T/AI 118.1-2022 Artificial intelligence computing center Part 1: Technical requirements
T/AI 118.1-2022 Artificial intelligence computing center Part 1: Technical requirements
Basic Information
Scope
Scope: This document specifies the composition, performance, and reliability technical requirements of artificial intelligence computing centers. This document is applicable to the design and construction of artificial intelligence computing centers, and also provides a reference and basis for the capacity testing of artificial intelligence computing centers; Main technical content: The technical specifications for artificial intelligence computing centers aim to solve the following industry problems. This section focuses on the parts related to technical requirements in the first three problems. a) The system architecture and composition of various artificial intelligence computing centers may vary significantly, and there are no baseline specifications for the computing characteristics and basic configurations of specific computing centers, which poses certain obstacles to the deployment, debugging, and porting of applications; b) The performance of artificial intelligence computing centers is one of the core conditions for their applications, and performance optimization should be based on testing. However, there are currently no comprehensive performance testing methods specifically designed for artificial intelligence computing centers; c) The reliability of artificial intelligence computing centers is an important concern for users. Currently, there are no technical requirements specifically targeting the reliability of artificial intelligence computing centers. The requirements and testing methods for reliability in data centers and software systems also need to be adjusted and compromised to a certain extent; d) There are no unified standardized guidelines for the certification procedures of artificial intelligence computing center construction. In the certification process, inconsistencies in personnel, tools, use cases, and processes may lead to deviations in the certification results.