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Dataflow Implementation of QR Decomposition on a Manycore
Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Centre for Research on Embedded Systems (CERES). (EPC Group)ORCID iD: 0000-0001-8652-0098
Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Centre for Research on Embedded Systems (CERES).
Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Centre for Research on Embedded Systems (CERES).
Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Centre for Research on Embedded Systems (CERES).ORCID iD: 0000-0002-4932-4036
Show others and affiliations
2016 (English)In: MES '16: Proceedings of the Third ACM International Workshop on Many-core Embedded Systems, New York, NY: ACM Press, 2016, 26-30 p.Conference paper (Refereed)
Abstract [en]

While parallel computer architectures have become mainstream, application development on them is still challenging. There is a need for new tools, languages and programming models. Additionally, there is a lack of knowledge about the performance of parallel approaches of basic but important operations, such as the QR decomposition of a matrix, on current commercial manycore architectures.

This paper evaluates a high level dataflow language (CAL), a source-to-source compiler (Cal2Many) and three QR decomposition algorithms (Givens Rotations, Householder and Gram-Schmidt). The algorithms are implemented both in CAL and hand-optimized C languages, executed on Adapteva's Epiphany manycore architecture and evaluated with respect to performance, scalability and development effort.

The performance of the CAL (generated C) implementations gets as good as 2\% slower than the hand-written versions. They require an average of 25\% fewer lines of source code without significantly increasing the binary size. Development effort is reduced and debugging is significantly simplified. The implementations executed on Epiphany cores outperform the GNU scientific library on the host ARM processor of the Parallella board by up to 30x. © 2016 Copyright held by the owner/author(s).

Place, publisher, year, edition, pages
New York, NY: ACM Press, 2016. 26-30 p.
National Category
Embedded Systems
Identifiers
URN: urn:nbn:se:hh:diva-32371DOI: 10.1145/2934495.2934499ScopusID: 2-s2.0-84991106778ISBN: 978-1-4503-4262-9 (print)OAI: oai:DiVA.org:hh-32371DiVA: diva2:1044642
Conference
MES '16, International Workshop on Many-core Embedded Systems, Seoul, Republic of Korea, June 19, 2016
Projects
ESCHERHiPEC
Funder
Knowledge FoundationSwedish Foundation for Strategic Research ELLIIT - The Linköping‐Lund Initiative on IT and Mobile Communications
Available from: 2016-11-04 Created: 2016-11-04 Last updated: 2017-05-05Bibliographically approved
In thesis
1. Utilizing Heterogeneity in Manycore Architectures for Streaming Applications
Open this publication in new window or tab >>Utilizing Heterogeneity in Manycore Architectures for Streaming Applications
2017 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

In the last decade, we have seen a transition from single-core to manycore in computer architectures due to performance requirements and limitations in power consumption and heat dissipation. The first manycores had homogeneous architectures consisting of a few identical cores. However, the applications, which are executed on these architectures, usually consist of several tasks requiring different hardware resources to be executed efficiently. Therefore, we believe that utilizing heterogeneity in manycores will increase the efficiency of the architectures in terms of performance and power consumption. However, development of heterogeneous architectures is more challenging and the transition from homogeneous to heterogeneous architectures will increase the difficulty of efficient software development due to the increased complexity of the architecture. In order to increase the efficiency of hardware and software development, new hardware design methods and software development tools are required. Additionally, there is a lack of knowledge on the performance of applications when executed on manycore architectures.

The transition began with a shift from single-core architectures to homogeneous multicore architectures consisting of a few identical cores. It now continues with a shift from homogeneous architectures with identical cores to heterogeneous architectures with different types of cores specialized for different purposes. However, this transition has increased the complexity of architectures and hence the complexity of software development and execution. In order to decrease the complexity of software development, new software tools are required. Additionally, there is a lack of knowledge on what kind of heterogeneous manycore design is most efficient for different applications and what are the performances of these applications when executed on current commercial manycores.

This thesis studies manycore architectures in order to reveal possible uses of heterogeneity in manycores and facilitate choice of architecture for software and hardware developers. It defines a taxonomy for manycore architectures that is based on the levels of heterogeneity they contain and discusses benefits and drawbacks of these levels. Additionally, it evaluates several applications, a dataflow language (CAL), a source-to-source compilation framework (Cal2Many), and a commercial manycore architecture (Epiphany). The compilation framework takes implementations written in the dataflow language as input and generates code targetting different manycore platforms. Based on these evaluations, the thesis identifies the bottlenecks of the architecture. It finally presents a methodology for developing heterogeneoeus manycore architectures which target specific application domains.

Our studies show that using different types of cores in manycore architectures has the potential to increase the performance of streaming applications. If we add specialized hardware blocks to a core, the performance easily increases by 15x for the target application while the core size increases by 40-50% which can be optimized further. Other results prove that dataflow languages, together with software development tools, decrease software development efforts significantly (25-50%) while having a small impact (2-17%) on the performance.

Place, publisher, year, edition, pages
Halmstad: Halmstad University Press, 2017. 78 p.
Series
Halmstad University Dissertations, 29
Keyword
Manycores, parallel architectures, parallelism, streaming applications, dataflow, manycore design, heterogeneous manycores
National Category
Computer Systems
Identifiers
urn:nbn:se:hh:diva-33792 (URN)978-91-87045-60-8 (ISBN)978-91-87045-61-5 (ISBN)
Presentation
2017-06-02, Wigforss, Kristian IV:s väg 3, Halmstad, 13:15 (English)
Opponent
Supervisors
Projects
HiPEC (High Performance Embedded Computing)NGES (Towards Next Generation Embedded Systems: Utilizing Parallelism and Reconfigurability)
Funder
VINNOVASwedish Foundation for Strategic Research
Available from: 2017-05-09 Created: 2017-05-05 Last updated: 2017-05-09Bibliographically approved

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