| docid.id | IEEE 2937-2022 |
|---|---|
| docid.type | IEEE |
| docid.primary | True |
| docid#2.id | IEEE 2937™-2022 |
| docid#2.type | IEEE |
| docid#2.primary | True |
| docid#2.scope | trademark |
| docid#3.id | 978-1-5044-8854-9 |
| docid#3.type | ISBN |
| docid#4.id | 10.1109/IEEESTD.2022.9930948 |
| docid#4.type | DOI |
| docnumber | IEEE 2937-2022 |
| language | en |
| type | standard |
| script | Latn |
| date.value | 2022 |
| date.type | created |
| date#2.value | Jan. 19, 2023 |
| date#2.type | published |
| date#3.value | June 16, 2022 |
| date#3.type | issued |
| link.content | https://ieeexplore.ieee.org/document/9930948 |
| link.type | src |
| title.content | IEEE Standard for Performance Benchmarking for Artificial Intelligence Server Systems |
| title.format | text/plain |
| title.type | main |
| abstract.content | Artificial intelligence (AI) computing differs from generic computing in terms of device formation, operators, and usage. AI server systems, including AI server, cluster, and high-performance computing (HPC) infrastructures are designed specifically for this purpose. The performance of these infrastructures is important to users not only on generic models but also on the ones for specific domains. Formal methods for the performance benchmarking for AI server systems are provided in this standard, including approaches for test, metrics, and measure. In addition, the technical requirements for benchmarking tools are discussed. |
| abstract.format | text/plain |
| abstract.script | Latn |
| abstract.language | en |
| revdate | Jan. 19, 2023 |
| contributor.role.type | publisher |
| contributor.organization.name.content | Institute of Electrical and Electronics Engineers |
| contributor.organization.contact.address.city | New York |
| contributor.organization.contact.address.country | USA |
| contributor.organization.url | http://www.ieee.org |
| contributor.organization.abbreviation.content | IEEE |
| keyword | IEEE Standards |
| keyword#2 | Benchmark testing |
| keyword#3 | Artificial intelligence |
| keyword#4 | Servers |
| keyword#5 | Performance evaluation |
| keyword#6 | artificial intelligence (AI) |
| keyword#7 | artificial intelligence computing |
| keyword#8 | artificial intelligence server system |
| keyword#9 | IEEE 2937 |
| keyword#10 | performance benchmarking |
| keyword#11 | performance benchmarking tool |
| copyright.from | 2022 |
| copyright.owner.name.content | Institute of Electrical and Electronics Engineers |
| copyright.owner.url | http://www.ieee.org |
| copyright.owner.abbreviation.content | IEEE |
| ext.schema-version | v1.0.0 |
| ics.code | 35.240.01 |
| ics.text | Application of information technology in general |
| editorialgroup.committee | Artificial Intelligence Standards Committee of the IEEE Computer Society |
| docstatus.stage.value | approved |
| schema-version | v1.2.1 |
| id | IEEE2937-2022 |