Hi,
I’ve converted our own Llama-3.2-1B model to DLA using the GAI Deployment Toolkit (NeuroPilot 8, targeting mdla5.3 / MT8371). Two topics I’d like to confirm:
1. NPU Simulator — pre-hardware performance estimation
I came across the MediaTek NPU Simulator (ai-neuropilot.mediatek.com / NeuroPilot) and would like to evaluate on-NPU performance before our Genio 520-EVK arrives.
- Can the NPU Simulator run/estimate a compiled
.dlafile on simulated MDLA compute to give performance and latency figures without physical hardware? - Does it support GAI/LLM DLAs specifically (the prompt + generative DLA pair from the GAI Deployment Toolkit), or is it intended only for vision/analytical models?
- If supported, what metrics does it provide (e.g. estimated tokens/sec for prompt + generative, latency), and how close are these estimates to real on-device numbers?
- What access is needed to use the simulation feature for the Genio 520/420 (MT8371) — is it included with our existing NeuroPilot/GAI access, or a separate request? Any setup guide for loading a GAI DLA?
2. Genio 420 (production target) workflow confirmation
Our production target is the Genio 420 (MT8371LV); we’re using the 520-EVK for development. Given they’re pin-compatible:
- Do the same GAI Toolkit workflow, NeuroPilot 8, and Yocto v26.0+ requirements apply identically to the Genio 420?
- Are our DLAs compiled for the 520 (
--arch mdla5.3) directly usable on the 420, or does the 420 need a separate compile/target? - Any 420-specific differences we should be aware of for LLM-on-NPU deployment?
For context: our conversion is a consistent NP8 stack (NeuroPilot 8.0.11, Neuron 8.2.31, ncc-tflite 8.2.31, mtk_llm_sdk 2.5.3), both DLAs compiled with --arch mdla5.3 --num-mdla 1.
Thanks in advance!
Best regards,
Chris