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A natural way to measure the power of a distributed-computing model is to characterize the set of tasks that can be solved in it. %the model. In general, however, the question of whether a given task can be solved in a given model is undecidable, even if we only consider the wait-free shared-memory model. In this paper, we address this question for restricted classes of models and tasks. We show that the question of whether a collection $C$ of emph{$(ell,j)$-set consensus} objects, for various $ell$ (the number of processes that can invoke the object) and $j$ (the number of distinct outputs the object returns), can be used by $n$ processes to solve wait-free $k$-set consensus is decidable. Moreover, we provide a simple $O(n^2)$ decision algorithm, based on a dynamic programming solution to the Knapsack optimization problem. We then present an emph{adaptive} wait-free set-consensus algorithm that, for each set of participating processes, achieves the best level of agreement that is possible to achieve using $C$. Overall, this gives us a complete characterization of a read-write model defined by a collection of set-consensus objects through its emph{set-consensus power}.
The set consensus problem has played an important role in the study of distributed systems for over two decades. Indeed, the search for lower bounds and impossibility results for this problem spawned the topological approach to distributed computing,
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