The Range of Topological Effects on Communication

We continue the study of communication cost of computing functions when inputs are distributed among

k

processors, each of which is located at one vertex of a network/graph called a terminal. Every other node of the network also has a processor, with no input. The communication is point-to-point and the cost is the total number of bits exchanged by the protocol, in the worst case, on all edges.

Chattopadhyay, Radhakrishnan and Rudra (FOCS’14) recently initiated the study of the effect of topology of the network on the total communication cost using tools from

$$L_1$$

embeddings. Their techniques provided tight bounds for simple functions like Element-Distinctness (ED), which depend on the 1-median of the graph. This work addresses two other kinds of natural functions. We show that for a large class of natural functions like Set-Disjointness the communication cost is essentially

n

times the cost of the optimal Steiner tree connecting the terminals. Further, we show for natural composed functions like

$$\text {ED} \circ \text {XOR}$$

and

$$\text {XOR} \circ \text {ED}$$

, the naive protocols suggested by their definition is optimal for general networks. Interestingly, the bounds for these functions depend on more involved topological parameters that are a combination of Steiner tree and 1-median costs.

To obtain our results, we use some new tools in addition to ones used in Chattopadhyay et al. These include (i) viewing the communication constraints via a linear program; (ii) using tools from the theory of tree embeddings to prove topology sensitive direct sum results that handle the case of composed functions and (iii) representing the communication constraints of certain problems as a family of collection of multiway cuts, where each multiway cut simulates the hardness of computing the function on the star topology.