Study finds Python 3.14's no-GIL build speeds up parallel workloads 4x but increases energy use 13-43% for sequential tasks; memory usage rises due to per-object locking.

Unlocking Python's Cores: Hardware Usage and Energy Implications of Removing the GIL

View PDF HTML (experimental) 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 consumpti...