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Title: GeantV: From CPU to accelerators

Abstract

The GeantV project aims to research and develop the next-generation simulation software describing the passage of particles through matter. While the modern CPU architectures are being targeted first, resources such as GPGPU, Intel© Xeon Phi, Atom or ARM cannot be ignored anymore by HEP CPU-bound applications. The proof of concept GeantV prototype has been mainly engineered for CPU's having vector units but we have foreseen from early stages a bridge to arbitrary accelerators. A software layer consisting of architecture/technology specific backends supports currently this concept. This approach allows to abstract out the basic types such as scalar/vector but also to formalize generic computation kernels using transparently library or device specific constructs based on Vc, CUDA, Cilk+ or Intel intrinsics. While the main goal of this approach is portable performance, as a bonus, it comes with the insulation of the core application and algorithms from the technology layer. This allows our application to be long term maintainable and versatile to changes at the backend side. The paper presents the first results of basket-based GeantV geometry navigation on the Intel© Xeon Phi KNC architecture. We present the scalability and vectorization study, conducted using Intel performance tools, as well as our preliminary conclusionsmore » on the use of accelerators for GeantV transport. Lastly, we also describe the current work and preliminary results for using the GeantV transport kernel on GPUs.« less

Authors:
 [1];  [2];  [3];  [2];  [3];  [4];  [5];  [3];  [6];  [3];  [7];  [6];  [3];  [8];  [3];  [1];  [6];  [6];  [4];  [3] more »;  [3];  [3];  [3];  [4];  [3];  [3];  [3];  [3] « less
  1. Univ. Estadual Paulista (Brazil)
  2. Indian Institute of Technology (India)
  3. European Organization for Nuclear Research (CERN), Geneva (Switzerland)
  4. Bhabha Atomic Research Center (India)
  5. Univ. Estadual Paulista (Brazil); Mackenzie Presbyterian Univ. (Brazil)
  6. Fermi National Accelerator Lab. (FNAL), Batavia, IL (United States)
  7. Intel Corp., Santa Clara, CA (United States)
  8. European Organization for Nuclear Research (CERN), Geneva (Switzerland); Institute of Space Sciences (Romania)
Publication Date:
Research Org.:
Fermi National Accelerator Lab. (FNAL), Batavia, IL (United States)
Sponsoring Org.:
USDOE Office of Science (SC), High Energy Physics (HEP)
OSTI Identifier:
1346932
Report Number(s):
FERMILAB-CONF-16-625-CD
Journal ID: ISSN 1742-6588; 1499965
Grant/Contract Number:  
AC02-07CH11359
Resource Type:
Journal Article: Accepted Manuscript
Journal Name:
Journal of Physics. Conference Series
Additional Journal Information:
Journal Volume: 762; Journal Issue: 1; Journal ID: ISSN 1742-6588
Publisher:
IOP Publishing
Country of Publication:
United States
Language:
English
Subject:
43 PARTICLE ACCELERATORS; 97 MATHEMATICS AND COMPUTING

Citation Formats

Amadio, G., Ananya, A., Apostolakis, J., Arora, A., Bandieramonte, M., Bhattacharyya, A., Bianchini, C., Brun, R., Canal, P., Carminati, F., Duhem, L., Elvira, D., Gheata, A., Gheata, M., Goulas, I., Iope, R., Jun, S., Lima, G., Mohanty, A., Nikitina, T., Novak, M., Pokorski, W., Ribon, A., Sehgal, R., Shadura, O., Vallecorsa, S., Wenzel, S., and Zhang, Y. GeantV: From CPU to accelerators. United States: N. p., 2016. Web. doi:10.1088/1742-6596/762/1/012019.
Amadio, G., Ananya, A., Apostolakis, J., Arora, A., Bandieramonte, M., Bhattacharyya, A., Bianchini, C., Brun, R., Canal, P., Carminati, F., Duhem, L., Elvira, D., Gheata, A., Gheata, M., Goulas, I., Iope, R., Jun, S., Lima, G., Mohanty, A., Nikitina, T., Novak, M., Pokorski, W., Ribon, A., Sehgal, R., Shadura, O., Vallecorsa, S., Wenzel, S., & Zhang, Y. GeantV: From CPU to accelerators. United States. https://doi.org/10.1088/1742-6596/762/1/012019
Amadio, G., Ananya, A., Apostolakis, J., Arora, A., Bandieramonte, M., Bhattacharyya, A., Bianchini, C., Brun, R., Canal, P., Carminati, F., Duhem, L., Elvira, D., Gheata, A., Gheata, M., Goulas, I., Iope, R., Jun, S., Lima, G., Mohanty, A., Nikitina, T., Novak, M., Pokorski, W., Ribon, A., Sehgal, R., Shadura, O., Vallecorsa, S., Wenzel, S., and Zhang, Y. 2016. "GeantV: From CPU to accelerators". United States. https://doi.org/10.1088/1742-6596/762/1/012019. https://www.osti.gov/servlets/purl/1346932.
@article{osti_1346932,
title = {GeantV: From CPU to accelerators},
author = {Amadio, G. and Ananya, A. and Apostolakis, J. and Arora, A. and Bandieramonte, M. and Bhattacharyya, A. and Bianchini, C. and Brun, R. and Canal, P. and Carminati, F. and Duhem, L. and Elvira, D. and Gheata, A. and Gheata, M. and Goulas, I. and Iope, R. and Jun, S. and Lima, G. and Mohanty, A. and Nikitina, T. and Novak, M. and Pokorski, W. and Ribon, A. and Sehgal, R. and Shadura, O. and Vallecorsa, S. and Wenzel, S. and Zhang, Y.},
abstractNote = {The GeantV project aims to research and develop the next-generation simulation software describing the passage of particles through matter. While the modern CPU architectures are being targeted first, resources such as GPGPU, Intel© Xeon Phi, Atom or ARM cannot be ignored anymore by HEP CPU-bound applications. The proof of concept GeantV prototype has been mainly engineered for CPU's having vector units but we have foreseen from early stages a bridge to arbitrary accelerators. A software layer consisting of architecture/technology specific backends supports currently this concept. This approach allows to abstract out the basic types such as scalar/vector but also to formalize generic computation kernels using transparently library or device specific constructs based on Vc, CUDA, Cilk+ or Intel intrinsics. While the main goal of this approach is portable performance, as a bonus, it comes with the insulation of the core application and algorithms from the technology layer. This allows our application to be long term maintainable and versatile to changes at the backend side. The paper presents the first results of basket-based GeantV geometry navigation on the Intel© Xeon Phi KNC architecture. We present the scalability and vectorization study, conducted using Intel performance tools, as well as our preliminary conclusions on the use of accelerators for GeantV transport. Lastly, we also describe the current work and preliminary results for using the GeantV transport kernel on GPUs.},
doi = {10.1088/1742-6596/762/1/012019},
url = {https://www.osti.gov/biblio/1346932}, journal = {Journal of Physics. Conference Series},
issn = {1742-6588},
number = 1,
volume = 762,
place = {United States},
year = {Fri Jan 01 00:00:00 EST 2016},
month = {Fri Jan 01 00:00:00 EST 2016}
}

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