  We introduce the computational problem of graphlet transform of a sparse
large graph. Graphlets are fundamental topology elements of all
graphs/networks. They can be used as coding elements to encode
graph-topological information at multiple granularity levels for classifying
vertices on the same graph/network as well as for making differentiation or
connection across different networks. Network/graph analysis using graphlets
has growing applications. We recognize the universality and increased encoding
capacity in using multiple graphlets, we address the arising computational
complexity issues, and we present a fast method for exact graphlet transform.
The fast graphlet transform establishes a few remarkable records at once in
high computational efficiency, low memory consumption, and ready translation to
high-performance program and implementation. It is intended to enable and
advance network/graph analysis with graphlets, and to introduce the relatively
new analysis apparatus to graph theory, high-performance graph computation, and
broader applications.
