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Dive into the research topics where Cameron Geddes is active.

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Featured researches published by Cameron Geddes.


Lawrence Berkeley National Laboratory | 2009

FastBit: interactively searching massive data

Kesheng Wu; Sean Ahern; Edward W Bethel; Jacqueline H. Chen; Hank Childs; E. Cormier-Michel; Cameron Geddes; Junmin Gu; Hans Hagen; Bernd Hamann; Wendy S. Koegler; Jerome Lauret; Jeremy S. Meredith; Peter Messmer; Ekow J. Otoo; V Perevoztchikov; A. M. Poskanzer; Prabhat; Oliver Rübel; Arie Shoshani; Alexander Sim; Kurt Stockinger; Gunther H. Weber; W. M. Zhang

As scientific instruments and computer simulations produce more and more data, the task of locating the essential information to gain insight becomes increasingly difficult. FastBit is an efficient software tool to address this challenge. In this article, we present a summary of the key underlying technologies, namely bitmap compression, encoding, and binning. Together these techniques enable FastBit to answer structured (SQL) queries orders of magnitude faster than popular database systems. To illustrate how FastBit is used in applications, we present three examples involving a high-energy physics experiment, a combustion simulation, and an accelerator simulation. In each case, FastBit significantly reduces the response time and enables interactive exploration on terabytes of data.


Journal of Computational Physics | 2011

Numerical methods for instability mitigation in the modeling of laser wakefield accelerators in a Lorentz-boosted frame

Jean-Luc Vay; Cameron Geddes; E. Cormier-Michel; David P. Grote

Modeling of laser-plasma wakefield accelerators in an optimal frame of reference [1] has been shown to produce orders of magnitude speed-up of calculations from first principles. Obtaining these speedups required mitigation of a high-frequency instability that otherwise limits effectiveness. In this paper, methods are presented which mitigated the observed instability, including an electromagnetic solver with tunable coefficients, its extension to accommodate Perfectly Matched Layers and Friedmans damping algorithms, as well as an efficient large bandwidth digital filter. It is observed that choosing the frame of the wake as the frame of reference allows for higher levels of filtering or damping than is possible in other frames for the same accuracy. Detailed testing also revealed the existence of a singular time step at which the instability level is minimized, independently of numerical dispersion. A combination of the techniques presented in this paper prove to be very efficient at controlling the instability, allowing for efficient direct modeling of 10GeV class laser plasma accelerator stages. The methods developed in this paper may have broader application, to other Lorentz-boosted simulations and Particle-In-Cell simulations in general.


ieee international conference on high performance computing data and analytics | 2008

High performance multivariate visual data exploration for extremely large data

Oliver Rübel; Prabhat; Kesheng Wu; Hank Childs; Jeremy S. Meredith; Cameron Geddes; E. Cormier-Michel; Sean Ahern; Gunther H. Weber; Peter Messmer; Hans Hagen; Bernd Hamann; E. Wes Bethel

One of the central challenges in modern science is the need to quickly derive knowledge and understanding from large, complex collections of data. We present a new approach that deals with this challenge by combining and extending techniques from high performance visual data analysis and scientific data management. This approach is demonstrated within the context of gaining insight from complex, time-varying datasets produced by a laser wakefield accelerator simulation. Our approach leverages histogram-based parallel coordinates for both visual information display as well as a vehicle for guiding a data mining operation. Data extraction and subsetting are implemented with state-of-the-art index/query technology. This approach, while applied here to accelerator science, is generally applicable to a broad set of science applications, and is implemented in a production-quality visual data analysis infrastructure. We conduct a detailed performance analysis and demonstrate good scalability on a distributed memory Cray XT4 system.


Journal of Computational Physics | 2013

Numerical modeling of laser tunneling ionization in explicit particle-in-cell codes

Min Chen; E. Cormier-Michel; Cameron Geddes; David L. Bruhwiler; Lule Yu; E. Esarey; C. B. Schroeder; W. P. Leemans

Methods for the calculation of laser tunneling ionization in explicit particle-in-cell codes used for modeling laser-plasma interactions are compared and validated against theoretical predictions. Improved accuracy is obtained by using the direct current form for the ionization rate. Multi level ionization in a single time step and energy conservation have been considered during the ionization process. The effects of grid resolution and number of macro-particles per cell are examined. Implementation of the ionization algorithm in two different particle-in-cell codes is compared for the case of ionization-based electron injection in a laser-plasma accelerator.


Journal of Computational Physics | 2011

Characteristics of an envelope model for laser-plasma accelerator simulation

Benjamin M. Cowan; David L. Bruhwiler; E. Cormier-Michel; E. Esarey; Cameron Geddes; Peter Messmer; Kevin Paul

Simulation of laser-plasma accelerator (LPA) experiments is computationally intensive due to the disparate length scales involved. Current experiments extend hundreds of laser wavelengths transversely and many thousands in the propagation direction, making explicit PIC simulations enormously expensive and requiring massively parallel execution in 3D. Simulating the next generation of LPA experiments is expected to increase the computational requirements yet further, by a factor of 1000. We can substantially improve the performance of LPA simulations by modeling the envelope evolution of the laser field rather than the field itself. This allows for much coarser grids, since we need only resolve the plasma wavelength and not the laser wavelength, and therefore larger timesteps can be used. Thus an envelope model can result in savings of several orders of magnitude in computational resources. By propagating the laser envelope in a Galilean frame moving at the speed of light, dispersive errors can be avoided and simulations over long distances become possible. The primary limitation to this envelope model is when the laser pulse develops large frequency shifts, and thus the slowly-varying envelope assumption is no longer valid. Here we describe the model and its implementation, and show rigorous benchmarks for the algorithm, establishing second-order convergence and correct laser group velocity. We also demonstrate simulations of LPA phenomena such as self-focusing and meter-scale acceleration stages using the model.


Philosophical Transactions of the Royal Society A | 2006

Laser guiding for GeV laser–plasma accelerators

Wim Leemans; E. Esarey; Cameron Geddes; C. B. Schroeder; Csaba Toth

Guiding of relativistically intense laser beams in preformed plasma channels is discussed for development of GeV-class laser accelerators. Experiments using a channel guided laser wakefield accelerator at Lawrence Berkeley National Laboratory (LBNL) have demonstrated that near mono-energetic 100 MeV-class electron beams can be produced with a 10 TW laser system. Analysis, aided by particle-in-cell simulations, as well as experiments with various plasma lengths and densities, indicate that tailoring the length of the accelerator, together with loading of the accelerating structure with beam, is the key to production of mono-energetic electron beams. Increasing the energy towards a GeV and beyond will require reducing the plasma density and design criteria are discussed for an optimized accelerator module. The current progress and future directions are summarized through comparison with conventional accelerators, highlighting the unique short-term prospects for intense radiation sources based on laser-driven plasma accelerators.


international conference on conceptual structures | 2010

Coupling visualization and data analysis for knowledge discovery from multi-dimensional scientific data

Oliver Rübel; Sean Ahern; E. Wes Bethel; Mark D. Biggin; Hank Childs; E. Cormier-Michel; Angela H. DePace; Michael B. Eisen; Charless C. Fowlkes; Cameron Geddes; Hans Hagen; Bernd Hamann; Min-Yu Huang; Soile V.E. Keranen; David W. Knowles; Chris L. Luengo Hendriks; Jitendra Malik; Jeremy S. Meredith; Peter Messmer; Prabhat; Daniela Ushizima; Gunther H. Weber; Kesheng Wu

Knowledge discovery from large and complex scientific data is a challenging task. With the ability to measure and simulate more processes at increasingly finer spatial and temporal scales, the growing number of data dimensions and data objects presents tremendous challenges for effective data analysis and data exploration methods and tools. The combination and close integration of methods from scientific visualization, information visualization, automated data analysis, and other enabling technologies -such as efficient data management- supports knowledge discovery from multi-dimensional scientific data. This paper surveys two distinct applications in developmental biology and accelerator physics, illustrating the effectiveness of the described approach.


Lawrence Berkeley National Laboratory | 2009

Simulating relativistic beam and plasma systems using an optimal boosted frame

J.-L. Vay; David L. Bruhwiler; Cameron Geddes; William M. Fawley; S. F. Martins; John R. Cary; E. Cormier-Michel; Benjamin M. Cowan; Ricardo Fonseca; Miguel A. Furman; Wei Lu; W. B. Mori; L. O. Silva

It was shown recently that it may be computationally advantageous to perform computer simulations in a Lorentz boosted frame for a certain class of systems. However, even if the computer model relies on a covariant set of equations, it was pointed out that algorithmic difficulties related to discretization errors may have to be overcome in order to take full advantage of the potential speedup. In this paper, we summarize the findings, the difficulties and their solutions, and review the applications of the technique that have been performed to date.


Computational Science & Discovery | 2009

Automatic Beam Path Analysis of Laser Wakefield Particle Acceleration Data

Oliver Rübel; Cameron Geddes; E. Cormier-Michel; Kesheng Wu; Prabhat; Gunther H. Weber; Daniela Ushizima; Peter Messmer; Hans Hagen; Bernd Hamann; E. Wes Bethel

Numerical simulations of laser wakefield particle accelerators play a key role in the understanding of the complex acceleration process and in the design of expensive experimental facilities. As the size and complexity of simulation output grows, an increasingly acute challenge is the practical need for computational techniques that aid in scientific knowledge discovery. To that end, we present a set of data-understanding algorithms that work in concert in a pipeline fashion to automatically locate and analyze high energy particle bunches undergoing acceleration in very large simulation datasets. These techniques work cooperatively by first identifying features of interest in individual timesteps, then integrating features across timesteps, and based on the information derived perform analysis of temporally dynamic features. This combination of techniques supports accurate detection of particle beams enabling a deeper level of scientific understanding of physical phenomena than has been possible before. By combining efficient data analysis algorithms and state-of-the-art data management we enable high-performance analysis of extremely large particle datasets in 3D. We demonstrate the usefulness of our methods for a variety of 2D and 3D datasets and discuss the performance of our analysis pipeline.


ADVANCED ACCELERATOR CONCEPTS: Proceedings of the Thirteenth Advanced Accelerator#N#Concepts Workshop | 2009

New Developments in the Simulation of Advanced Accelerator Concepts

David L. Bruhwiler; John R. Cary; Benjamin M. Cowan; Kevin Paul; Cameron Geddes; Paul Mullowney; Peter Messmer; E. Esarey; E. Cormier-Michel; Wim Leemans; Jean-Luc Vay

Improved computational methods are essential to the diverse and rapidly developing field of advanced accelerator concepts. We present an overview of some computational algorithms for laser‐plasma concepts and high‐brightness photocathode electron sources. In particular, we discuss algorithms for reduced laser‐plasma models that can be orders of magnitude faster than their higher‐fidelity counterparts, as well as important on‐going efforts to include relevant additional physics that has been previously neglected. As an example of the former, we present 2D laser wakefield accelerator simulations in an optimal Lorentz frame, demonstrating >10 GeV energy gain of externally injected electrons over a 2 m interaction length, showing good agreement with predictions from scaled simulations and theory, with a speedup factor of ∼2,000 as compared to standard particle‐in‐cell.

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C. B. Schroeder

Lawrence Berkeley National Laboratory

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E. Esarey

Lawrence Berkeley National Laboratory

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Wim Leemans

Lawrence Berkeley National Laboratory

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Csaba Toth

Lawrence Berkeley National Laboratory

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E. Cormier-Michel

Lawrence Berkeley National Laboratory

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David L. Bruhwiler

University of Colorado Boulder

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John R. Cary

University of Colorado Boulder

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Jeroen van Tilborg

Lawrence Berkeley National Laboratory

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W. P. Leemans

Lawrence Berkeley National Laboratory

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Eric H. Esarey

University of California

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