论文标题
Vegasflow：跨平台加速蒙特卡洛模拟
VegasFlow: accelerating Monte Carlo simulation across platforms
论文作者
论文摘要
在这项工作中，我们演示了Vegasflow库在多审查情况下的用法：一个单个节点中的多GPU和集群中的多节点。 Vegasflow是一种新软件，用于基于蒙特卡洛集成快速评估高度可行的积分。它的灵感来自Vegas算法，通常用作横截面集成的驱动程序，并基于Google功能强大的TensorFlow库。在此程序中，我们考虑了一种典型的多GPU配置，以基准测试不同的批次大小如何增加（或降低）领先顺序示例集成的性能。
In this work we demonstrate the usage of the VegasFlow library on multidevice situations: multi-GPU in one single node and multi-node in a cluster. VegasFlow is a new software for fast evaluation of highly parallelizable integrals based on Monte Carlo integration. It is inspired by the Vegas algorithm, very often used as the driver of cross section integrations and based on Google's powerful TensorFlow library. In this proceedings we consider a typical multi-GPU configuration to benchmark how different batch sizes can increase (or decrease) the performance on a Leading Order example integration.
