异步批量贝叶斯优化与管道评估在实验设备有限的情况下
Yujin Taguchi1, Yusuke Shibuya1, Yusuke Hiki1
1Center for Biosciences and Informatics, Graduate School of Fundamental Science and Technology, Keio University, Kanagawa, Japan.
SLAS technology
|February 1, 2026
概括
管道贝叶斯优化 (PipeBO) 通过重叠实验过程加速科学发现. 这种方法显著减少了优化时间,特别是当并行实验受到设备限制的限制时.
科学领域:
- 计算科学 计算科学
- 工程 工程师 工程师 工程师
- 化学 化学 化学
- 生物学 生物学 生物学
背景情况:
- 贝叶斯优化 (BO) 是数据效率高,在科学和工程领域广泛使用.
- 批量BO通过并行实验来加速优化,但受到设备限制的限制.
- 当并行实验稀缺时,顺序方法变得具有时间限制.
研究的目的:
- 开发一种新的方法,管道贝叶斯优化 (PipeBO),以减少优化处理时间.
- 为了实现高效的优化,即使在有限数量的并行实验.
主要方法:
- PipeBO的灵感来源于CPU管道,将计算任务分为多个过程.
- 它通过重叠各种实验过程来实现实验并行.
- PipeBO使用已完成的结果更新正在运行的实验,将实验建模为异步过程.
主要成果:
- 对于两个过程的实验,PipeBO 将平均优化处理时间减少了约56%.
- 对于具有两个以上过程的实验,观察到进一步的时间缩短.
- 该方法在24个基准函数中的20个中显示出显著的加快速度.
结论:
- 在设备有限的场景中,PipeBO有效地减少了优化时间.
- 它为加速科学和工程优化流程提供了可行的解决方案.
- 即使完全并行是不可行的,PipeBO也可以实现高效的贝叶斯优化.
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