| Title |
Using meta-heuristics and machine learning for software optimization of parallel computing systems: a systematic literature review
|
|---|---|
| Published in |
Computing, April 2018
|
| DOI | 10.1007/s00607-018-0614-9 |
| Authors |
Suejb Memeti, Sabri Pllana, Alécio Binotto, Joanna Kołodziej, Ivona Brandic |
X Demographics
The data shown below were collected from the profiles of 16 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 5 | 31% |
| United Kingdom | 2 | 13% |
| Austria | 2 | 13% |
| Sri Lanka | 1 | 6% |
| Unknown | 6 | 38% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 11 | 69% |
| Scientists | 3 | 19% |
| Science communicators (journalists, bloggers, editors) | 1 | 6% |
| Unknown | 1 | 6% |
Mendeley readers
The data shown below were compiled from readership statistics for 133 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 133 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 26 | 20% |
| Student > Master | 17 | 13% |
| Student > Bachelor | 11 | 8% |
| Student > Doctoral Student | 8 | 6% |
| Researcher | 7 | 5% |
| Other | 19 | 14% |
| Unknown | 45 | 34% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 50 | 38% |
| Engineering | 15 | 11% |
| Business, Management and Accounting | 4 | 3% |
| Decision Sciences | 4 | 3% |
| Mathematics | 2 | 2% |
| Other | 10 | 8% |
| Unknown | 48 | 36% |
Attention Score in Context
This research output has an Altmetric Attention Score of 14. 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 21 September 2023.
All research outputs
#2,593,567
of 25,637,545 outputs
Outputs from Computing
#9
of 235 outputs
Outputs of similar age
#52,114
of 340,571 outputs
Outputs of similar age from Computing
#2
of 2 outputs
Altmetric has tracked 25,637,545 research outputs across all sources so far. Compared to these this one has done well and is in the 89th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 235 research outputs from this source. They receive a mean Attention Score of 4.5. This one has done particularly well, scoring higher than 96% 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 340,571 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 84% of its contemporaries.
We're also able to compare this research output to 2 others from the same source and published within six weeks on either side of this one.