SLA-aware Interactive Workflow Assistant for HPC Parameter Sweeping Experiments

TL;DR

This paper presents a novel SLA-aware interactive tool for optimizing parameter sweeping workflows in HPC, enabling users to adapt strategies based on intermediate results and SLA constraints.

Contribution

The paper introduces a new interactive tool that leverages user feedback on intermediate results to improve parameter selection in HPC workflows under SLA constraints.

Findings

Users benefit from interaction with intermediate results.

The tool adapts strategies based on user feedback and SLA constraints.

Evaluation with three diverse applications shows improved workflow efficiency.

Abstract

A common workflow in science and engineering is to (i) setup and deploy large experiments with tasks comprising an application and multiple parameter values; (ii) generate intermediate results; (iii) analyze them; and (iv) reprioritize the tasks. These steps are repeated until the desired goal is achieved, which can be the evaluation/simulation of complex systems or model calibration. Due to time and cost constraints, sweeping all possible parameter values of the user application is not always feasible. Experimental Design techniques can help users reorganize submission-execution-analysis workflows to bring a solution in a more timely manner. This paper introduces a novel tool that leverages users' feedback on analyzing intermediate results of parameter sweeping experiments to advise them about their strategies on parameter selections tied to their SLA constraints. We evaluated our tool with three applications of distinct domains and search space shapes. Our main finding is that users with submission-execution-analysis workflows can benefit from their interaction with intermediate results and adapt themselves according to their domain expertise and SLA constraints.