How can I run ONNX Runtime inference on the 8 A100 AI cores of a SpacemiT K3 COM260 board running Android/AOSP?

Hi everyone,

I’m working on an AI application running on a SpacemiT K3 COM260 RISC-V board with a custom-built Android/AOSP environment.

Currently, my application performs AI inference using the general-purpose CPU cores (X100). I want to move the inference workload to the board’s 8 dedicated A100 AI cores to improve performance.

Current setup

Hardware: SpacemiT K3 COM260 RISC-V board

OS: Custom-built Android/AOSP

Inference framework: ONNX Runtime

Access: ADB shell available

Current execution: General-purpose CPU cores

Target: 8 A100 AI cores

Questions

Is there an Android-compatible SpaceMITExecutionProvider or an official SDK/runtime for the K3 A100 AI cores?

If not, what would be the recommended approach to port the existing SpacemiT ONNX Runtime backend to Android/AOSP?

Are the A100 cores exposed as schedulable CPU cores, or must inference be submitted through a separate driver/runtime API?

Can standard ONNX Runtime be configured to use these cores, or is a vendor-specific execution provider and optimized operator library required?

Are there any sample projects, build instructions, kernel configurations, or documentation for running ONNX Runtime inference on A100 under Android?

I’d appreciate advice from anyone who has worked with SpacemiT K3, RISC-V AI acceleration, Android NDK, or custom ONNX Runtime execution providers.

My goal is to keep the existing Android application and ONNX model where possible, while changing the inference execution backend to use the A100 hardware.

Thanks in advance!

submitted by /u/Practical_Emm4600
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