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Title: WARP

Abstract

WARP, which can stand for ``Weaving All the Random Particles,'' is a three-dimensional (3D) continuous energy Monte Carlo neutron transport code developed at UC Berkeley to efficiently execute on NVIDIA graphics processing unit (GPU) platforms. WARP accelerates Monte Carlo simulations while preserving the benefits of using the Monte Carlo method, namely, that very few physical and geometrical simplifications are applied. WARP is able to calculate multiplication factors, neutron flux distributions (in both space and energy), and fission source distributions for time-independent neutron transport problems. It can run in both criticality or fixed source modes, but fixed source mode is currently not robust, optimized, or maintained in the newest version. WARP can transport neutrons in unrestricted arrangements of parallelepipeds, hexagonal prisms, cylinders, and spheres. The goal of developing WARP is to investigate algorithms that can grow into a full-featured, continuous energy, Monte Carlo neutron transport code that is accelerated by running on GPUs. The crux of the effort is to make Monte Carlo calculations faster while producing accurate results. Modern supercomputers are commonly being built with GPU coprocessor cards in their nodes to increase their computational efficiency and performance. GPUs execute efficiently on data-parallel problems, but most CPU codes, including thosemore » for Monte Carlo neutral particle transport, are predominantly task-parallel. WARP uses a data-parallel neutron transport algorithm to take advantage of the computing power GPUs offer.« less

Authors:
ORCiD logo [1]; ORCiD logo [1]
  1. University of California - Berkeley
Publication Date:
Research Org.:
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Sponsoring Org.:
USDOE National Nuclear Security Administration (NNSA)
Contributing Org.:
University of California - Berkeley
OSTI Identifier:
1357227
Report Number(s):
WARP; 005219WKSTN00
DOE Contract Number:
NA0000979
Resource Type:
Software
Software Revision:
00
Software Package Number:
005219
Software CPU:
WKSTN
Open Source:
Yes
https://github.com/weft
Source Code Available:
Yes
Other Software Info:
Publications: doi:10.1016/j.anucene.2014.10.039 doi:10.1016/j.anucene.2017.01.027
Related Software:
CUB, moderngpu
Country of Publication:
United States

Citation Formats

Bergmann, Ryan M., and Rowland, Kelly L. WARP. Computer software. https://www.osti.gov//servlets/purl/1357227. Vers. 00. USDOE National Nuclear Security Administration (NNSA). 12 Apr. 2017. Web.
Bergmann, Ryan M., & Rowland, Kelly L. (2017, April 12). WARP (Version 00) [Computer software]. https://www.osti.gov//servlets/purl/1357227.
Bergmann, Ryan M., and Rowland, Kelly L. WARP. Computer software. Version 00. April 12, 2017. https://www.osti.gov//servlets/purl/1357227.
@misc{osti_1357227,
title = {WARP, Version 00},
author = {Bergmann, Ryan M. and Rowland, Kelly L.},
abstractNote = {WARP, which can stand for ``Weaving All the Random Particles,'' is a three-dimensional (3D) continuous energy Monte Carlo neutron transport code developed at UC Berkeley to efficiently execute on NVIDIA graphics processing unit (GPU) platforms. WARP accelerates Monte Carlo simulations while preserving the benefits of using the Monte Carlo method, namely, that very few physical and geometrical simplifications are applied. WARP is able to calculate multiplication factors, neutron flux distributions (in both space and energy), and fission source distributions for time-independent neutron transport problems. It can run in both criticality or fixed source modes, but fixed source mode is currently not robust, optimized, or maintained in the newest version. WARP can transport neutrons in unrestricted arrangements of parallelepipeds, hexagonal prisms, cylinders, and spheres. The goal of developing WARP is to investigate algorithms that can grow into a full-featured, continuous energy, Monte Carlo neutron transport code that is accelerated by running on GPUs. The crux of the effort is to make Monte Carlo calculations faster while producing accurate results. Modern supercomputers are commonly being built with GPU coprocessor cards in their nodes to increase their computational efficiency and performance. GPUs execute efficiently on data-parallel problems, but most CPU codes, including those for Monte Carlo neutral particle transport, are predominantly task-parallel. WARP uses a data-parallel neutron transport algorithm to take advantage of the computing power GPUs offer.},
url = {https://www.osti.gov//servlets/purl/1357227},
doi = {},
year = {Wed Apr 12 00:00:00 EDT 2017},
month = {Wed Apr 12 00:00:00 EDT 2017},
note =
}

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  • This milestone has been accomplished. The Heavy Ion Fusion Science Virtual National Laboratory (HIFS-VNL) has developed and implemented an initial beam-in-plasma implicit modeling capability in Warp; has carried out tests validating the behavior of the models employed; has compared the results of electrostatic and electromagnetic models when applied to beam expansion in an NDCX-I relevant regime; has compared Warp and LSP results on a problem relevant to NDCX-I; has modeled wave excitation by a rigid beam propagating through plasma; and has implemented and begun testing a more advanced implicit method that correctly captures electron drift motion even when timesteps toomore » large to resolve the electron gyro-period are employed. The HIFS-VNL is well on its way toward having a state-of-the-art source-to-target simulation capability that will enable more effective support of ongoing experiments in the NDCX series and allow more confident planning for future ones.« less
  • This paper describes the Time Warp Operating System, under development for three years at the Jet Propulsion Laboratory for the Caltech Mark III Hypercube multiprocessor. Its primary goal is concurrent execution of large, irregular discrete event simulations at maximum speed. It also supports any other distributed applications that are synchronized by virtual time. In this paper, the authors review the mechanics of Time Warp, describe the TWOS operating system, show how to construct simulations in object-oriented form to run under TWOS, and offer a qualitative comparison of Time Warp to the Chandy-Misra method of distributed simulation. They also include detailsmore » of two benchmark simulations and preliminary measurements of time-to-completion, speedup, rollback rate, and antimessage rate, all as functions of the number of processors used.« less
  • In the course of implementing low-level (image to image) vision algorithms on Warp, the authors have understood the mapping of this class of algorithms well enough so that the programming of these algorithms is now a straightforward and stereotypical task. The partitioning method used is input partitioning, which provides an efficient, natural implementation of this class of algorithms. A special programming language call Apply was developed, which reduces the problem of writing the algorithm for this class of programs to the task of writing the function to be applied to a window around a single pixel. Apply provides a methodmore » for programming Warp in these applications that is easy, consistent, and efficient. Apply is application-specific, but machine independent, it is possible to implement versions of Apply that run efficiently on a wide variety of computers. Implementations are described of Apply on Warp, UNIX and the Hughes HBA, and implementation is sketched on bit-serial processor arrays and distributed-memory machines.« less
  • A variation of the Time Warp parallel discrete-event simulation mechanism is presented that is optimized for execution on a shared-memory multiprocessor. In particular, the direct cancellation mechanism is proposed that eliminates the need for anti-messages and provides an efficient mechanism for cancelling erroneous computations. The mechanism thereby eliminates many of the overheads associated with conventional, message-based implementations of Time Warp. More importantly, this mechanism effects rapid repairs of the parallel computation when an error is discovered. Initial performance measurements of an implementation of the mechanism executing on a BBN Butterfly multiprocessor are presented. These measurements indicate that the mechanism achievesmore » good performance, particularly for many workloads where conservative clock synchronization algorithms perform poorly. Speedups as high as 56.8 using 64 processors were obtained. However, the studies also indicate that state saving overheads represent a significant stumbling block for many parallel simulations using Time Warp.« less
  • Drying sized textile warp yarns without contacting the warp is easily accomplished by either radio frequency or infrared techniques. Although the process is more expensive than conventional drying, the substantial savings accrued during subsequent weaving and finishing of the cloth can help keep the US textile industry competitive and support electrical load. 5 refs., 8 figs., 14 tabs.

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