2 repository-uri
Awesome GitHub RepositoriesDevice Data Model Execution
Runtime execution of read, write, and command operations based on a device's data model definition.
Distinct from Dynamic Data Model Execution: Focuses on the operational execution of a smart device data model rather than analytics models.
Explore 2 awesome GitHub repositories matching data & databases · Device Data Model Execution. Refine with filters or upvote what's useful.
Awesome Device Data Model Execution GitHub Repositories
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- project-chip/connectedhomeip
project-chip/connectedhomeip
8,586Vezi pe GitHubThis project is an open-source software development kit and framework for implementing the Matter smart home standard. It provides a universal IPv6-based application layer and a cluster-based data model to ensure interoperability between diverse smart home devices and controllers. The system is distinguished by its multi-transport network abstraction, which maps Bluetooth LE, Thread, and Wi-Fi implementations to a common layer. It includes specialized tooling for secure device commissioning via QR codes and NFC, as well as a comprehensive over-the-air firmware update system for distributing s
Executes read, write, and command operations on device clusters and handles attribute reporting.
C++build-with-matterchipconnected-devices - pytorch/executorch
pytorch/executorch
4,296Vezi pe GitHubExecuTorch is a lightweight C++ runtime for deploying PyTorch models on mobile, embedded, and edge hardware. It provides an ahead-of-time compilation pipeline that exports, quantizes, and lowers model graphs into compact serialized programs, then executes them through a minimal runtime with hardware acceleration and on-device large language model inference capabilities. The project distinguishes itself through a hardware accelerator delegate system that partitions model subgraphs and offloads computation to specialized backends including NPUs, GPUs, and DSPs from Apple, Arm, Intel, MediaTek,
Provides an abstraction to load model files from files, memory, or other data sources.
Pythondeep-learningembeddedgpu
