Scientific Application Performance on Candidate PetaScale Platforms

Oliker, Leonid; Canning, Andrew; Carter, Jonathan T.; lancu, C.; Lijewski, Michael J.; Kamil, Shoaib; Shalf, John; Shan, Hongzhang; Strohmaier, Erich; Ethier, S.; Goodale, Tom

doi:10.1109/ipdps.2007.370259

Cited by 34 publications

(19 citation statements)

References 16 publications

(15 reference statements)

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“…Existing particle-in-cell (PIC) techniques [5,6] have clearly demonstrated excellent scaling on current terascale leadership class supercomputers. For example, the Gyrokinetic Toroidal Code (GTC) [7,8] a mature PIC code has demonstrated excellent scaling on virtually all of the current leadership class facilities worldwide utilizing MPI and OpenMP [9,10,11,12,13].…”

Section: Pfr Special Issue On Itc20 2010mentioning

confidence: 99%

Scientific and Computational Challenges of the Fusion Simulation Program (FSP)

Tang

2011

Plasma and Fusion Research

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This paper highlights the scientific and computational challenges facing the Fusion Simulation Program (FSP) -a major national initiative in the United States with the primary objective being to enable scientific discovery of important new plasma phenomena with associated understanding that emerges only upon integration. This requires developing a predictive integrated simulation capability for magnetically-confined fusion plasmas that are properly validated against experiments in regimes relevant for producing practical fusion energy. It is expected to provide a suite of advanced modeling tools for reliably predicting fusion device behavior with comprehensive and targeted science-based simulations of nonlinearly-coupled phenomena in the core plasma, edge plasma, and wall region on time and space scales required for fusion energy production. As such, it will strive to embody the most current theoretical and experimental understanding of magnetic fusion plasmas and to provide a living framework for the simulation of such plasmas as the associated physics understanding continues to advance over the next several decades. Substantive progress on answering the outstanding scientific questions in the field will drive the FSP toward its ultimate goal of developing the ability to predict the behavior of plasma discharges in toroidal magnetic fusion devices with high physics fidelity on all relevant time and space scales. From a computational perspective, this will demand computing resources in the petascale range and beyond together with the associated multi-core algorithmic formulation needed to address burning plasma issues relevant to ITER -a multibillion dollar collaborative experiment involving seven international partners representing over half the world's population. Even more powerful exascale platforms will be needed to meet the future challenges of designing a demonstration fusion reactor (DEMO). Analogous to other major applied physics modeling projects (e.g., Climate Modeling), the FSP will need to develop software in close collaboration with computers scientists and applied mathematicians and validated against experimental data from tokamaks around the world. Specific examples of expected advances needed to enable such a comprehensive integrated modeling capability and possible "co-design" approaches will be discussed.

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Section: Pfr Special Issue On Itc20 2010mentioning

confidence: 99%

Scientific and Computational Challenges of the Fusion Simulation Program (FSP)

Tang

2011

Plasma and Fusion Research

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“…While there have been rankings based on fictitious performance numbers or theoretical peak performance numbers, most of these rankings focus on measured performances. Benchmarks used for these rankings vary in complexity greatly from simply synthetic tests such as STREAM [9] to full (scientific) applications as often used in focused performance studies [10,11]. The benchmarks and problem sizes used in these rankings often have to be adapted or replaced to reflect the changing usage of computer systems.…”

Section: Performance Rankingsmentioning

confidence: 99%

Generalized utility metrics for supercomputers

Strohmaier

2009

Comp. Sci. Res. Dev.

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The problem of ranking the utility of supercomputer systems arises frequently in situations such as procurements and other types of evaluations of architectures. It is also central for any general ranking of supercomputers such as the Top500. Rankings of computer systems have traditionally solely focused on performance aspects. In recent years restrictions due to power and space requirements of large supercomputers have become very noticeable, which has increased the importance of including these factors in generalized rankings. In this paper we present an overview of the current practice for utility metrics and analyze their shortcomings. We then present and discuss in detail a new concept for a parameterized utility metric for supercomputers, which is based on effective performance, available memory size, actual power consumption, and (if desired) the floor space required for supercomputers. This metric is designed and proposed for augmenting the current Top500 ranking.

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“…GTC has been run effectively, with scaling up to 32K cores, on all of the recent high performance computational architectures [4]. The GTC programing model uses FORTRAN 90 and MPI, and uses PETSc for the potential solves in Poisson's equation, which is discretized with linear finite elements.…”

Section: Introductionmentioning

confidence: 99%

Performance of particle in cell methods on highly concurrent computational architectures

Adams¹,

Ethier²,

Wichmann³

2009

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Abstract. Particle in cell (PIC) methods are effective in computing Vlasov-Poisson system of equations used in simulations of magnetic fusion plasmas. PIC methods use grid based computations, for solving Poisson's equation or more generally Maxwell's equations, as well as Monte-Carlo type methods to sample the Vlasov equation. The presence of two types of discretizations, deterministic field solves and Monte-Carlo methods for the Vlasov equation, pose challenges in understanding and optimizing performance on today large scale computers which require high levels of concurrency. These challenges arises from the need to optimize two very different types of processes and the interactions between them. Modern cache based high-end computers have very deep memory hierarchies and high degrees of concurrency which must be utilized effectively to achieve good performance. The effective use of these machines requires maximizing concurrency by eliminating serial or redundant work and minimizing global communication. A related issue is minimizing the memory traffic between levels of the memory hierarchy because performance is often limited by the bandwidths and latencies of the memory system. This paper discusses some of the performance issues, particularly in regard to parallelism, of PIC methods. The gyrokinetic toroidal code (GTC) is used for these studies and a new radial grid decomposition is presented and evaluated. Scaling of the code is demonstrated on ITER sized plasmas with up to 16K Cray XT3/4 cores.

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Scientific Application Performance on Candidate PetaScale Platforms

Cited by 34 publications

References 16 publications

Scientific and Computational Challenges of the Fusion Simulation Program (FSP)

Scientific and Computational Challenges of the Fusion Simulation Program (FSP)

Generalized utility metrics for supercomputers

Performance of particle in cell methods on highly concurrent computational architectures

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