I/O complexity and pebble games with partial computations

Optimizing data movements during program executions is essential for achieving high performance in modern computing systems. This has been classically modeled with the Red-Blue Pebble Game and its variants. In existing models, it is typically assumed that the number of red pebbles, i.e., the size of the fast memory, is larger than the maximum in-degree in the computational directed acyclic graph (DAG). Graphs that do not satisfy this constraint need to be first transformed appropriately, which is not a trivial task for general graphs. In this work we propose a Pebble Game variant to model DAGs with arbitrary in-degrees, by allowing partial computations. In the new model, we show that it is NP-complete to decide whether there exists an optimal pebbling strategy with cost k, even for single-level DAGs and when only two words fit in the fast memory. Approximation algorithms for special cases are also outlined.