IEEE 2941.2-2023
IEEE Standard for Application Programming Interfaces (APIs) for Deep Learning (DL) Inference Engines
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- Language: English
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About This Item
IEEE 2941.2-2023 is a technical standard for application programming interfaces used by deep learning inference engines in computing and processing environments. It focuses on how software can interact with inference systems in a more consistent way, which can help support portability, integration, and implementation clarity. For teams building or evaluating AI-capable software platforms, IEEE 2941.2-2023 offers a structured reference for API-oriented design and interoperability at the inference stage.
Overview of IEEE 2941.2-2023
IEEE 2941.2-2023 addresses the interface layer between applications and deep learning inference engines. In practical terms, it is concerned with how requests, outputs, and related functions are organized so that systems can be implemented and used with greater consistency. Within the broader computing and processing field, this type of standard may help define common expectations for API behavior, making it easier to compare solutions, align development work, and support more predictable technical integration.
Typical use cases
This standard is typically relevant when software teams are building inference-driven applications that depend on defined API behavior. It may be used for runtime integration in AI software stacks, embedded processing platforms, edge inference systems, or server-based deployment workflows where deep learning models must be accessed reliably. IEEE 2941.2-2023 can also be useful when reviewing platform compatibility, designing reusable software components, or documenting interface requirements for procurement and implementation planning.
Why it matters
IEEE 2941.2-2023 matters because API consistency can reduce integration risk and improve the repeatability of deep learning inference deployments. Clear interface expectations may support better design control, testing, and system validation, especially where different tools or hardware targets must work together. For organizations managing computing and processing projects, the standard can help improve technical alignment across development, evaluation, and operational use, while also supporting more disciplined compliance and procurement decisions.
- API structure for inference engines
- Deep learning software integration
- Computing and processing context
- Implementation and testing reference
- Interoperability and consistency focus
- Publication Date: 2023
- Standard Status: Active
- Publisher: IEEE
- Subject: Computing and Processing
- Official IEEE: Doi link
- This Version: 2941.2 (2023)
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