onnxruntime

f26054de - [XNNPACK] Support running in multi-thread with seperate pthreadpool (#11762)

[XNNPACK] Support running in multi-thread with seperate pthreadpool (#11762) **Description**: Describe your changes. XNNPACK takes pthreadpool as its internal threadpool implemtation, it couples calculation and parallelization. Thus it's impossible to leverage ORT's threadpool (EIGEN/OPENMP based). So we enabled pthreadpool in XNNPACK EP in this PR. Case 1: Pthreadpool coexist with ORT-threadpool simply Expriments setup hardware:RedMi8A with 8 cores, ARMv7 The two threadpool has the same pool size form 1 to 8. Two models: mobilenet_v2 and mobilenet_egetppu. we can see the picture below and draw a conclusion, latency are even higher from 5 threads or more.  Case 2: For the reason of performance regression with 5 more threads, ORT-threads are spinning on CPU and diddn't realease it after computation finished. It's equivalent of creating 5x2 threads for parallelization while we have only 8 cpu cores. So I mannuly disabled spinning after ort-threadpool finished and enabled it when enter ort-threadpool. The result is quite normal now.  Case 3: Even we achieved a reasonable results with disabling spinning, Will ORT-threadpool still impact performance of pthreadpool? we have expriment setting up as: Setting ORT-threadpool size (intra_thread_num) as 1, and only pthreadpool created. Attention that, almost a third of ops are running by CPU EP. we are surprisingly find that disabling ort-threadpool is even better in performance than creating two threadpool.  Case 4: Use a unified threadpool between CPU ep and XNNPACK ep. It's the fastest among all. But if we take the similar workload partition strategy as ORT-threadpool, it could be faster.  **Motivation and Context** - Why is this change required? What problem does it solve? - If it fixes an open issue, please link to the issue here. Co-authored-by: Jicheng Wen <jicwen@microsoft.com>