Steven Lantz
Cornell University
36 Papers
57 Citations
Steven Lantz is an academic researcher from Cornell University. The author has contributed to research in topics: Event reconstruction & Xeon Phi. The author has an hindex of 12, co-authored 33 publications.
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Papers
Computationally efficient implementation of combustion chemistry in parallel PDF calculations
TL;DR: The ISAT algorithm is extended to the multi-processor environment, with the aim of minimizing the wall clock time required for the whole ensemble, and an adaptive distribution strategy, which blends PLP, URAN and PREF, is devised and implemented.
46
Large-scale parallel simulations of turbulent combustion using combined dimension reduction and tabulation of chemistry
Varun Hiremath,Steven Lantz,Haifeng Wang,Stephen B. Pope +3 more
- 22 May 2012
TL;DR: A combined dimension reduction and tabulation strategy for implementing chemistry in large scale parallel Large-Eddy Simulation (LES)/ Probability Density Function (PDF) computations of turbulent reacting flows and shows that relative to using ISAT alone with the 38-species full representation, the combined ISAT/RCCE approach is efficient.
Dynamical Behavior of Magnetic Fields in a Stratified, Convecting Fluid Layer
Steven Lantz
- 01 Nov 1991
TL;DR: In this paper, the mixing length theory of convection (MLT) is reviewed; from this, a scaling law for convective structures is derived and compared with observations of the solar convection zone.
22
Speeding up particle track reconstruction using a parallel Kalman filter algorithm
Steven Lantz,Kevin Mcdermott,Michael Reid,Daniel Riley,Peter Wittich,S. Berkman,Giuseppe Benedetto Cerati,Matti J Kortelainen,A. Reinsvold Hall,P. Elmer,Bei Wang,Leonardo Giannini,Vyacheslav Krutelyov,Mario Masciovecchio,M. Tadel,Frank Würthwein,A. Yagil,Brian Gravelle,Boyana Norris +18 more
TL;DR: The design and performance of the improved tracking algorithm, referred to as mkFit, is discussed, containing dedicated code to optimally vectorize operations on small matrices, which is comparable to the nominal CMS tracking algorithm when reconstructing tracks from simulated proton-proton collisions within the CMS detector.
Kalman Filter Tracking on Parallel Architectures
Giuseppe Benedetto Cerati,Peter Elmer,Slava Krutelyov,Steven Lantz,Matthieu Lefebvre,Kevin Mcdermott,Daniel Riley,M. Tadel,Peter Wittich,Frank Würthwein,A. Yagil +10 more
TL;DR: It is shown how the data and associated tasks can be organized in a way that is conducive to both multithreading and vectorization, and very good performance on Intel Xeon and Xeon Phi architectures is demonstrated, as well as promising first results on Nvidia GPUs.