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Nordén, Markus
Publications (10 of 11) Show all publications
Nordén, M., Löf, H., Rantakokko, J. & Holmgren, S. (2007). Dynamic data migration for structured AMR solvers. International journal of parallel programming, 35, 477-491
Open this publication in new window or tab >>Dynamic data migration for structured AMR solvers
2007 (English)In: International journal of parallel programming, ISSN 0885-7458, E-ISSN 1573-7640, Vol. 35, p. 477-491Article in journal (Refereed) Published
National Category
Computer Sciences Computational Mathematics
Identifiers
urn:nbn:se:uu:diva-11396 (URN)10.1007/s10766-007-0056-z (DOI)000249405600004 ()
Available from: 2007-09-11 Created: 2007-09-11 Last updated: 2018-01-12Bibliographically approved
Nordén, M., Löf, H., Rantakokko, J. & Holmgren, S. (2006). Geographical locality and dynamic data migration for OpenMP implementations of adaptive PDE solvers.
Open this publication in new window or tab >>Geographical locality and dynamic data migration for OpenMP implementations of adaptive PDE solvers
2006 (English)Report (Other academic)
Series
Technical report / Department of Information Technology, Uppsala University, ISSN 1404-3203 ; 2006-038
National Category
Computer Sciences Computational Mathematics
Identifiers
urn:nbn:se:uu:diva-81928 (URN)
Available from: 2008-02-15 Created: 2008-02-15 Last updated: 2018-01-13Bibliographically approved
Nordén, M. (2006). Multithreaded PDE Solvers on Non-Uniform Memory Architectures. (Doctoral dissertation). Uppsala: Acta Universitatis Upsaliensis
Open this publication in new window or tab >>Multithreaded PDE Solvers on Non-Uniform Memory Architectures
2006 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

A trend in parallel computer architecture is that systems with a large shared memory are becoming more and more popular. A shared memory system can be either a uniform memory architecture (UMA) or a cache coherent non-uniform memory architecture (cc-NUMA).

In the present thesis, the performance of parallel PDE solvers on cc-NUMA computers is studied. In particular, we consider the shared namespace programming model, represented by OpenMP. Since the main memory is physically, or geographically distributed over several multi-processor nodes, the latency for local memory accesses is smaller than for remote accesses. Therefore, the geographical locality of the data becomes important.

The focus of the present thesis is to study multithreaded PDE solvers on cc-NUMA systems, in particular their memory access pattern with respect to geographical locality. The questions posed are: (1) How large is the influence on performance of the non-uniformity of the memory system? (2) How should a program be written in order to reduce this influence? (3) Is it possible to introduce optimizations in the computer system for this purpose?

The main conclusion is that geographical locality is important for performance on cc-NUMA systems. This is shown experimentally for a broad range of PDE solvers as well as theoretically using a model involving characteristics of computer systems and applications.

Geographical locality can be achieved through migration directives that are inserted by the programmer or — possibly in the future — automatically by the compiler. On some systems, it can also be accomplished by means of transparent, hardware initiated migration and replication. However, a necessary condition that must be fulfilled if migration is to be effective is that the memory access pattern must not be "speckled", i.e. as few threads as possible shall make accesses to each memory page.

We also conclude that OpenMP is competitive with MPI on cc-NUMA systems if care is taken to get a favourable data distribution.

Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis, 2006. p. 33
Series
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Science and Technology, ISSN 1651-6214 ; 224
Keywords
PDE solver, high-performance, NUMA, UMA, OpenMP, MPI, data migration, data replication, thread scheduling, data affinity
National Category
Software Engineering
Research subject
Scientific Computing
Identifiers
urn:nbn:se:uu:diva-7149 (URN)91-554-6656-7 (ISBN)
Public defence
2006-10-20, Room 2446, Polacksbacken, Lägerhyddsvägen 2D, Uppsala, 10:15 (English)
Opponent
Supervisors
Available from: 2006-09-28 Created: 2006-09-28 Last updated: 2018-01-13Bibliographically approved
Nordén, M., Holmgren, S. & Thuné, M. (2006). OpenMP versus MPI for PDE solvers based on regular sparse numerical operators. Future generations computer systems, 22, 194-203
Open this publication in new window or tab >>OpenMP versus MPI for PDE solvers based on regular sparse numerical operators
2006 (English)In: Future generations computer systems, ISSN 0167-739X, E-ISSN 1872-7115, Vol. 22, p. 194-203Article in journal (Refereed) Published
National Category
Software Engineering Computational Mathematics
Identifiers
urn:nbn:se:uu:diva-47210 (URN)10.1016/j.future.2003.09.004 (DOI)000234408800016 ()
Available from: 2006-05-23 Created: 2006-05-23 Last updated: 2018-01-11Bibliographically approved
Nordén, M. (2006). Performance modelling for parallel PDE solvers on NUMA-systems.
Open this publication in new window or tab >>Performance modelling for parallel PDE solvers on NUMA-systems
2006 (English)Report (Other academic)
Series
Technical report / Department of Information Technology, Uppsala University, ISSN 1404-3203 ; 2006-041
National Category
Computer Sciences Computational Mathematics
Identifiers
urn:nbn:se:uu:diva-81930 (URN)
Available from: 2008-02-19 Created: 2008-02-19 Last updated: 2018-01-13Bibliographically approved
Löf, H., Nordén, M. & Holmgren, S. (2004). Improving Geographical Locality of Data for Shared Memory Implementations of PDE Solvers. In: Computational Science – ICCS 2004 (pp. 9-16). Berlin: Springer-Verlag
Open this publication in new window or tab >>Improving Geographical Locality of Data for Shared Memory Implementations of PDE Solvers
2004 (English)In: Computational Science – ICCS 2004, Berlin: Springer-Verlag , 2004, p. 9-16Conference paper, Published paper (Refereed)
Place, publisher, year, edition, pages
Berlin: Springer-Verlag, 2004
Series
Lecture Notes in Computer Science ; 3037
National Category
Computer Sciences Computational Mathematics
Identifiers
urn:nbn:se:uu:diva-71098 (URN)10.1007/b97988 (DOI)
Available from: 2007-03-11 Created: 2007-03-11 Last updated: 2018-01-10Bibliographically approved
Löf, H., Nordén, M. & Holmgren, S. (2004). Improving geographical locality of data for shared memory implementations of PDE solvers.
Open this publication in new window or tab >>Improving geographical locality of data for shared memory implementations of PDE solvers
2004 (English)Report (Other academic)
Series
Technical report / Department of Information Technology, Uppsala University, ISSN 1404-3203 ; 2004-006
National Category
Computer Sciences Computational Mathematics
Identifiers
urn:nbn:se:uu:diva-66907 (URN)
Available from: 2006-12-05 Created: 2006-12-05 Last updated: 2018-01-10Bibliographically approved
Nordén, M. (2004). Parallel PDE Solvers on cc-NUMA Systems. (Licentiate dissertation). Uppsala University
Open this publication in new window or tab >>Parallel PDE Solvers on cc-NUMA Systems
2004 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

The current trend in parallel computers is that systems with a large shared memory are becoming more and more popular. A shared memory system can be either a uniform memory architecture (UMA) or a cache coherent non-uniform memory architecture (cc-NUMA).

In the present thesis, the performance of parallel PDE solvers on cc-NUMA computers is studied. In particular, we consider the shared namespace programming model, represented by OpenMP. Since the main memory is physically, or geographically distributed over several multi-processor nodes, the latency for local memory accesses is smaller than for remote accesses. Therefore, the geographical locality of the data becomes important.

The questions posed in this thesis are: (1) How large is the influence on performance of the non-uniformity of the memory system? (2) How should a program be written in order to reduce this influence? (3) Is it possible to introduce optimizations in the computer system for this purpose?

Most of the application codes studied address the Euler equations using a finite difference method and a finite volume method respectively and are parallelized with OpenMP. Comparisons are made with an alternative implementation using MPI and with PDE solvers implemented with OpenMP that solve other equations using different numerical methods.

The main conclusion is that geographical locality is important for performance on cc-NUMA systems. This can be achieved through self optimization provided in the system or through migrate-on-next-touch directives that could be inserted automatically by the compiler.

We also conclude that OpenMP is competitive with MPI on cc-NUMA systems if care is taken to get a favourable data distribution.

Place, publisher, year, edition, pages
Uppsala University, 2004
Series
Information technology licentiate theses: Licentiate theses from the Department of Information Technology, ISSN 1404-5117 ; 2004-002
National Category
Software Engineering
Research subject
Scientific Computing
Identifiers
urn:nbn:se:uu:diva-86307 (URN)
Supervisors
Available from: 2004-03-26 Created: 2006-05-14 Last updated: 2018-01-13Bibliographically approved
Nordén, M., Holmgren, S. & Thuné, M. (2002). OpenMP versus MPI for PDE solvers based on regular sparse numerical operators. In: Computational Science – ICCS 2002 (pp. 681-690). Berlin: Springer-Verlag
Open this publication in new window or tab >>OpenMP versus MPI for PDE solvers based on regular sparse numerical operators
2002 (English)In: Computational Science – ICCS 2002, Berlin: Springer-Verlag , 2002, p. 681-690Conference paper, Published paper (Other academic)
Place, publisher, year, edition, pages
Berlin: Springer-Verlag, 2002
Series
Lecture Notes in Computer Science ; 2331
National Category
Software Engineering Computational Mathematics
Identifiers
urn:nbn:se:uu:diva-44296 (URN)
Available from: 2006-05-17 Created: 2006-05-17 Last updated: 2018-01-11Bibliographically approved
Holmgren, S., Nordén, M., Rantakokko, J. & Wallin, D. (2002). Performance of PDE solvers on a self-optimizing NUMA architecture. Parallel Algorithms and Applications, 17, 285-299
Open this publication in new window or tab >>Performance of PDE solvers on a self-optimizing NUMA architecture
2002 (English)In: Parallel Algorithms and Applications, ISSN 1063-7192, E-ISSN 1029-032X, Vol. 17, p. 285-299Article in journal (Refereed) Published
National Category
Computer Sciences Computational Mathematics
Identifiers
urn:nbn:se:uu:diva-66909 (URN)10.1080/01495730208941445 (DOI)
Available from: 2006-05-22 Created: 2006-05-22 Last updated: 2018-01-10Bibliographically approved
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