The MERA Compiler and Framework developed by EdgeCortix offers a comprehensive software infrastructure for deploying AI models efficiently at the edge. Designed to work alongside the Dynamic Neural Accelerator (DNA), MERA facilitates the compilation and inference of deep neural networks. It enhances developers' workflows through robust tools, APIs, code generators, and runtime environments, enabling easy deployment of pre-trained neural networks after calibration and quantization.
MERA is notable for its support of heterogeneous systems, integrating smoothly with various processors including AMD, Intel, Arm, and RISC-V. By supporting popular AI frameworks like PyTorch, TensorFlow Lite, and ONNX, as well as interfaces in Python and C++, MERA provides a flexible development environment. This versatility allows for the seamless addition of AI technology into existing IT infrastructures, vastly improving deployment times and reducing the time to market for AI solutions.
Pre-defined, optimized models from platforms such as Hugging Face and EdgeCortix's own model library ensure that solutions can be tailored for specific needs. MERA's advanced capabilities in graph partitioning, calibration, and quantization make it ideally suited for tackling complex AI challenges in fields like vision, language, and audio processing, all while maintaining energy efficiency and low latency.
