Space-Efficient k-d Tree-Based Storage Format for Sparse Tensors

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21240%2F20%3A00341786" target="_blank" >RIV/68407700:21240/20:00341786 - isvavai.cz</a>

Výsledek na webu

<a href="https://doi.org/10.1145/3369583.3392692" target="_blank" >https://doi.org/10.1145/3369583.3392692</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1145/3369583.3392692" target="_blank" >10.1145/3369583.3392692</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Space-Efficient k-d Tree-Based Storage Format for Sparse Tensors

Popis výsledku v původním jazyce

Computations with tensors are widespread in many scientific areas. Usually, the used tensors are very large but sparse, i.e., the vast majority of their elements are zero. The space complexity of sparse tensor storage formats varies significantly. For overall efficiency, it is important to reduce the execution time and additional space requirements of the initial preprocessing (i.e., converting tensors from common storage formats to the given internal format). The main contributions of this paper are threefold. Firstly, we present a new storage format for sparse tensors, which we call the succinct k-d tree-based tensor (SKTB) format. We compare the space complexity of common tensor storage formats and of the SKTB format and demonstrate the viability of using a tree as a data structurefor sparse tensors. Secondly, we present a parallel space-efficient algorithm for converting tensors to the SKTB format. Thirdly, we demonstrate the computational efficiency of the proposed format in sparse tensor-vector multiplication.

Název v anglickém jazyce

Space-Efficient k-d Tree-Based Storage Format for Sparse Tensors

Popis výsledku anglicky

Computations with tensors are widespread in many scientific areas. Usually, the used tensors are very large but sparse, i.e., the vast majority of their elements are zero. The space complexity of sparse tensor storage formats varies significantly. For overall efficiency, it is important to reduce the execution time and additional space requirements of the initial preprocessing (i.e., converting tensors from common storage formats to the given internal format). The main contributions of this paper are threefold. Firstly, we present a new storage format for sparse tensors, which we call the succinct k-d tree-based tensor (SKTB) format. We compare the space complexity of common tensor storage formats and of the SKTB format and demonstrate the viability of using a tree as a data structurefor sparse tensors. Secondly, we present a parallel space-efficient algorithm for converting tensors to the SKTB format. Thirdly, we demonstrate the computational efficiency of the proposed format in sparse tensor-vector multiplication.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

<a href="/cs/project/EF16_019%2F0000765" target="_blank" >EF16_019/0000765: Výzkumné centrum informatiky</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2020

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Proceedings of the 29th International Symposium on High-Performance Parallel and Distributed Computing

ISBN

978-1-4503-7052-3

ISSN

—

e-ISSN

—

Počet stran výsledku

5

Strana od-do

29-33

Název nakladatele

Association for Computing Machinery

Místo vydání

New York

Místo konání akce

Stockholm

Datum konání akce

23. 6. 2020

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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