# ZMCintegral: a Package for Multi-Dimensional Monte Carlo Integration on Multi-GPUs

## TL;DR

ZMCintegral is a Python package enabling efficient multi-dimensional Monte Carlo integration on multiple GPUs, supporting user-defined functions and demonstrating comparable speed to VEGAS for complex integrands.

## Contribution

The paper introduces ZMCintegral, a novel Python package that simplifies multi-GPU Monte Carlo integration with user-friendly interfaces and scalable algorithms.

## Key findings

- Speed comparable to VEGAS for 6D and 9D integrals
- Supports user-defined functions with TensorFlow and Numba
- Scalable on distributed GPU clusters

## Abstract

We have developed a Python package ZMCintegral for multi-dimensional Monte Carlo integration on multiple Graphics Processing Units(GPUs). The package employs a stratified sampling and heuristic tree search algorithm. We have built three versions of this package: one with Tensorflow and other two with Numba, and both support general user defined functions with a user-friendly interface. We have demonstrated that Tensorflow and Numba help inexperienced scientific researchers to parallelize their programs on multiple GPUs with little work. The precision and speed of our package is compared with that of VEGAS for two typical integrands, a 6-dimensional oscillating function and a 9-dimensional Gaussian function. The results show that the speed of ZMCintegral is comparable to that of the VEGAS with a given precision. For heavy calculations, the algorithm can be scaled on distributed clusters of GPUs.