3 research outputs found
InfiniCloud 2.0: Distributing High Performance Computing across Continents
InfiniCloud 2.0 is the world's first native InfiniBand High Performance Cloud distributed across four continents, spanning Asia, Australia, Europe and North America. The project provides researchers with instant access to computational, storage and network resources distributed around the globe. These resources are then used to build a geographically distributed, virtual supercomputer, complete with globally-accessible parallel file system and job scheduling. This paper describes the high level design and the implementation details of InfiniCloud 2.0. Two example applications types, a gene sequencing pipeline and plasma physics simulation code were chosen to demonstrate the system's capabilities
Overcoming Challenges in Predictive Modeling of Laser-Plasma Interaction Scenarios. The Sinuous Route from Advanced Machine Learning to Deep Learning
The interaction of ultrashort and intense laser pulses with solid targets and dense plasmas is a rapidly developing area of physics, this being mostly due to the significant advancements in laser technology. There is, thus, a growing interest in diagnosing as accurately as possible the numerous phenomena related to the absorption and reflection of laser radiation. At the same time, envisaged experiments are in high demand of increased accuracy simulation software. As laser-plasma interaction modelings are experiencing a transition from computationally-intensive to data-intensive problems, traditional codes employed so far are starting to show their limitations. It is in this context that predictive modelings of laser-plasma interaction experiments are bound to reshape the definition of simulation software. This chapter focuses an entire class of predictive systems incorporating big data, advanced machine learning algorithms and deep learning, with improved accuracy and speed. Making use of terabytes of already available information (literature as well as simulation and experimental data) these systems enable the discovery and understanding of various physical phenomena occurring during interaction, hence allowing researchers to set up controlled experiments at optimal parameters. A comparative discussion in terms of challenges, advantages, bottlenecks, performances and suitability of laser-plasma interaction predictive systems is ultimately provided
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Pulsar, PIC and Pigeon
The dissertation presents the computational technique Particle-In-Cell, or PIC for short, and its applications in studying the magnetospheres of neutron stars, modeled as conducting rotators with strong magnetic fields. Pigeon, an open-source PIC simulator written by the author in modern C++, is anatomically examined as an instrument to illustrate the principles, algorithms and engineering difficulties of the PIC technique. Two types of rotators are studied using Pigeon. The monopolar rotator, which has an exact solution in the force free limit, serves as a tester for the code, as well as an example of the PIC's capability. The main application of Pigeon is on the ab initio simulation of an (axisymmetric) dipolar rotator with self-consistent gamma ray photon emission and pair creation, the study of which could reveal valuable information of the mechanism of the pulsars.
Thanks to the performance boost brought by Pigeon's dynamic load balancing functionality, we are able to perform the simulation with a 4096x4096 high resolution grid. The high resolution is critical in obtaining a Lorentz factor of 10000 of the polar cap potential drop, which in turn enables good separations of energy levels and hence makes the simulation closer to representing the real-life pulsars. With the high resolution, we are also able to study the Y point more closely, where we find that the angular momentum conservation dictates the process of magnetic flux surface crossing that is responsible for the release of electromagnetic energies into the plasma