<div class="csl-bib-body">
<div class="csl-entry">Forsell, M., Roivainen, J., Leppänen, V., & Träff, J. L. (2023). Preliminary Performance and Memory Access Scalability Study of Thick Control Flow Processors. In J. Nurmi, M. Shen, P. Ellervee, P. Koch, & F. Moradi (Eds.), <i>Proceedings 2023 IEEE Nordic Circuits and Systems Conference (NorCAS)</i> (pp. 1–7). IEEE. https://doi.org/10.1109/NorCAS58970.2023.10305463</div>
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dc.identifier.uri
http://hdl.handle.net/20.500.12708/190270
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dc.description.abstract
Scalability of performance and memory bandwidth over a wide variety of computational and memory access patterns are important goals of multicore processor design. Current commercial processor lines are, however, not succeeding well in meeting key requirements for efficient parallel execution in their small, entry-level designs nor tolerating increasing latency of shared memory accesses, retaining memory access bandwidth per core and keeping the cost of synchronization low as the number of processor cores increases towards high-end products. We have introduced the thick control flow processor architecture (TPA), which combines an advanced shared memory abstraction architecture with the thick control flow (TCF) programming scheme and shown that it can address these requirements in its entry-level configuration. In this paper, we study the performance and memory access scalability of TCF processors. For that we measure the execution time of a number of parallel kernel programs and access patterns over a range of TPA processor configurations and compare them against each other and Intel Skylake-class client and server processors. The results indicate excellent scaling in both execution speed of kernels and bandwidth of memory access.
en
dc.language.iso
en
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dc.subject
parallel computing
en
dc.subject
processor architecture
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dc.subject
TCF
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dc.subject
performance scalablity
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dc.subject
memory access
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dc.title
Preliminary Performance and Memory Access Scalability Study of Thick Control Flow Processors
en
dc.type
Inproceedings
en
dc.type
Konferenzbeitrag
de
dc.contributor.affiliation
Digital Technologies, VTT
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dc.contributor.affiliation
Digital Technologies, VTT
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dc.contributor.affiliation
University of Turku, Finland
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dc.contributor.editoraffiliation
Aalborg University, Denmark
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dc.contributor.editoraffiliation
Tallinn University of Technology, Estonia
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dc.contributor.editoraffiliation
Aalborg University, Denmark
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dc.contributor.editoraffiliation
Aarhus University, Denmark
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dc.relation.isbn
979-8-3503-3757-0
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dc.relation.doi
10.1109/NorCAS58970.2023
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dc.description.startpage
1
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dc.description.endpage
7
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dc.type.category
Full-Paper Contribution
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tuw.booktitle
Proceedings 2023 IEEE Nordic Circuits and Systems Conference (NorCAS)
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tuw.peerreviewed
true
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tuw.relation.publisher
IEEE
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tuw.researchTopic.id
I2
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tuw.researchTopic.id
C5
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tuw.researchTopic.name
Computer Engineering and Software-Intensive Systems
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tuw.researchTopic.name
Computer Science Foundations
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tuw.researchTopic.value
90
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tuw.researchTopic.value
10
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tuw.publication.orgunit
E191-04 - Forschungsbereich Parallel Computing
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tuw.publisher.doi
10.1109/NorCAS58970.2023.10305463
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dc.description.numberOfPages
7
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tuw.author.orcid
0000-0002-4864-9226
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tuw.editor.orcid
0000-0002-0745-6743
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tuw.event.name
9th IEEE Nordic Circuits and Systems Conference (NorCAS 2023)