# Distributed-Memory Load Balancing with Cyclic Token-based Work-Stealing Applied to Reverse Time Migration

## TL;DR

This paper introduces a cyclic token-based work-stealing algorithm for distributed memory systems to improve load balancing in reverse time migration, significantly reducing imbalance and increasing computational speed.

## Contribution

It presents a novel cyclic token approach for work-stealing that reduces communication overhead and simplifies load balancing in large-scale RTM computations.

## Key findings

- Achieved 14.1% speedup in RTM workload balancing.
- Reduced load imbalance by 78.4% compared to static distribution.
- Implemented as a C library using MPI one-sided communication.

## Abstract

Reverse time migration (RTM) is a prominent technique in seismic imaging. Its resulting subsurface images are used in the industry to investigate with higher confidence the existence and the conditions of oil and gas reservoirs. Because of its high computational cost, RTM must make use of parallel computers. Balancing the workload distribution of an RTM is a growing challenge in distributed computing systems. The competition for shared resources and the differently-sized tasks of the RTM are some of the possible sources of load imbalance. Although many load balancing techniques exist, scaling up for large problems and large systems remains a challenge because synchronization overhead also scales. This paper proposes a cyclic token-based work-stealing (CTWS) algorithm for distributed memory systems applied to RTM. The novel cyclic token approach reduces the number of failed steals, avoids communication overhead, and simplifies the victim selection and the termination strategy. The proposed method is implemented as a C library using the one-sided communication feature of the message passing interface (MPI) standard. Results obtained by applying the proposed technique to balance the workload of a 3D RTM system present a factor of 14.1% speedup and reductions of the load imbalance of 78.4% when compared to the conventional static distribution.