Summary: Causal Memory Meets the Consistency and Performance Needs of
Distributed Applications! \Lambda
Mustaque Ahamad y
College of Computing
Georgia Institute of Technology
Atlanta, GA U.S.A
In order to provide acceptable performance in large scale distributed systems, shared data must
be cached at or close to nodes where it is accessed. Maintaining the consistency of such cached
data is an important problem in distributed systems. We claim that causal memory, which de
fines consistency of shared data based on causal orderings between data accesses, provides strong
enough consistency guarantees to be usable yet it allows efficient and scalable implementations.
In this paper, we describe some results of our recent work that support this claim.
Distributed systems differ from other types of systems in the support they provide for sharing state
across nodes. Operating systems must provide abstractions that reduce the complexity of state
sharing, yet it should be possible to implement these abstractions efficiently. A shared memory