Using Answer Set Programming for HPC Dependency Solving

TL;DR

This paper presents a novel approach using Answer Set Programming to efficiently solve complex dependency problems in high-performance computing software stacks, improving compatibility and configuration quality.

Contribution

It introduces ASP as a declarative method to model and solve HPC dependency issues, handling complex compatibility rules and large configuration spaces.

Findings

ASP can express HPC dependency rules concisely

ASP provides strong solution quality guarantees

Solver performs well with tens of thousands of packages

Abstract

Modern scientific software stacks have become extremely complex, using many programming models and libraries to exploit a growing variety of GPUs and accelerators. Package managers can mitigate this complexity using dependency solvers, but they are reaching their limits. Finding compatible dependency versions is NP-complete, and modeling the semantics of package compatibility modulo build-time options, GPU runtimes, flags, and other parameters is extremely difficult. Within this enormous configuration space, defining a "good" configuration is daunting. We tackle this problem using Answer Set Programming (ASP), a declarative model for combinatorial search problems. We show, using the Spack package manager, that ASP programs can concisely express the compatibility rules of HPC software stacks and provide strong quality-of-solution guarantees. Using ASP, we can mix new builds with preinstalled binaries, and solver performance is acceptable even when considering tens of thousands of packages.