{"work":{"id":"69ae0df4-8381-4f4e-b7e4-79c11ea7c479","openalex_id":null,"doi":null,"arxiv_id":"1801.06601","raw_key":null,"title":"CMSIS-NN: Efficient Neural Network Kernels for Arm Cortex-M CPUs","authors":null,"authors_text":"L","year":2018,"venue":"cs.NE","abstract":"Deep Neural Networks are becoming increasingly popular in always-on IoT edge devices performing data analytics right at the source, reducing latency as well as energy consumption for data communication. This paper presents CMSIS-NN, efficient kernels developed to maximize the performance and minimize the memory footprint of neural network (NN) applications on Arm Cortex-M processors targeted for intelligent IoT edge devices. Neural network inference based on CMSIS-NN kernels achieves 4.6X improvement in runtime/throughput and 4.9X improvement in energy efficiency.","external_url":"https://arxiv.org/abs/1801.06601","cited_by_count":null,"metadata_source":"pith","metadata_fetched_at":"2026-05-21T13:25:11.499430+00:00","pith_arxiv_id":"1801.06601","created_at":"2026-05-09T06:00:36.616511+00:00","updated_at":"2026-05-21T13:25:11.499430+00:00","title_quality_ok":true,"display_title":"CMSIS-NN: Efficient neural network kernels for ARM Cortex-M CPUs","render_title":"CMSIS-NN: Efficient neural network kernels for ARM Cortex-M CPUs"},"hub":{"state":{"work_id":"69ae0df4-8381-4f4e-b7e4-79c11ea7c479","tier":"hub","tier_reason":"10+ Pith inbound or 1,000+ external citations","pith_inbound_count":11,"external_cited_by_count":null,"distinct_field_count":7,"first_pith_cited_at":"2018-06-02T04:45:58+00:00","last_pith_cited_at":"2026-05-20T07:44:39+00:00","author_build_status":"not_needed","summary_status":"needed","contexts_status":"needed","graph_status":"needed","ask_index_status":"not_needed","reader_status":"not_needed","recognition_status":"not_needed","updated_at":"2026-05-31T06:52:11.577466+00:00","tier_text":"hub"},"tier":"hub","role_counts":[{"context_role":"background","n":2},{"context_role":"baseline","n":1}],"polarity_counts":[{"context_polarity":"background","n":2},{"context_polarity":"baseline","n":1}],"runs":{},"summary":{},"graph":{},"authors":[]}}