: Al 2 O 3 based conductive bridge RAM (CBRAM) is co-integrated with an optimized Ge-Se-Sb-N based back-end selector in 1S1R memory arrays for low voltage and advanced CMOS compatibility as mentioned in this paper.
Abstract: Al 2 O 3 based Conductive Bridge RAM (CBRAM) is co-integrated with an optimized Ge-Se-Sb-N based back-end selector in 1S1R memory arrays for low voltage and advanced CMOS compatibility. Electrical characterization is performed to extract device features, showing forming free behavior, ~3.5V maximum operating voltage, s table 2 decades for I on /I off during 107 cycles, ~1V reading voltage margin and moderate leakage current. Compatible with 100kbit sector size, this optimized stack is found very promising for embedded applications on advanced process nodes. Indeed, design exploration on a 28nm core process shows that peripherals can be designed with middle voltage MOS, fitting best with low voltage 1S1R cross-point array and leading to reduced overall memory area.

6 citations


Cited by
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Journal ArticleDOI
TL;DR: Most of the NOM can be removed by coagulation, although, the hydrophobic fraction and high molar mass compounds of NOM are removed more efficiently than hydrophilic fraction and the low molarmass compounds.

1,106 citations

Journal ArticleDOI
TL;DR: The review ends with the current status of RRAMs in terms of stability, scalability and switching speed, which are three important aspects of integration onto semiconductors.
Abstract: The resistance switching behaviour of several materials has recently attracted considerable attention for its application in non-volatile memory (NVM) devices, popularly described as resistive random access memories (RRAMs). RRAM is a type of NVM that uses a material(s) that changes the resistance when a voltage is applied. Resistive switching phenomena have been observed in many oxides: (i) binary transition metal oxides (TMOs), e.g. TiO(2), Cr(2)O(3), FeO(x) and NiO; (ii) perovskite-type complex TMOs that are variously functional, paraelectric, ferroelectric, multiferroic and magnetic, e.g. (Ba,Sr)TiO(3), Pb(Zr(x) Ti(1-x))O(3), BiFeO(3) and Pr(x)Ca(1-x)MnO(3); (iii) large band gap high-k dielectrics, e.g. Al(2)O(3) and Gd(2)O(3); (iv) graphene oxides. In the non-oxide category, higher chalcogenides are front runners, e.g. In(2)Se(3) and In(2)Te(3). Hence, the number of materials showing this technologically interesting behaviour for information storage is enormous. Resistive switching in these materials can form the basis for the next generation of NVM, i.e. RRAM, when current semiconductor memory technology reaches its limit in terms of density. RRAMs may be the high-density and low-cost NVMs of the future. A review on this topic is of importance to focus concentration on the most promising materials to accelerate application into the semiconductor industry. This review is a small effort to realize the ambitious goal of RRAMs. Its basic focus is on resistive switching in various materials with particular emphasis on binary TMOs. It also addresses the current understanding of resistive switching behaviour. Moreover, a brief comparison between RRAMs and memristors is included. The review ends with the current status of RRAMs in terms of stability, scalability and switching speed, which are three important aspects of integration onto semiconductors.

950 citations

Journal ArticleDOI
02 Jan 2017
TL;DR: The relevant virtues and limitations of these devices are assessed, in terms of properties such as conductance dynamic range, (non)linearity and (a)symmetry of conductance response, retention, endurance, required switching power, and device variability.
Abstract: Dense crossbar arrays of non-volatile memory (NVM) devices represent one possible path for implementing massively-parallel and highly energy-efficient neuromorphic computing systems. We first revie...

800 citations

Journal ArticleDOI
TL;DR: Emphasis will be placed on the use of bioaccumulation and biomarker responses in air, soil, water and food, as monitoring tools for the assessment of the risks and hazards of PAH concentrations for the ecosystem, as well as on its limitations.
Abstract: Polycyclic aromatic hydrocarbons (PAHs) are a large group of organic compounds with two or more fused aromatic rings. They have a relatively low solubility in water, but are highly lipophilic. Most of the PAHs with low vapour pressure in the air are adsorbed on particles. When dissolved in water or adsorbed on particulate matter, PAHs can undergo photodecomposition when exposed to ultraviolet light from solar radiation. In the atmosphere, PAHs can react with pollutants such as ozone, nitrogen oxides and sulfur dioxide, yielding diones, nitro- and dinitro-PAHs, and sulfonic acids, respectively. PAHs may also be degraded by some microorganisms in the soil. PAHs are widespread environmental contaminants resulting from incomplete combustion of organic materials. The occurrence is largely a result of anthropogenic emissions such as fossil fuel-burning, motor vehicle, waste incinerator, oil refining, coke and asphalt production, and aluminum production, etc. PAHs have received increased attention in recent years in air pollution studies because some of these compounds are highly carcinogenic or mutagenic. Eight PAHs (Car-PAHs) typically considered as possible carcinogens are: benzo(a)anthracene, chrysene, benzo(b)fluoranthene, benzo(k)fluoranthene, benzo(a)pyrene (B(a)P), dibenzo(a,h)anthracene, indeno(1,2,3-cd)pyrene and benzo(g,h,i)perylene. In particular, benzo(a)pyrene has been identified as being highly carcinogenic. The US Environmental Protection Agency (EPA) has promulgated 16 unsubstituted PAHs (EPA-PAH) as priority pollutants. Thus, exposure assessments of PAHs in the developing world are important. The scope of this review will be to give an overview of PAH concentrations in various environmental samples and to discuss the advantages and limitations of applying these parameters in the assessment of environmental risks in ecosystems and human health. As it well known, there is an increasing trend to use the behavior of pollutants (i.e. bioaccumulation) as well as pollution-induced biological and biochemical effects on human organisms to evaluate or predict the impact of chemicals on ecosystems. Emphasis in this review will, therefore, be placed on the use of bioaccumulation and biomarker responses in air, soil, water and food, as monitoring tools for the assessment of the risks and hazards of PAH concentrations for the ecosystem, as well as on its limitations.

798 citations