HASEonGPU Documentation

HASEonGPU (High performance Amplified Spontaneous Emission on GPU) is an open-source HPC software for calculating amplified spontaneous emission (ASE) flux in laser gain media.

It is intended to support the design and analysis of high-power laser systems, where ASE is an important limiting effect for stored energy, gain distribution, and overall amplifier performance.

For installation and usage see Getting Started.

Contents

Documentation

• Getting Started
  • Repository Setup
  • Dependencies
  • Additional Notes
  • Compilation Notes
  • Choose an Interface
  • Typical Workflow
  • Next Step
• Binary Interface
  • Compilation
  • Usage
  • Example
  • Command-Line Arguments
• MATLAB Interface
  • Compilation
  • Installation
  • Usage
  • Example
  • Input Argument Description
• Python Interface
  • Installation
  • Usage
  • Example
  • Input Conventions
  • Input Argument Description

Scientific Background

HASEonGPU builds on earlier ASE modeling work by D. Albach et. al [2], where ray-tracing techniques and Monte Carlo integration were used to calculate ASE in laser gain media in a single-threaded cpu-centered context. Based on this scientific foundation, HASEonGPU [1] extends the approach with multi-GPU acceleration, adaptive sampling, and distributed multi-node execution.

Nature of the problem

Accurate ASE simulations require a large number of sampling points as well as a high number of rays. In addition, reflections on the upper and lower surfaces of the gain medium can substantially increase the computational workload. On traditional CPU-based systems, this makes detailed ASE simulations time-consuming and limits the number of practical simulation runs.

Solution method

HASEonGPU addresses this by combining a non-uniform spatial sampling of the gain medium with Monte Carlo integration, importance sampling, adaptive sampling, and GPU parallelization[1]. The code also supports execution on GPU clusters, where the workload is distributed across multiple GPUs using MPI in a master-worker scheme.

Restrictions

The number of rays used for the Monte Carlo integration of a single sampling point is limited by the available GPU memory.

Features

HASEonGPU can run both on a single workstation in threaded mode and on larger GPU clusters in MPI mode. The simulation supports features such as polychromatic laser pulses, cladding, surface coatings, refractive indices, and reflections on the upper and lower surfaces of the gain medium. If a target mean squared error is not reached with the current number of rays, the algorithm can automatically increase the sampling effort.

References

[1] C.H.J. Eckert, E. Zenker, M. Bussmann, and D. Albach,

HASEonGPU—An adaptive, load-balanced MPI/GPU-code for calculating the amplified spontaneous emission in high power laser media, Computer Physics Communications, 207, 2016, 362–374. DOI: 10.1016/j.cpc.2016.05.019

[2] D. Albach, J.-C. Chanteloup, G. l. Touzé,

Influence of ASE on the gain distribution in large size, high gain Yb3+:YAG slabs, Optics Express, 17(5), 2009, 3792–3801.