Supported Frameworks & Applications
Enabling software-defined heterogeneous AI inference acceleration
EdgeCortix MERA is the software companion to the EdgeCortix Dynamic Neural Accelerator IP (DNA IP), whether the hardware core sits in an FPGA, a custom SoC, or the EdgeCortix SAKURA-I Energy-efficient Edge AI Co-processor. MERA provides the entire stack for developing edge AI inference applications from modeling to deployment.
Integrated in familiar AI inference workflows
MERA is a compiler and software tool kit enabling deep neural network graph compilation and AI inference using the Dynamic Neural Accelerator IP (DNA IP). It provides the necessary tools, APIs, code-generator and runtime needed to deploy a pre-trained deep neural network after a simple calibration and quantization step.
MERA offers software developers and data scientists familiar workflows for developing neural network models without dealing with details of chip-level hardware architecture.
- Native support for PyTorch, TensorFlow, TensorFlow Lite, and ONNX
- Python and C++ interfaces for workflow integration and customization
- Post-training calibration and INT8 quantization of user-defined models
- Supports stand-alone estimation of inference latency and throughput
- Over 50 pre-defined AI inference applications ready for use
Everything needed for AI inference development and deployment
- Runtime configuration of DNA IP
- Simulation and profiling for stand-alone use
- Low-level IR (intermediate representation)
- Host processor code generation
- High-level graph partitioning
- APIs for popular machine learning frameworks
- Model calibration and quantization
- Pre-trained applications in the Model Zoo
Given the tectonic shift in information processing at the edge, companies are now seeking near cloud level performance where data curation and AI driven decision making can happen together. Due to this shift, the market opportunity for the EdgeCortix solutions set is massive, driven by the practical business need across multiple sectors which require both low power and cost-efficient intelligent solutions. Given the exponential global growth in both data and devices, I am eager to support EdgeCortix in their endeavor to transform the edge AI market with an industry-leading IP portfolio that can deliver performance with orders of magnitude better energy efficiency and a lower total cost of ownership than existing solutions."