Abstract:Python's Global Interpreter Lock prevents execution on more than one CPU core at the same time, even when multiple threads are used. However, starting with Python 3.13 an experimental build allows disabling the GIL. While prior work has examined speedup implications of this disabling, the effects on energy consumption and hardware utilization have received less attention. This study measures execution time, CPU utilization, memory usage, and energy consumption using four workload categories: NumPy-based, sequential kernels, threaded numerical workloads, and threaded object workloads, comparing GIL and free-threaded builds of Python 3.14.2.
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，推荐阅读新收录的资料获取更多信息
Gadfly.plot(sin, 0, 2π)
await blocking.writer.write(chunk2); // ok
。新收录的资料是该领域的重要参考
SelectWhat's included。新收录的资料对此有专业解读
# `where.c`, in `whereScanInit()`