Neutron is NXP's Neural Processing Unit (NPU) and it's integrated on the i.MX95 SoC. It is capable of running inferences on a large range of ML models and targets edge AI applications.
Signed-off-by: Ioana Ciocoi-Radulescu ruxandra.radulescu@nxp.com --- Documentation/accel/index.rst | 1 + Documentation/accel/neutron/index.rst | 12 +++ Documentation/accel/neutron/neutron.rst | 131 ++++++++++++++++++++++++++++++++ 3 files changed, 144 insertions(+)
diff --git a/Documentation/accel/index.rst b/Documentation/accel/index.rst index cbc7d4c3876a..dbe177074739 100644 --- a/Documentation/accel/index.rst +++ b/Documentation/accel/index.rst @@ -9,5 +9,6 @@ Compute Accelerators
introduction amdxdna/index + neutron/index qaic/index rocket/index diff --git a/Documentation/accel/neutron/index.rst b/Documentation/accel/neutron/index.rst new file mode 100644 index 000000000000..8f15346d16c7 --- /dev/null +++ b/Documentation/accel/neutron/index.rst @@ -0,0 +1,12 @@ +.. SPDX-License-Identifier: GPL-2.0-only + +========================== + accel/neutron NPU driver +========================== + +The accel/neutron driver supports the Neutron NPU (Neural Processing Unit) +from NXP. + +.. toctree:: + + neutron diff --git a/Documentation/accel/neutron/neutron.rst b/Documentation/accel/neutron/neutron.rst new file mode 100644 index 000000000000..c5066d53ce69 --- /dev/null +++ b/Documentation/accel/neutron/neutron.rst @@ -0,0 +1,131 @@ +.. SPDX-License-Identifier: GPL-2.0-only + +.. include:: <isonum.txt> + +==================== + Neutron NPU Driver +==================== + +:Copyright: |copy| 2026 NXP + +Overview +======== + +Neutron is NXP's eIQ Neutron Neural Processing Unit (NPU). It is a highly +scalable, power-efficient machine learning accelerator targeting quantized +ML models for edge AI applications. Neutron is integrated into i.MX95 and +other NXP platforms. + +A more detailed description of Neutron NPU and usage scenarios can be +found at [1]_. + +Hardware Description +==================== + +Neutron has the following hardware components: + +- RISC-V core: this is the "brain" of the Neutron NPU. It runs a proprietary + firmware responsible for programming registers, processing commands and + managing the other hardware components +- one or more Neutron cores: the main computation engine performing Machine + Learning (ML) operations +- TCM: a dedicated fast memory +- Data Mover: a DMA engine that handles data transfers between system memory + and Neutron's internal memory + +Software Stack +============== + +The following software components are required for running an inference +on the Neutron accelerator: + +- Neutron converter [2]_, [3]_: this is an offline tool that converts models + from standard TFLite (LiteRT) format to a custom format for execution on the + Neutron NPU; +- An inference engine, e.g. LiteRT's XNNPack, which in turn uses +- A LiteRT custom delegate [4]_ to dispatch custom operators to Neutron NPU; +- A userspace library [5]_ that the delegate links to, which wraps IOCTLs + to the kernel driver in a higher-level API. It handles microcode, weights + and kernels preparation and base address computations needed by the NPU for + job execution. It also triggers cache syncs when required; +- The Neutron kernel driver, which handles device initialization and + communicates directly with the Neutron firmware; +- Neutron firmware [5]_, a proprietary firmware that executes on the RISC-V + core and directly drives the execution of the NPU hardware. + +Usage Flow +========== + +This section describes the steps required to run an inference job on the +Neutron NPU. + +Offline Conversion +------------------ + +The first step is to convert a standard TFLite model using the Neutron +converter. Supported standard operators are extracted together and mapped +to one or multiple **NeutronGraph** custom operators in the converted model. +Standard operators that are not supported by the NPU are left unchanged and +will be executed on the CPU. + +Runtime Flow +------------ + +On the platform's Cortex-A cores running Linux, the LiteRT inference engine +is responsible for loading the ML model, pre-processing the input data and +handing over the tensor computation to the NPU via the custom delegate. + +The inference engine can be exercised via one of the standard TFLite tools +(e.g. benchmark_model, label_image, etc) or via any custom application that +uses the LiteRT runtime API. + +When preparing to run an inference job, userspace requests a memory buffer +from the kernel driver. It loads both the model and the input data in the +buffer, while also reserving a section for the inference output. It then +issues a job submission command with the prepared buffer and waits for +completion. + +The kernel driver sends the inference job details to the Neutron firmware +via mailbox registers. The NPU executes the inference and issues an interrupt +to the Linux core once it is finished. The driver in return marks the job +as complete so userspace can access and post-process the output. + +Boot Sequence +============= + +The Neutron driver is responsible for loading the firmware image and +initiating the NPU boot sequence. The device is powered down during suspend +and each resume operation implies running the firmware load and boot sequence +again. + +Hardware Constraints +==================== + +Cache Coherency +--------------- + +Some of the NXP platforms that Neutron is integrated on, including i.MX95, +do not ensure Neutron memory coherency at hardware level, generating the +need for explicit DMA sync operations. Given that only parts of the memory +buffer may require syncing at any given time (e.g. multiple inferences using +the same model but different input data) and that the kernel driver is unaware +of the buffer partitioning, the sync operations are driven from userspace. + +Buffer alignment +---------------- + +The Neutron DMA engine requires the inference buffers to be aligned to 1MB +boundary. We allocate buffers for Neutron NPU from a reserved CMA pool that +satisfies this alignment requirement. + +References +========== + +.. [1] i.MX Machine Learning User's Guide: https://www.nxp.com/docs/en/user-guide/UG10166.pdf +.. [2] Neutron Converter binary and User Guide available for download here: + https://www.nxp.com/design/design-center/software/eiq-ai-development-environ... +.. [3] NXP's eIQ PyPi repository: https://eiq.nxp.com/repository/eiq-neutron-sdk/ +.. [4] TFLite delegate source code: https://github.com/nxp-imx/tflite-neutron-delegate +.. [5] Neutron firmware, library and TFLite delegate available here as binaries: + https://github.com/nxp-upstream/neutron/tree/upstream +