Skip to main content
Disciplines
Automotive Business IT + Informatics Construction + Real Estate Electrical Engineering + Electronics Energy + Sustainability Insurance + Risk Finance + Banking Management + Leadership Marketing + Sales Mechanical Engineering + Materials
Events
DE
EN
Books
Journals
Topic Page
Marketing
Start single access now
Access for companies
EXTENDED SEARCH
Log in
Top
Published in:
Behavioral Emulation for Scalable Design-Space Exploration of Algorithms and Architectures Read chapter Read first chapter

2016 | OriginalPaper | Chapter

Applying the Roofline Performance Model to the Intel Xeon Phi Knights Landing Processor

Authors : Douglas Doerfler, Jack Deslippe, Samuel Williams, Leonid Oliker, Brandon Cook, Thorsten Kurth, Mathieu Lobet, Tareq Malas, Jean-Luc Vay, Henri Vincenti

Published in: High Performance Computing

Publisher: Springer International Publishing

Log in

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

The Roofline Performance Model is a visually intuitive method used to bound the sustained peak floating-point performance of any given arithmetic kernel on any given processor architecture. In the Roofline, performance is nominally measured in floating-point operations per second as a function of arithmetic intensity (operations per byte of data). In this study we determine the Roofline for the Intel Knights Landing (KNL) processor, determining the sustained peak memory bandwidth and floating-point performance for all levels of the memory hierarchy, in all the different KNL cluster modes. We then determine arithmetic intensity and performance for a suite of application kernels being targeted for the KNL based supercomputer Cori, and make comparisons to current Intel Xeon processors. Cori is the National Energy Research Scientific Computing Center’s (NERSC) next generation supercomputer. Scheduled for deployment mid-2016, it will be one of the earliest and largest KNL deployments in the world.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

inform now
previous chapter Application Suitability Assessment for Many-Core Targets
next chapter Dynamic SIMD Vector Lane Scheduling
Footnotes
1
We added a #pragma unroll (8) around the inner loop to enable vectorization.
 
Literature
1.
Aktulga, H.M., Buluc, A., Williams, S., Yang, C.: Optimizing sparse matrix-multiple vector multiplication for nuclear configuration interaction calculations. In: International Parallel and Distributed Processing Symposium (IPDPS 2014), May 2014
2.
Aktulga, H.M., Yang, C., Ng, E.G., Maris, P., Vary, J.P.: Improving the scalability of a symmetric iterative eigensolver for multi-core platforms. Concurrency Comput. Pract. Exp. 26(16), 2631–2651 (2014). doi:10.​1002/​cpe.​3129 CrossRef
3.
4.
Birdsall, C.K., Langdon, A.B.: Plasma Physics Via Computer Simulation. Series in Plasma Physics. CRC Press, Boca Raton (2005)
5.
6.
7.
Doerfler, D.: Understanding application data movement characteristics using intel vtune amplifier and software development emulator tools. In: IXPUG 2015, Berkeley, CA, September 28 - October 2 2015
8.
Hill, M.D., Smith, A.J.: Evaluating associativity in CPU caches. IEEE Trans. Comput. 38(12), 1612–1630 (1989)CrossRef
9.
10.
11.
Malas, T., Kurth, T., Deslippe, J.: Optimization of the sparse matrix-vector products of an idr krylov iterative solver for the intel knl manycore processor (in preparation)
12.
13.
14.
15.
16.
17.
18.
19.
20.
Vincenti, H., Lehe, R., Sasanka, R., Vay, J.: An efficient and portable SIMD algorithm for charge/current deposition in Particle-In-Cell codes. ArXiv e-prints, January 2016
21.
Williams, S.: Auto-tuning Performance on Multicore Computers. Ph.D. thesis, EECS Department, University of California, Berkeley, December 2008
22.
Williams, S., Watterman, A., Patterson, D.: Roofline: an insightful visual performance model for floating-point programs and multicore architectures. Commun. ACM 52(4), 65–76 (2009)CrossRef
23.
Metadata
Title
Applying the Roofline Performance Model to the Intel Xeon Phi Knights Landing Processor
Authors
Douglas Doerfler
Jack Deslippe
Samuel Williams
Leonid Oliker
Brandon Cook
Thorsten Kurth
Mathieu Lobet
Tareq Malas
Jean-Luc Vay
Henri Vincenti
Copyright Year
2016
Book
High Performance Computing

Print ISBN: 978-3-319-46078-9

Electronic ISBN: 978-3-319-46079-6

Copyright Year: 2016

DOI
https://doi.org/10.1007/978-3-319-46079-6_24