NOTE

This project is no longer maintained and has been moved to https://github.com/airockchip/rknn-toolkit2/tree/master/rknpu2

RKNPU2

RKNPU2 provides an advanced interface to access Rockchip NPU.

Support Platform

• RK3566/RK3568
• RK3588/RK3588S
• RV1103/RV1106
• RK3562

Note: The rknn model must be generated using RKNN Toolkit 2: https://github.com/rockchip-linux/rknn-toolkit2

​ For RK1808/RV1109/RV1126/RK3399Pro, please use:

​ https://github.com/rockchip-linux/rknn-toolkit

​ https://github.com/rockchip-linux/rknpu

​ https://github.com/airockchip/RK3399Pro_npu

ReleaseLog

1.5.2

• Improved dynamic shape support
• Improved matmul api support
• Add GPU back-end implementations for some operators such as matmul
• Improve transformer support
• Reduce rknn_init memory usage
• Optimize rknn_init time-consuming

1.5.0

• Support RK3562
• Support more NPU operator fuse, such as Conv-Silu/Conv-Swish/Conv-Hardswish/Conv-sigmoid/Conv-HardSwish/Conv-Gelu ..
• Improve support for NHWC output layout
• RK3568/RK3588：The maximum input resolution up to 8192
• Improve support for Swish/DataConvert/Softmax/Lstm/LayerNorm/Gather/Transpose/Mul/Maxpool/Sigmoid/Pad
• Improve support for CPU operators (Cast, Sin, Cos, RMSNorm, ScalerND, GRU)
• Limited support for dynamic resolution
• Provide MATMUL API
• Add RV1103/RV1106 rknn_server application as proxy between PC and board
• Add more examples such as rknn_dynamic_shape_input_demo and video demo for yolov5
• Bug fix

1.4.0

• Support more NPU operators, such as Reshape、Transpose、MatMul、 Max、Min、exGelu、exSoftmax13、Resize etc.
• Add Weight Share function, reduce memory usage.
• Add Weight Compression function, reduce memory and bandwidth usage.(RK3588/RV1103/RV1106)
• RK3588 supports storing weights or feature maps on SRAM, reducing system bandwidth consumption.
• RK3588 adds the function of running a single model on multiple cores at the same time.
• Add new output layout NHWC (C has alignment restrictions) .
• Improve support for non-4D input.
• Add more examples such as rknn_yolov5_android_apk_demo and rknn_internal_mem_reuse_demo.
• Bug fix.

1.3.0

• Support RV1103/RV1106（Beta SDK）
• rknn_tensor_attr support w_stride(rename from stride) and h_stride
• Rename rknn_destroy_mem()
• Support more NPU operators, such as Where, Resize, Pad, Reshape, Transpose etc.
• RK3588 support multi-batch multi-core mode
• When RKNN_LOG_LEVEL=4, it supports to display the MACs utilization and bandwidth occupation of each layer.
• Bug fix

1.2.0

• Support RK3588
• Support more operators, such as GRU、Swish、LayerNorm etc.
• Reduce memory usage
• Improve zero-copy interface implementation
• Bug fix

1.1.0

• Support INT8+FP16 mixed quantization to improve model accuracy
• Support specifying input and output dtype, which can be solidified into the model
• Support multiple inputs of the model with different channel mean/std
• Improve the stability of multi-thread + multi-process runtime
• Support flashing cache for fd pointed to internal tensor memory which are allocated by users
• Improve dumping internal layer results of the model
• Add rknn_server application as proxy between PC and board
• Support more operators, such as HardSigmoid、HardSwish、Gather、ReduceMax、Elu
• Add LSTM support (structure cifg and peephole are not supported, function: layernormal, clip is not supported)
• Bug fix

1.0

• Optimize the performance of rknn_inputs_set()
• Add more functions for zero-copy
• Add new OP support, see OP support list document for details.
• Add multi-process support
• Support per-channel quantitative model
• Bug fix

0.7

• Optimize the performance of rknn_inputs_set(), especially for models whose input width is 8-byte aligned.
• Add new OP support, see OP support list document for details.
• Bug fix

0.6

• Initial version