Mr. Julien Bernard Profile

Julien Bernard

Software Engineer at ANU

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Publications (8)

Proceedings Article | 26 July 2024 Presentation

MAVIS RTC: a COSMIC-based real-time and low latency GPU accelerated system for adaptive optics

Julien Bernard, Florian Ferreira, Nicolas Doucet, Arnaud Sevin, Jesse Cranney, François Rigaut, Damien Gratadour, David Brodrick

Proceedings Volume 13101, 131011J (2024) https://doi.org/10.1117/12.3019054

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Proceedings Article | 13 December 2020 Poster + Paper

MAVIS real-time control system: a high-end implementation of the COSMIC platform

D. Gratadour, J. Bernard, N. Doucet, F. Ferreira, A. Sevin, R. Biasi, F. Rigaut

Proceedings Volume 11448, 114482M (2020) https://doi.org/10.1117/12.2562082

KEYWORDS: Real-time computing, Control systems, Data acquisition, Control systems design, Telecommunications, Field programmable gate arrays, Software development, Data communications, Turbulence, Tomography

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Proceedings Article | 13 December 2020 Presentation + Paper

Hard real-time core software of the AO RTC COSMIC platform: architecture and performance

F. Ferreira, A. Sevin, J. Bernard, O. Guyon, A. Bertrou-Cantou, J. Raffard, F. Vidal, E. Gendron, D. Gratadour

Proceedings Volume 11448, 1144815 (2020) https://doi.org/10.1117/12.2561244

KEYWORDS: Real-time computing, Adaptive optics, Computer architecture, Telescopes, Interfaces, Structural health monitoring, Computing systems, Deformable mirrors, Large telescopes, Actuators

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With the upcoming giant class of telescopes, Adaptive Optics (AO) has become more essential than ever before to get access to the full potential offered by those telescopes. The complexity of such AO systems is reaching extreme heights, and disruptive developments will have to be made in order to build them. One of the critical component of a AO system is the Real Time Controller (RTC) which will have to compute the slopes and the Deformable Mirror (DM) commands at high frequency, in a range of 0.5 to several kHz. Since the complexity of the computations involved in the RTC is increasing with the size of the telescope, fulfilling RTC requirements for Extremely Large Telescope (ELT) class is a challenge. As an example, the MICADO SCAO (Single Conjugate Adaptive Optics) system requires around 1 TMAC/s for the RTC to get sufficient performance. This complexity brings the need for High Performance Computing (HPC) techniques and standards, such as the use of hardware accelerator like GPU. On top of that, building a RTC is often project-dependent as the components and the interfaces change from one instrument to an other. The COSMIC platforms aims at developing a common AO RTC platform which is meant to be powerful, modular and available to the AO community. This development is a joint effort between Observatoire de Paris and the Australian National University (ANU) in collaboration with the Subaru Telescope. We focus here on the current status of the core hard real-time component of this platform. The H-RTC pipeline is composed of Business Units (BU): each BU is an independent process in charge of one particular operation, such as Matrix Vector Multiply (MVM) or centroid computation, that can be made on CPU or on GPU. BUs read and write data on Shared Memory (SHM) handled by the CACAO framework. Synchronization between each BU can then be made either by using semaphore or by busy waiting on the GPU to ensure very low jitter. The RTC pipeline can then be controlled through a Python interface. One of the key point of this architecture is that the interfaces of a BU with the various SHM is abstracted, so adding a new BU in the collection of available ones is straight forward. This approach allows a high performance, scalable, modular and configurable RTC pipeline that could fit the needs of any AO system configuration. Performance has been measured on a MICADO SCAO scale RTC pipeline with around 25,000 slopes by 5,000 actuators on a DGX-1 system equipped with 8 Tesla V100 GPUs. The considered pipeline is composed of two BUs : the first one takes an input the raw pyramid WFS image (produced by simulator), applies on it dark and flat references, and then extract the useful pixel from the image. The second BU performs the MVM and the integration of the commands following a classical integrator command law. Synchronization between the BU is made through GPU busy waiting on the BU inputs. Performance obtained shows a mean latency up to 235 μs using 4 GPUs, with a jitter of 4.4 μs rms and a maximum jitter of 30 μs

Proceedings Article | 18 July 2018 Paper

Design and performance of a scalable GPU-based AO RTC prototype

Julien Bernard, Denis Perret, Arnaud Sevin, Maxime Laine, Tristan Buey, Damien Gratadour

Proceedings Volume 10703, 107034B (2018) https://doi.org/10.1117/12.2313196

KEYWORDS: Real-time computing, Adaptive optics, Field programmable gate arrays, Computer simulations, Prototyping, Time metrology, Computer architecture

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In the context of the Green Flash project we have assembled a full scale demonstrator for an E-ELT first light AO RTC, based on the GPU technology. Such facility, designed to drive in real-time the AO system, is composed of a real-time core, processing streaming data from sensors and controlling deformable optics, and a supervisor module, optimizing the control loop by providing updated versions of the control matrix at a regular rate depending on the observing conditions evolution. This RTC prototype is designed to assess the system performance in various configurations from single conjugate AO for the E-ELT, i.e. about 10 Gb/s of streaming data from a single sensor and a required performance of about 100 GMAC/s; to the dimensioning of a MCAO system with 100 Gb/s of streaming data and 1.5 TMAC/s performance. Both concepts rely on the same architecture, the latter being a scaled version of the former. We chose a very low level approach using a persistent kernel strategy on the GPUs to handle all the computation steps including pixel calibration, slopes and command vector computation. This approach simplifies the latency management by reducing the communication but led us to re-implement some GPUs standard features : communication mechanisms (guard, peer-to-peer), algorithms (generalized matrix-vector multiplication, reduce/all reduce) and new synchronization mechanisms on a multi node - multi GPUs system. In order to assess the performance of the full AO RTC prototype under realistic conditions, we have concurrently implemented a real-time simulator able to feed the real-time core with data by emulating the sensors data transfer protocols and interacting with simulated deformable optics. The real-time simulator is able to deliver high precision simulated data and simulate the whole retro-action loop for the SCAO case, enabling a full scale / full feature test of the prototype. In this paper, we report on the design and characterization the AO RTC prototype performance in SCAO mode and discuss a strategy for its integration in tmographic AO mode.

Proceedings Article | 17 July 2018 Presentation + Paper

The compute and control for adaptive optics (CACAO) real-time control software package

Olivier Guyon, Arnaud Sevin, Damien Gratadour, Julien Bernard, Hatem Ltaief, Dalal Sukkari, Sylvain Cetre, Nour Skaf, Julien Lozi, Frantz Martinache, Christophe Clergeon, Barnaby Norris, Alison Wong, Jared Males

Proceedings Volume 10703, 107031E (2018) https://doi.org/10.1117/12.2314315

KEYWORDS: Adaptive optics, Control systems, Actuators, Wavefronts, Image processing, Cameras, Data processing, Adaptive control, Process control, Sensor fusion

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Proceedings Article | 10 July 2018 Presentation + Paper

Prototyping AO RTC using emerging high performance computing technologies with the Green Flash project

Damien Gratadour, Tim Morris, Roberto Biasi, Hugues Deneux, Julien Bernard, Jean-Tristan Buey, Nicolas Doucet, Florian Ferreira, Maxime Laine, Denis Perret, Arnaud Sevin, Alastair Basden, Deli Geng, James Osborn, Lazar Staykov, Matthew Townson, Edward Younger, Mario Andrighettoni, Christian Patauner, Dietrich Pescoller, Jerome Lemaitre, Paolo Palazzari, Damien Pretet, Christophe Rouaud

Proceedings Volume 10703, 1070318 (2018) https://doi.org/10.1117/12.2312686

KEYWORDS: Field programmable gate arrays, Adaptive optics, Prototyping, Real-time computing, Cameras, Computer simulations, Computing systems, Sensors, Interfaces, Data storage

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Proceedings Article | 27 July 2016 Paper

Bridging FPGA and GPU technologies for AO real-time control

Denis Perret, Maxime Lainé, Julien Bernard, Damien Gratadour, Arnaud Sevin

Proceedings Volume 9909, 99094M (2016) https://doi.org/10.1117/12.2232858

KEYWORDS: Adaptive optics, Computer simulations, Field programmable gate arrays, Control systems, Device simulation, Cameras, Real-time computing, Control systems, Frame grabbers, Deformable mirrors, Signal processing

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Proceedings Article | 27 July 2016 Paper

Green FLASH: energy efficient real-time control for AO

D. Gratadour, N. Dipper, R. Biasi, H. Deneux, J. Bernard, J. Brule, R. Dembet, N. Doucet, F. Ferreira, E. Gendron, M. Laine, D. Perret, G. Rousset, A. Sevin, U. Bitenc, D. Geng, E. Younger, M. Andrighettoni, G. Angerer, C. Patauner, D. Pescoller, F. Porta, G. Dufourcq, A. Flaischer, J.-B. Leclere, A. Nai, P. Palazzari, D. Pretet, C. Rouaud

Proceedings Volume 9909, 99094I (2016) https://doi.org/10.1117/12.2232642

KEYWORDS: Adaptive optics, Control systems, Real-time computing, Computing systems, Field programmable gate arrays, Prototyping, Sensors, Telecommunications, Telescopes, Tomography

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Showing 5 of 8 publications

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