SAT Solving in the Serverless Cloud

Alex Ozdemir, Haoze Wu, Clark W. Barrett

Abstract: In recent years, cloud service providers have sold computation in increasingly granular units. Most recently, “serverless” executors run a single executable with restricted network access and for a limited time. The benefit of these restrictions is scale: thousand-way parallelism can be allocated in seconds, and CPU time is billed with sub-second granularity. To exploit these executors, we introduce gg-SAT: an implementation of divide-and-conquer SAT solving. Infrastructurally, gg-SAT departs substantially from previous implementations: rather than handling process or server management itself, gg-SAT builds on the gg framework, allowing computations to be executed on a configurable backend, including serverless offerings such as AWS Lambda. Our experiments suggest that when run on the same hardware, gg-SAT performs competitively with other D&C solvers, and that the 1000-way parallelism it offers (through AWS Lambda) is useful for some challenging SAT instances.