A new video has been produced that highlights activities at The Plasma Science and Technology Institute at UCLA. This Institute consists of affiliated laboratories and research groups that investigate fundamental questions related plasmas, and it includes the research activities performed by PICKSC scientists.
The areas of study include basic plasma physics, fusion research, space plasmas, laser-plasma interactions, advanced accelerators, novel radiation sources, and plasma-materials processing. Diverse programs encompass experimentation, theory, and computer simulation.
The video may be seen here.
Ben Swift, a Research Fellow in the School of Computer Science at the Australian National University, has been working on a project looking at run-time load balancing and optimisation of scientific simulations running on parallel computing architectures. He chose PICKSC’s Skeleton Codes as a basis for studying live programming workflow.
You can watch a video here: Live programming: bringing the HPC development workflow to life
More about Ben Swift may be found on his webpage.
Skeleton codes are bare-bones but fully functional PIC codes containing all the crucial elements but not the diagnostics and initial conditions typical of production codes. These are sometimes also called mini-apps. We are providing a hierarchy of skeleton PIC codes, from very basic serial codes for beginning students to very sophisticated codes with 3 levels of parallelism for HPC experts. The codes are designed for high performance, but not at the expense of code obscurity. They illustrate the use of a variety of parallel programming techniques, such as MPI, OpenMP, and CUDA, in both Fortran and C. For students new to parallel processing, we also provide some Tutorial and Quickstart codes.
If you like to register to receive regular software updates, please contact us.
UCLA graduate student Peicheng Yu, current PICKSC post-doc Xinlu Xu, and collaborators have been investigating the mitigation of the numerical Cerenkov instability (NCI) which occurs when a plasma drifts near the speed of light in a PIC code. In a series of papers (references below) they have developed a general theory as well as mitigation strategies for fully spectral (FFT based) and hybrid (FFT and finite difference) solvers. Recently they published an article in Communications in Computer Physics  and posted a new article on the arxiv: arXiv:1502.01376 [physics.comp-ph]. If you would like more information, please contact Mr. Peicheng Yu at email@example.com.
Expand for References:
2. P. Yu, X. Xu, V. K. Decyk, W. An, J. Vieira, F. S. Tsung, R. A. Fonseca, W. Lu, L. O. Silva, W. B. Mori, “Modeling of laser wakefield acceleration in Lorentz boosted frame using EM-PIC code with spectral solver.” JOURNAL OF COMPUTATIONAL PHYSICS 266, 124 (2014). doi link
3. X. Xu, P. Yu, S. F. Martins, F. S. Tsung, V. K. Decyk, J. Vieira, R. A. Fonseca, W. Lu, L. O. Silva, W. B. Mori, “Numerical instability due to relativistic plasma drift in EM-PIC simulations.” COMPUTER PHYSICS COMMUNICATIONS 184, 2503 (2013). doi link
4. P. Yu, et al., in Proc. 16th Advanced Accelerator Concepts Workshop, San Jose, California, 2014.
5. P. Yu, X. Xu, V. K. Decyk, S. F. Martins, F. S. Tsung, J. Vieira, R. A. Fonseca, W. Lu, L. O. Silva, and W. B. Mori, “Modeling of laser wakefield acceleration in the Lorentz boosted frame using OSIRIS and UPIC framework,” AIP Conf. Proc. 1507, 416 (2012). doi link
PICKSC member Asher Davidson has recently published an article in the Journal of Computational Physics detailing the implementation of a quasi-3D algorithm into OSIRIS. Read more
Breakthrough in plasma-based accelerator research is facilitated using QuickPIC, a code based on the UPIC Framework. Recently, a team of researchers from SLAC and UCLA demonstrated a milestone in plasma based accelerator research. Using two properly space electron bunches, they were able to demonstrate efficient transfer of energy from a drive electron beam to a second trailing electron beam. The planning and interpretation of the experiment relied on QuickPIC as well as OSIRIS.
Nature (current issue — Vol. 515, Num. 7525)
Nature (direct link to paper)
Nature New & Views (Mike Downer)
Nature Podcast (includes actual audio interview)
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Voice of America
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Welt der Physik (Germany)
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The GPU version of OSIRIS is fully operational in one, two and three dimensions, with support for most of the features of OSIRIS. Dynamic GPU load balancing/tuning is included and the code is fully MPI ready and capable of running on thousands of GPU nodes, with tailored support for Fermi and Kepler generations.
Inertial (laser-initiated) fusion energy (IFE) holds incredible promise as a source of clean and sustainable energy for powering devices. However, significant obstacles to obtaining and harnessing IFE in a controllable manner remain, including the fact that self-sustained ignition has not yet been achieved in IFE experiments. This inability is attributed in large part to excessive laser-plasma instabilities (LPIs) encountered by the laser beams.
LPIs such as two-plasmon decay and stimulated Raman scattering can absorb, deflect, or reflect laser light, disrupting the fusion drive, and can also generate energetic electrons that threaten to preheat the target. Nevertheless, IFE schemes like shock ignition (where a high-intensity laser is introduced toward the end of the compression pulse) could potentially take advantage of LPIs to generate energetic particles to create a useful shock that drives fusion. Therefore, developing an understanding of LPIs will be crucial to the success of any IFE scheme.
The physics involved in LPI processes is complex and highly nonlinear, involving both wave- wave and wave-particle interactions and necessitating the use of fully nonlinear kinetic computer models, such as fully explicit particle-in-cell (PIC) simulations that are computationally intensive and thus limit how many spatial and temporal scales can be modeled.
By using highly optimized PIC codes, however, researchers will focus on using fully kinetic simulations to study the key basic high energy density science directly relevant to IFE. The ultimate goal is to develop a hierarchy of kinetic, fluid, and other reduced-description approaches that can model the full space and time scales, and close the gap between particle- based simulations and current experiments.