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The Dynamic Neural Accelerator II (DNA-II) is an advanced IP core that elevates neural processing capabilities for edge AI applications. It is adaptable to various systems, exhibiting remarkable efficiency through its runtime reconfigurable interconnects, which aid in managing both transformer and convolutional neural networks. Designed for scalability, DNA-II supports numerous applications ranging from 1k MACs to extensive SoC implementations. DNA-II's architecture enables optimal parallelism by dynamically managing data paths between compute units, ensuring minimized on-chip memory bandwidth and maximizing operational efficiency. Paired with the MERA software stack, it provides seamless integration and optimization of neural network tasks, significantly enhancing computation ordering and resource distribution. Its applicability extends across various industry demands, massively increasing the operational efficiency of AI tasks at the edge. DNA-II, the pivotal force in the SAKURA-II Accelerator, brings innovative processing strength in compact formats, driving forward the development of edge-based generative AI and other demanding applications.
The SAKURA-II AI Accelerator stands out as a high-performance, energy-efficient edge co-processor designed to handle advanced AI tasks. Tailored for real-time, batch-one AI inferencing, it supports multi-billion parameter models, such as Llama 2 and Stable Diffusion, while maintaining low power consumption. The core technology leverages a dynamic neural accelerator for runtime reconfigurability and exceptional parallel processing, making it ideal for edge-based generative AI applications. With its flexible architecture, SAKURA-II facilitates the seamless execution of diverse AI models concurrently, without compromising on efficiency or speed. Integrated with the MERA compiler framework, it ensures easy deployment across various hardware systems, supporting frameworks like PyTorch and TensorFlow Lite for seamless integration. This AI accelerator excels in AI models for vision, language, and audio, fostering innovative content creation across these domains. Moreover, SAKURA-II supports a robust DRAM bandwidth, far surpassing competitors, ensuring superior performance for large language and vision models. It offers support for significant neural network demands, making it a powerful asset for developers in the edge AI landscape.
The MERA Compiler and Framework by EdgeCortix is a groundbreaking software platform crafted to facilitate AI inference across heterogeneous computing systems. It enables seamless integration and deployment of AI models using the Dynamic Neural Accelerator and supports complex generative AI applications for vision, audio, and language tasks. Offering a comprehensive suite of tools and APIs, MERA aids in graph compilation, model calibration, and quantization, ensuring the rapid deployment of pre-trained neural networks. The framework supports multiple machine learning frameworks, such as PyTorch, TensorFlow Lite, and ONNX, empowering developers to efficiently adapt AI solutions without delving into intricate hardware specifics. MERA stands out with its inherent support for diverse processors, such as AMD, Intel, and Arm, providing flexibility and compatibility across various hardware environments. This platform enhances development speed and reduces time-to-market, delivering high-performance AI inference solutions that are energy-efficient and versatile for edge AI applications.
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