Abstract

The abstraction of a shared memory is of growing importance in distributed computing systems. Traditional memory consistency ensures that all processes agree on a common order of all operations on memory. Unfortunately, providing these guarantees entails access latencies that prevent scaling to large systems. This paper weakens such guarantees by defining causal memory, an abstraction that ensures that processes in a system agree on the relative ordering of operations that are causally related. Because causal memory is weakly consistent, it admits more executions, and hence more concurrency, than either atomic or sequentially consistent memories. This paper provides a formal definition of causal memory and gives an implementation for message-passing systems. In addition, it describes a practical class of programs that, if developed for a strongly consistent memory, run correctly with causal memory. College of Computing Georgia Institute of Technology Atlanta, Georgia 30332-0280 This ...

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