Serverless seismic imaging in the cloud

TL;DR

This paper introduces a serverless cloud-based seismic imaging method utilizing containerized batch processing and a domain-specific language compiler, significantly reducing costs and demonstrating viability as an alternative to traditional HPC clusters.

Contribution

It presents a novel serverless framework for seismic imaging that combines high-throughput processing, event-driven computation, and specialized compilation, enabling cost-effective cloud solutions.

Findings

Cost reduction of up to 6 times compared to traditional methods

Successful 3D seismic imaging case study on Azure

Cloud approach is a viable alternative to on-premise HPC clusters

Abstract

This abstract presents a serverless approach to seismic imaging in the cloud based on high-throughput containerized batch processing, event-driven computations and a domain-specific language compiler for solving the underlying wave equations. A 3D case study on Azure demonstrates that this approach allows reducing the operating cost of up to a factor of 6, making the cloud a viable alternative to on-premise HPC clusters for seismic imaging.