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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
A machine learning accelerator core designed for energy-efficient AI at the edge.
| Date | Stars |
|---|---|
| 2026-07-31 | 2487 |
| 2026-08-02 | 2490 |
| 2026-08-06 | 2501 |
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# Coral NPU Coral NPU is a hardware accelerator for ML inferencing. Coral NPU is an Open Source IP designed by Google Research and is freely available for integration into ultra-low-power System-on-Chips (SoCs) targeting wearable devices such as hearables, augmented reality (AR) glasses and smart watches. Coral NPU is a neural processing unit (NPU), also known as an AI accelerator or deep-learning processor. Coral NPU is based on the 32-bit RISC-V Instruction Set Architecture (ISA). Coral NPU includes three distinct processor components that work together: matrix, vector (SIMD), and scalar.  [Coral NPU Architecture Datasheet](https://developers.google.com/coral/guides/hardware/datasheet) ## Coral NPU Features Coral NPU offers the following top-level feature set: * RV32IMF_Zve32x RISC-V instruction set (specifically `rv32imf_zve32x_zicsr_zifencei_zbb`) * 32-bit address space for applications and operating system kernels * Four-stage processor, in-order dispatch, out-of-order retire * Four-way scalar, two-way vector dispatch * 128-bit SIMD, 256-bit (future) pipeline * 8 KB ITCM memory (tightly-coupled memory for instructions) * 32 KB DTCM memory (tightly-coupled memory for data) * Both memories are single-cycle-latency SRAM, more efficient than cache memory * AXI4 bus interfaces, functioning as both manager and subordinate, to interact with external memory and allow external CPUs to configure Coral NPU ## System Requirements * Bazel 7.4.1 * Python 3.9-3.12 (3.13 support is in progress) * [SRecord](https://srecord.sourceforge.net/) ## Verification & Testing For details on our testing methodologies and how to run or write tests, see the corresponding test READMEs: * [Cocotb Tests (RTL & Netlist simulation)](tests/cocotb/README.md) * [UVM Testbench (Co-simulation)](tests/uvm/README.md) ## Quick Start ```bash # Ensure that test suite passes bazel run //tests/cocotb:core_mini_axi_sim_cocotb # Build a binary bazel build //examples:coralnpu_v2_hello_world_add_floats # Build the Simulator (non-RVV for shorter build time): bazel build //tests/verilator_sim:core_mini_axi_sim # Run the binary on the simulator: bazel-bin/tests/verilator_sim/core_mini_axi_sim --binary bazel-out/k8-fastbuild-ST-dd8dc713f32d/bin/examples/coralnpu_v2_hello_world_add_floats.elf ``` 
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Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:01d7e943d2063357, llm:description: 'A machine learning accelerator core designed for energy-efficient AI at the edge.'
matched fp:01d7e943d2063357, llm:description: 'A machine learning accelerator core designed for energy-efficient AI at the edge.'
matched fp:01d7e943d2063357, llm:description: 'A machine learning accelerator core designed for energy-efficient AI at the edge.'