An interactive Ascend-NPU process viewer
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Updated
May 6, 2026 - Python
An interactive Ascend-NPU process viewer
A general-purpose real-time streaming media and deep learning inference acceleration framework, supporting H264, H265, AAC, MP4, FLV, RTSP, RTMP, and YOLO.实时流媒体及深度学习推理加速通用处理框架,支持H264、H265、AAC、MP4、FLV、RTSP、RTMP、YOLO。
TileXR (eXtreme Rendezvous for Asynchronous Tile Communication) is a data-centric asynchronous communication runtime for Huawei Ascend NPUs.
Ascend NPU fork of nanochat for LLM training with torch_npu/HCCL (experimental)
Run nanochat training efficiently on Huawei Ascend NPUs with minimal code changes, supporting tokenizer, pretraining, and evaluation workflows.
Cholesky decomposition reference implementation on Ascend NPU
Out-of-tree HCCL Task DAG and P2P traffic capture studio
Predicting California house prices with MindSpore
Automated GLM interaction detection via CANN, NID scores, and SHAP interaction values for insurance pricing.
Native AscendC Mamba2 selective scan / SSD forward-backward custom operator for Huawei Ascend 910B3 and 950PR, with CANN, torch_npu, A100 benchmarks and msprof profiling.
A repository to store neural network test code.
Linear classification of CIFAR-10 dataset with MindSpore
Read-only mirror of https://gitcode.com/donaldsebleung/my-ascend-notebook-images
Minimal runnable Ascend C (CANN) operator examples on cannsim card-free (no-NPU) CAModel simulation
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