Monday, June 17, 2024

Edge AI Enhanced With New Performance Processor

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The Edge AI processor transforms laptops and servers for energy-efficient video analytics, LLMs, and AI model processing.


Kinara has launched the Ara-2 Edge AI processor, targeting edge servers and laptops. This processor is designed for performance and energy-efficient inference to run applications such as video analytics, Large Language Models (LLMs), and Generative AI models. The Ara-2 is suitable for edge applications using traditional AI models and AI models with transformer-based architectures. 

The Ara-2 has a feature set that improves user experience and increases performance over the Ara-1 processor. It combines a design optimised for latency with on-chip memories and off-chip bandwidth. This enables the Ara-2 to execute large models with low latency.

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LLMs and Generative AI are popular, with most applications running on GPUs in data centres facing issues like latency, cost, and privacy. Kinara’s Ara-2 aims to move the computation closer to the user, supporting the large number of parameters used by these Generative AI models and enabling a shift to edge computing.

The Ara-2’s compute engines and software development kit (SDK) are designed to support quantization, a host runtime, and direct FP32 support. This facilitates the transition from GPUs for a range of AI models, making it more accessible and efficient for various applications.

The Ara-2 includes a secure boot, encrypted memory access, and a secure host interface for security in enterprise AI deployments. Kinara provides an SDK for the Ara-2, which consists of a model compiler and compute-unit scheduler, quantization options with an integrated Kinara quantizer, and support for pre-quantized PyTorch and TFLite models. It also features a load balancer for systems with multiple chips and a host runtime.

“With Ara-2 added to our family of processors, we can better provide customers with performance and cost options to meet their requirements. For example, Ara-1 is the right solution for smart cameras as well as edge AI appliances with 2-8 video streams, whereas Ara-2 is strongly suited for handling 16-32+ video streams fed into edge servers, as well as laptops and even high-end cameras,” said Ravi Annavajjhala, Kinara’s CEO. 

For more information, click here.

Nidhi Agarwal
Nidhi Agarwal
Nidhi Agarwal is a journalist at EFY. She is an Electronics and Communication Engineer with over five years of academic experience. Her expertise lies in working with development boards and IoT cloud. She enjoys writing as it enables her to share her knowledge and insights related to electronics, with like-minded techies.


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