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qq20739111

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    qq20739111 reacted to Omer Ozgur Cetinoglu in [Orange Pi Zero 3] Finally stable for 24/7 SDR server — Armbian 13 Trixie + legacy kernel 6.6.75 — complete guide   
    After nearly one year of kernel crashes, I finally found the 
    stable configuration for Orange Pi Zero 3 as a 24/7 SDR server.
     
    The critical discovery: legacy kernel 6.6.75-sunxi64 is the only
    stable option. The current kernel crashes within hours under SDR load.
     
    Additional fixes:
    - Blacklist aw859a WiFi driver (causes kernel instability)
    - Blacklist DVB modules for RTL-SDR
    - Lock libairspyhfSupport.so with chattr +i (SpyServer/SoapySDR conflict)
    - Mask systemd-networkd-wait-online
    - CPU governor: schedutil
    - usbcore.autosuspend=-1 for USB SDR dongles
     
    Running 3 SDRs simultaneously: RTL-SDR Blog V4, Airspy HF+, 
    dedicated ADS-B. 4 antennas via HMC241 GPIO RF switch.
    30+ decoders. Full Android control.
     
    Complete guide: https://ozcet.github.io/sdr-server-guide
  2. Like
    qq20739111 reacted to Nick A in Radxa Cubie A7A/A7Z - Allwinner a733   
    Support for DP Alt Mode is now functional for the A7S running kernel 6.6.


    https://github.com/NickAlilovic/build/releases/tag/Radxa-cubie-A7S-v0.6.4
  3. Like
    qq20739111 reacted to Maberikku in Radxa Cubie A7A/A7Z - Allwinner a733   
    I made some patches so that the unified driver / TIM-VX for the NPU works on the A7Z. I am also building a MLIR pipeline that emit TIM-VX code, so hopefully we can get more flexibility running ML models on the SBC soon.
    https://github.com/MaverickLong/Radxa-A733-NPU-Unified-Driver-Support-Package
  4. Like
    qq20739111 reacted to tiobily in Radxa Cubie A7A/A7Z - Allwinner a733   
    @qq20739111 thks, official community = github? https://github.com/radxa-docs/docs/

    i asked claude to make a summary of my project with npu:
     
    We use the vendor's ACUITY toolkit inside a Docker container (ubuntu-npu:v2.0.10.1) to convert ONNX → quantized .nb files. - Pipeline: onnxsim → pegasus_import → pegasus_quantize → pegasus_export, uint8 quantization, deployed to ~/npu_models/ via push.sh. - Runtime: custom npu_server.c (pre-allocated input buffer, no per-call mmap) that the Python app talks to. - Hard lesson #1 — quantization: only pure Conv+BN+ReLU survives uint8. Attention, SE blocks, hard-swish, LayerNorm all collapse to constant outputs. So no MobileNetV3+, no transformers. - Hard lesson #2 — concurrency hang: NPU IRQs get lost when camera ISP DMA runs in parallel (shared memory bus). Fix: suppress GStreamer buffer copies during inference. Never STREAMOFF/ON the sunxi-vin driver — instant kernel crash. - Result: 12 models running (9 NPU + 3 CPU) at ~40ms/inference.  


     
  5. Like
    qq20739111 reacted to Nick A in Radxa Cubie A7A/A7Z - Allwinner a733   
    @qq20739111  I'll add it soon. 6.18 might take awhile.
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