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Tensor slicing and optimization for multicore NPUs

Overview of attention for article published in Journal of Parallel & Distributed Computing, May 2023
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (65th percentile)

Mentioned by

twitter
7 X users

Readers on

mendeley
10 Mendeley
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Title
Tensor slicing and optimization for multicore NPUs
Published in
Journal of Parallel & Distributed Computing, May 2023
DOI 10.1016/j.jpdc.2022.12.008
Authors

Rafael Sousa, Marcio Pereira, Yongin Kwon, Taeho Kim, Namsoon Jung, Chang Soo Kim, Michael Frank, Guido Araujo

X Demographics

X Demographics

The data shown below were collected from the profiles of 7 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 10 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 10 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 2 20%
Student > Ph. D. Student 2 20%
Other 2 20%
Professor > Associate Professor 1 10%
Student > Doctoral Student 1 10%
Other 0 0%
Unknown 2 20%
Readers by discipline Count As %
Computer Science 3 30%
Unspecified 2 20%
Business, Management and Accounting 1 10%
Engineering 1 10%
Unknown 3 30%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 17 April 2023.
All research outputs
#8,127,684
of 25,805,386 outputs
Outputs from Journal of Parallel & Distributed Computing
#163
of 702 outputs
Outputs of similar age
#139,980
of 411,548 outputs
Outputs of similar age from Journal of Parallel & Distributed Computing
#1
of 4 outputs
Altmetric has tracked 25,805,386 research outputs across all sources so far. This one has received more attention than most of these and is in the 67th percentile.
So far Altmetric has tracked 702 research outputs from this source. They receive a mean Attention Score of 4.4. This one has done well, scoring higher than 75% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 411,548 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 65% of its contemporaries.
We're also able to compare this research output to 4 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them