Unigen has announced the Amaretti E1.S, an AI module designed to fit into standard M.2 or E1.S slots, similar in form factor to an SSD. Utilizing the EdgeCortix SAKURA-II accelerator, the module provides high-efficiency AI processing for local agents and GenAI workflows with a low power draw of approximately 10W.
Key features include:
* Up to 60 TOPS of INT8 performance and 30 TFLOPS of BF16 compute.
* Memory configurations of 16 GB or 32 GB with up to 68 GB/s bandwidth.
* Capability to run Large Language Models (LLMs) with up to 20B parameters.
* Support for major AI frameworks including TensorFlow, PyTorch, ONNX, and Hugging Face.
* Scalable design allowing multiple modules to be stacked in available slots.
Key features include:
* Up to 60 TOPS of INT8 performance and 30 TFLOPS of BF16 compute.
* Memory configurations of 16 GB or 32 GB with up to 68 GB/s bandwidth.
* Capability to run Large Language Models (LLMs) with up to 20B parameters.
* Support for major AI frameworks including TensorFlow, PyTorch, ONNX, and Hugging Face.
* Scalable design allowing multiple modules to be stacked in available slots.
An article about Rockchip's RKLLM toolkit, which provides NPU-accelerated large language models for RK3588, RK3588S, and RK3576 processors.
