Enabling enterprises to rapidly and efficiently customize end- cloud integrated AI solutions (Multi- chip platform , multi- application scenarios , multi- operating systems ,high-performance , maximizing impact)

Business layout and planning

  • End-Cloud Integrated Solution
  • Supports Top30+ models for different application scenarios

  • Supports mainstream global chip platforms and adapts to multiple operating systems

  • Supporting Automotive,Mobile, and IoT devices

  • Provides performance optimization for large language models and multimodal language models

AIOS Ecosystem Development Plan

ArraymoAIOS collaborates with chip, model, and application partners to create integrated AIOS hardware and software solutions.

AI Acceleration Engine AMLightning

Optimization of Computing Resources

The AI acceleration engine AMLightning fully leverages the tensor computing capabilities of hardware to solve the following issues

On the Qualcomm platform, the most optimal energy efficiency for algorithms on mainstream chip platforms is achieved through techniques such as quantization-aware training, custom operators, and operator fusion.

AI algorithm acceleration

Rapid migration of mature AI algorithms to hardware platforms.

Custom operator

Development of efficient operators for customer-specific algorithms.

Operator fusion

Accelerating algorithm inference speed by analyzing customer algorithm models and fusing operators.

Algorithm tuning

Optimizing the backend scheduling performance of AI algorithms on hardware platforms to minimize precision loss.

AI Acceleration Engine AMLightning

Optimization of Hardware Computing Units

As the number of AI chip manufacturers and models increases, and with most being heterogeneous computing units, developers need to perform complex adaptation optimizations to achieve quality application services.

  • Addressing the issue where chip computing units cannot quickly achieve optimal performance.
  • Reducing the development cycle of AI projects.

Helping developers quickly schedule the capabilities of various computing units of AI chips, enabling various inference tasks to run on the most suitable computing units, thereby improving operational efficiency.

  • Parallel computing of multiple tasks

  • Different tasks running on the optimal computing units

  • One-click scheduling to enhance computing power

Large models deployed on the Qualcomm chipset platform