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NXP i.MX 95

The EdgeFirst Profiler runs on the NXP i.MX 95 (aarch64) and uses the Neutron NPU for hardware-accelerated inference. The Neutron NPU is exposed to the profiler through the TFLite C library and the NXP libneutron_delegate.so.

For a guided platform tour see the i.MX 95 Quick Start. This page covers only the profiler-specific setup.

Prerequisites

  • NXP Linux BSP image with the EdgeFirst SDK overlay
  • libtensorflowlite_c.so (preinstalled in the EdgeFirst image)
  • libneutron_delegate.so (preinstalled in the EdgeFirst image)
  • neutron-converter toolchain (cross-host, used to compile models before deployment)

The Neutron NPU only executes models that have been passed through the Neutron Converter — the converter rewrites a standard TFLite model into a graph the Neutron NPU can run. See the Neutron Converter guide.

Install the profiler

pip install edgefirst-profiler

curl -fsSL https://raw.githubusercontent.com/EdgeFirstAI/profiler-cli/main/install.sh | bash

Confirm:

edgefirst-profiler --version

Delegate selection

When launching the profiler with a TFLite model on i.MX 95, a delegate selection dialog appears in the TUI. The dialog works like the ONNX execution-provider modal — the user picks Neutron, VX, or CPU/XNNPACK explicitly rather than relying on auto-detection. Models that require the Neutron delegate (detected from the model file) skip the general dialog and go straight to a Neutron-specific picker. For headless use, the --delegate CLI flag bypasses the dialog entirely.

Value Behavior
(omitted) / auto Probe well-known NPU paths (/usr/lib/libneutron_delegate.so, /usr/lib/libvx_delegate.so); fall back to XNNPACK.
xnnpack Explicit XNNPACK CPU delegate.
none / cpu No delegate — reference kernels.
path to .so Load a custom delegate from disk.

Auto-detection reads /sys/firmware/devicetree/base/compatible to identify i.MX 95 and pre-populate the delegate path in the TUI's profile configuration screen.

Neutron inference modes

The Neutron delegate supports two inference modes. The profiler detects which mode is available automatically — profiling works correctly in both.

DMA-BUF zero-copy mode (default when the kernel zero-copy patch is present, or NEUTRON_ENABLE_ZERO_COPY=1)

The delegate binds a single DMA-BUF tensor shared between the CPU and the NPU. One inference slot runs at a time; preprocessing serializes with inference. This is the original Neutron inference mode.

CPU-staging mode (activated automatically when the kernel zero-copy patch is absent, or NEUTRON_ENABLE_ZERO_COPY=0)

No DMA-BUF binding is used. Up to 4 independent inference slots run in parallel, giving significantly higher throughput. The profiler sets the inference depth to 4 automatically in this mode. Measured throughput on i.MX 95 Pro running YOLOv5n at 640×640: ~73 FPS at depth 1, ~97 FPS at depth 4.

Fallback from zero-copy

Previously, running a Neutron model on a board without the kernel zero-copy patch caused a crash on the first frame. The profiler now detects the missing patch and falls back to CPU-staging automatically.

Per-tick Neutron profiling

When both conditions below are met, the profiler reports per-tick timing — every NPU kernel (Conv2DDenseTT, AddTT, …) appears as its own slice in the Studio trace view:

  1. The model was compiled with enable_profiling: true in the Neutron Converter.
  2. The target runs Neutron drivers ≥ 3.0.1 (tested on 3.0.1), shipped as part of the eIQ Neutron SDK.

Older 2.x drivers

The profiler remains fully functional with Neutron drivers 2.x — inference timing, pipeline-stage breakdown, and accuracy metrics all work normally. Only the per-operation NPU timing (op-level profiling of the Neutron graph) is unavailable without 3.0.1+ drivers.

To get human-readable kernel names rather than opaque IDs, pass the Neutron converter statistics file produced when the model was compiled:

neutron-converter --dump-statistics-file yolov8n_neutron.statistics ...

Provide that file to the validation session via --neutron-statistics yolov8n_neutron.statistics. Without the statistics file the timing is still captured — only the labels become opaque IDs.

Verifying the install

edgefirst-profiler login
edgefirst-profiler              # opens TUI on F1 Help; F4 auto-populates the delegate path

Then run a validation session — see Validation from Studio or Validation from the Profiler.