Abstract. Graph pebbling is a network optimization model for transporting discrete resources that are consumed in transit: the movement of 2 pebbles across an edge consumes one of the pebbles. The pebbling number of a graph is the fewest number of pebbles t so that, from any initial configuration of t pebbles on its vertices, one can place a pebble on any given target vertex via such pebbling steps. It is known that deciding whether a given configuration on a particular graph can reach a specified target is NP-complete, even for diameter 2 graphs, and that deciding whether the pebbling number has a prescribed upper bound is Π P 2 -complete. On the other hand, for many families of graphs there are formulas or polynomial algorithms for computing pebbling numbers; for example, complete graphs, products of paths (including cubes), trees, cycles, diameter 2 graphs, and more. Moreover, graphs having minimum pebbling number are called Class 0, and many authors have studied which graphs are Class 0 and what graph properties guarantee it, with no characterization in sight. In this paper we investigate an important family of diameter 3 chordal graphs called split graphs; graphs whose vertex set can be partitioned into a clique and an independent set. We provide a formula for the pebbling number of a split graph, along with an algorithm for calculating it that runs in O(n β ) time, where β = 2ω/(ω + 1) ∼ = 1.41 and ω ∼ = 2.376 is the exponent of matrix multiplication. Furthermore we determine that all split graphs with minimum degree at least 3 are Class 0.Key words. pebbling number, split graphs, class 0, graph algorithms, complexity AMS subject classifications. 05C85, 68Q17, 90C35 DOI. 10.1137/130914607 1. Introduction. Graph pebbling is a network optimization model for transporting discrete resources that are consumed in transit: while 2 pebbles cross an edge of a graph, only one arrives at the other end as the other is consumed (or spent on toll, one can imagine). This operation is called a pebbling step. The basic questions in the subject revolve around deciding whether a particular configuration of pebbles on the vertices of a graph can reach a given root vertex via pebbling steps (for this reason, graph pebbling is carried out on connected graphs only). If a configuration can reach r, it is called r-solvable, and r-unsolvable otherwise.Various rules for pebbling steps have been studied for years and have found applications in a wide array of areas. One version, dubbed black and white pebbling, was applied to computational complexity theory in studying time-space tradeoffs (see [15,28]), as well as to optimal register allocation for compilers (see [30]). Connections have also been made to pursuit and evasion games and graph searching (see [21,27]). Another version (black pebbling) is used to reorder large sparse matrices to minimize in-core storage during an out-of-core Cholesky factorization scheme (see [12,22,24]). A third version yields results in computational geometry in the rigidity of graphs,