#multithreading
DataFrame
This C++ analytical library offers comprehensive data manipulation and analysis functions similar to Pandas and R data.frame, featuring extensive multithreading to efficiently process large datasets. It supports slicing, joining, merging, and grouping data, as well as executing statistical, financial, and machine learning algorithms. The library supports multiple-column sorting and custom algorithm implementations, making it versatile for different analytical needs. It includes a range of analytical algorithms from basic statistics to complex analyses like Fast Fourier transforms. Verified performance comparisons against Polars and Pandas highlight its consistency and speed.
codon
Codon is a Python compiler that transforms code into native machine language, offering 10-100x speed improvements over standard Python and comparable performance to C/C++. It features native multithreading, multi-core, and GPU support while maintaining a syntax similar to CPython for ease of use. Its optimization framework further enhances performance, and it supports JIT compiling and interoperability with Python modules, enabling efficient execution of Python-compatible code.
taskflow
Taskflow improves parallel programming by providing efficient task decomposition strategies with both regular and irregular compute patterns. It features work-stealing scheduling, conditional and heterogeneous tasking, and modular graph composition for optimal CPU-GPU performance. The built-in profiling tools enable workflow visualization and optimization, suitable for scientific computing and industrial applications. Many leaders in academia and industry utilize this system for advanced task graph computing.
rknn-cpp-Multithreading
This open-source project builds upon the rknpu2, using a thread pool to enable asynchronous RKNN model operations on RK3588/RK3588s, thus improving NPU utilization and inference speeds. The project incorporates relu activation function optimization for yolov5s models. Recent changes have resolved cmake pthread issues, added a nosigmoid branch for better performance with rknn_model_zoo models, and updated the NPU SDK to version 1.5.0. The project supports multi-threaded performance testing with OpenCV, and provides guidance for application deployment using the rkYolov5s.hpp.
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