Prince Kohli

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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(More)
Shared memories that provide weaker consistency guarantees than the traditional sequentially consistent or atomic memories have been claimed to provide the key to building scalable systems. One influential memory model, processor considency, has been cited widely in the literature but, due to the lack of a precise and formal definition, contradictory claims(More)
The traditional consistency requirements of shared memory are expensive to provide both in large scale multiprocessor systems and in distributed systems that implement a shared memory abstraction. As a result, several memory systems have been proposed that enhance performance and scalabil ity by providing weaker consistency. The differing models used to(More)
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 <i>causal memory</i>, which defines consistency of shared data based on causal orderings between(More)
Distributed systems that consist of workstations connected by high performance interconnects ooer computational power comparable to moderate size parallel machines. Middleware like Distributed Shared Memory (DSM) or Distributed Shared Objects (DSO) attempts to improve the programmability of such hardware by presenting to application programmers interfaces(More)
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