1## RKNPU2 2 RKNPU2 provides an advanced interface to access Rockchip NPU. 3 4## Support Platform 5 - RK3566/RK3568 6 - RK3588/RK3588S 7 - RV1103/RV1106 8 - RK3562 9 10Note: 11 The rknn model must be generated using RKNN Toolkit 2: https://github.com/rockchip-linux/rknn-toolkit2 12 13 **For RK1808/RV1109/RV1126/RK3399Pro, please use:** 14 15 https://github.com/rockchip-linux/rknn-toolkit 16 17 https://github.com/rockchip-linux/rknpu 18 19 https://github.com/airockchip/RK3399Pro_npu 20 21## ReleaseLog 22 23# 1.5.0 24 25- Support RK3562 26- Support more NPU operator fuse, such as Conv-Silu/Conv-Swish/Conv-Hardswish/Conv-sigmoid/Conv-HardSwish/Conv-Gelu .. 27- Improve support for NHWC output layout 28- RK3568/RK3588：The maximum input resolution up to 8192 29- Improve support for Swish/DataConvert/Softmax/Lstm/LayerNorm/Gather/Transpose/Mul/Maxpool/Sigmoid/Pad 30- Improve support for CPU operators (Cast, Sin, Cos, RMSNorm, ScalerND, GRU) 31- Limited support for dynamic resolution 32- Provide MATMUL API 33- Add RV1103/RV1106 rknn_server application as proxy between PC and board 34- Add more examples such as rknn_dynamic_shape_input_demo and video demo for yolov5 35- Bug fix 36 37 38 39### 1.4.0 40 41- Support more NPU operators, such as Reshape、Transpose、MatMul、 Max、Min、exGelu、exSoftmax13、Resize etc. 42- Add **Weight Share** function, reduce memory usage. 43- Add **Weight Compression** function, reduce memory and bandwidth usage.(RK3588/RV1103/RV1106) 44- RK3588 supports storing weights or feature maps on SRAM, reducing system bandwidth consumption. 45- RK3588 adds the function of running a single model on multiple cores at the same time. 46- Add new output layout NHWC (C has alignment restrictions) . 47- Improve support for non-4D input. 48- Add more examples such as rknn_yolov5_android_apk_demo and rknn_internal_mem_reuse_demo. 49- Bug fix. 50 51### 1.3.0 52 53- Support RV1103/RV1106（Beta SDK） 54- rknn_tensor_attr support w_stride(rename from stride) and h_stride 55- Rename rknn_destroy_mem() 56- Support more NPU operators, such as Where, Resize, Pad, Reshape, Transpose etc. 57- RK3588 support multi-batch multi-core mode 58- When RKNN_LOG_LEVEL=4, it supports to display the MACs utilization and bandwidth occupation of each layer. 59- Bug fix 60 61### 1.2.0 62 63- Support RK3588 64- Support more operators, such as GRU、Swish、LayerNorm etc. 65- Reduce memory usage 66- Improve zero-copy interface implementation 67- Bug fix 68 69### 1.1.0 70 71 - Support INT8+FP16 mixed quantization to improve model accuracy 72 - Support specifying input and output dtype, which can be solidified into the model 73 - Support multiple inputs of the model with different channel mean/std 74 - Improve the stability of multi-thread + multi-process runtime 75 - Support flashing cache for fd pointed to internal tensor memory which are allocated by users 76 - Improve dumping internal layer results of the model 77 - Add rknn_server application as proxy between PC and board 78 - Support more operators, such as HardSigmoid、HardSwish、Gather、ReduceMax、Elu 79 - Add LSTM support (structure cifg and peephole are not supported, function: layernormal, clip is not supported) 80 - Bug fix 81 82 83### 1.0 84 - Optimize the performance of rknn_inputs_set() 85 - Add more functions for zero-copy 86 - Add new OP support, see OP support list document for details. 87 - Add multi-process support 88 - Support per-channel quantitative model 89 - Bug fix 90 91 92### 0.7 93 - Optimize the performance of rknn_inputs_set(), especially for models whose input width is 8-byte aligned. 94 - Add new OP support, see OP support list document for details. 95 - Bug fix 96 97### 0.6 98 - Initial version 99 100