Scientific direction Development of key enabling technologies
Transfer of knowledge to industry

PhD : selection by topics

Microalgae strain selection and caracterisation for cultivation under industrial CO2

DPACA (CTReg)

Autre

01-09-2018

SL-DRT-18-0205

florian.delrue@cea.fr

Microalgae have the advantage of being able to convert CO2 into a valuable biomass via photosynthesis. They are capable of capturing industrial CO2 emissions while reducing the environmental impact of the emitting industry. However, due to high production costs, microalgae are restricted to specialty markets (cosmetics, nutraceuticals). The use of industrial CO2 by microalgae would imply significant quantities of CO2 to be recovered. This would require a drastic reduction of the production costs. For that, the surface (or volume) productivity need to be significantly improved to reduce costs and the footprint reduced. It is therefore essential to select microalgae that can be more efficient. This thesis proposes to screen the microalgae biodiversity in search of strains which exhibit excellent performances of CO2 to biomass conversion. Another criterion of this screening will be the tolerance of microalgae to high concentrations of CO2 since industrial exhaust fumes generally contains high concentration of CO2. The objective of this screening is to select and characterize microalgae strains with high CO2 uptake rate and good tolerance to high CO2 concentrations. The most efficient strains will be characterized more precisely and their ability to tolerate high CO2 concentrations will be studied.

Approximate occupancy model of a sensor with Machine Learning

Département Architectures Conception et Logiciels Embarqués (LIST-LETI)

Laboratoire Infrastructure et Ateliers Logiciels pour Puces

01-01-2018

SL-DRT-18-0219

frederic.heitzmann@cea.fr

This topic falls in the context of the development of autonomous vehicles, drones, and robotics. The environment of the vehicle is described in an occupation grid, while each cell of the grid contains the probability of the occupation by an object. Bayesian fusion technique allow to fuse information provided by several sensors into the grid. Thus, we plan to take benefit from knowledge in CEA-LETI, about both physics behind sensors and applications of occupation grid, and focus this thesis on approximation of a occupation model with Machine Learning techniques. A key aspect in this technique is the shift from a ?measurement? coming from a sensor, and the ?occupancy? information for each cell of the grid. Since each sensor has its own specifications in terms of radial or angular accuracy, misdetection rate ? each of them has a specific occupancy model. The exact computation of this model is intractable in practice in the general case, even though the formulae is well known, due to a combinational explosion of the number of terms. At the same time, the recent success of Deep and Reinforcement Learning ? image classification, automatic language translation, strategy games ? pushed in the front scene the capability of neuron networks to approximate any function.

New Perovskite based material for medical X-ray

Département Microtechnologies pour la Biologie et la Santé (LETI)

Laboratoire Détecteurs

01-10-2018

SL-DRT-18-0233

eric.grosdaillon@cea.fr

The Laboratory Imaging System for Life is part of the Department of Microtechnologies for Biology and Health of the CEA/LETI. It has a solid expertise in the development of new detection modules based on a semiconductor or a scintillator layer, combined with a readout electronics for X-ray or gamma-ray imaging in the fields of medical imaging or control for security. The objective of this thesis, in collaboration with a leading industrial in the field of digital radiography, is to study a new perovskite-based semiconductor material for direct X-ray detection. A thesis is underway since October 2017 at the CEA/LITEN about the elaboration of this material. Their use in photoconducting devices is expected to increase the signal and improve the spatial resolution of images, thus reduce the dose administered to the patient, or even, in counting mode, provide access to new information on tissue composition. For this, the student, physicist and experimenter, will have to characterize the transport properties of charge carriers, the nature of defects, and the electric field of crystals elaborated at the CEA/LITEN. He will model their behavior. Finally, it will study their performances for different applications, in integration mode and photon counting mode.

Exploration and design of in-memory computing architectures based on emerging non volatile memories

Département Architectures Conception et Logiciels Embarqués (LIST-LETI)

Laboratoire Intégration Silicium des Architectures Numériques

01-09-2018

SL-DRT-18-0258

jean-philippe.noel@cea.fr

The thesis objective is to study and propose new architectures for in-memory-computing based on emerging non-volatile mémories and thus explore future applications. L'objectif de cette thèse est d'explorer l'utilisation des mémoire non-volatiles émergentes pour les architectures de in-memory-computing afin d'ouvrir le champ d'application de ces mémoires limitées aujourdh'ui à des implemntations SRAM. The usage of any devices, from embedded to super-computers, is becoming more and more data-centric. On the other hand, the performance gap between processor and memory has been steadily growing during the last decades (known as the ?memory wall?). The energy consumption gap between computation (GFlop/s) and data-movement (GByte/s) is also showing the same trend. A very large proportion, if not the largest, of the efforts made by silicon companies and researchers have been focused on improving the characteristics of memories such as size, bandwidth, non-volatility, etc. The solution advocated to reduce the data-movement cost amounted to bring part of the memory (e.g. the caches) on the die nearby the processor. Despite the clear advantages of cache hierarchy, the latency of data transfers between the different memory levels remains an important performance bottleneck. In terms of energy consumption, I/O largely dominates the overall cost (70% to 90%). Eventually, in terms of security, data transfers between CPU and memory constitutes the Achilles heel of a computing system largely exploited by hackers. Therefore, other solutions came up over the years to address those problems. They can be grouped in the following terms: Processing-In-Memory, Logic-In-Memory and In-Memory-Computing (or Computing-In-Memory). Processing-In-Memory (PIM) is a concept based on DRAM process consisting in driving computation units implemented in DIMMs through the existing memory bus. In more recent works, and with the progress of the 3D technologies, researchers propose to design stacks of computation unit next to the DRAM stack, which permits to create massive data parallelism. Logic-In-Memory is the concept of integrating some computation ability into the memory. However, it is more used to implement logic operations on a specific memory layer or logic layer dedicated for 3Ds memories. Finally, In-Memory-Computing (IMC) consists in integrating a part of the computation units into the memory boundary, which means that data do not leave memory. This should offer significant gain in the execution time, reducing the power consumption and improving the security. The IMC concept has been successfully implemented in CEA-LETI. Despite the promising results of existing works, all the applications has been experimented only based on SRAM bitcell arrays. To go further and target high capacity memory application (video, ...), the usage of non-volatile memories based on emerging technologies (ReRAM, PCM, MRAM, ...) will be explored in this thesis. Based on in-house software platform and hardware architecture, the main goal will be to evaluate the performance (power, timing, ...) and explore new architecture and design solutions.

Unifying Distributed Memories in Heterogeneous Systems

Département Architectures Conception et Logiciels Embarqués (LIST-LETI)

Laboratoire Calcul Embarqué

01-10-2018

SL-DRT-18-0290

loic.cudennec@cea.fr

Future computers in high-performance and embedded systems lead to complex memory hierarchies. Hundreds of computing nodes will have to be connected to tera-bytes of memories. In such systems, both the processing units (CPU, GPU, DSP, FPGA) and the memories (DRAM, NVRAM, FLASH) can be heterogeneous. Several architectures exist (distributed memory, shared memory, NUMA) with different hardware implementations (cache coherence, communication protocols), software implementations (thread parallelism, OpenMP, transactions) and communication technologies between processing units and memory (MPI, RDMA, RoCE, CCIX, GenZ). None of the approaches above offer a simple, unified programming model and memory model for parallel applications. The purpose of this Ph.D. Thesis is to study the possibility of using emerging technologies related to computing units, hybrid memories (persistent or not) and remote communication standards in order to accelerate data sharing onto heterogeneous platforms and provide a convenient programming model.

Refrigerant purification in absorption chiller by heat and mass transfer optimization in falling films inside rectifier and generator

Département Thermique Biomasse et Hydrogène (LITEN)

Laboratoire Systèmes Solaires Haute Température

01-10-2018

SL-DRT-18-0308

francois.boudehenn@cea.fr

From more than fifteen years, the development of air-conditioning offers more and more comfort to people. Major part of commercial air-conditioners uses electricity-powered vapor compression machines to provide the frigorific effect. The use of that technology must face to a paradox: more the number of air-conditioners installed in a city increases, more heat released to urban atmosphere rises, thus increasing the ambient air temperature which implies a decreasing the performance of the chiller and increasing the cooling load of buildings. In fine, peak electricity demand for cooling can be tripled. One of the solution could be the use of thermally driven chillers powered by waste-heat or solar energy. Ammonia-water chillers are particularly interesting because of their low production and maintenance costs. The main failing of this working pair is the small difference of volatility between the absorbent and the refrigerant, which implies the use of a rectifier to remove traces of water in the ammonia vapors at the outlet of the generator. In this context, the thesis will focus on understanding and modeling of coupled heat and mass transfers at the steam generation part (generator/rectifier) made by falling film. An experimental validation will be realized using an existing prototype at laboratory. This experimental and numerical validation will then make possible a global steam generation optimization aimed at improving overall compactness and increasing the performance of the thermodynamic cycle.

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