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Software distributed shared-memory (SDSM) provides the abstraction necessary to run shared-memory applications on cost-effective parallel platforms such as clusters of workstations. However, problems such as cluster component reliability and cluster management, which are not directly related to performance, need to be addressed before SDSM solutions can be widely adopted. This paper presents Raptor, an SDSM cluster management system based on checkpoint/recovery and thread migration. Raptor checkpoints decouple the runtime system and application data from application threads, allowing efficient load balancing, resource allocation, and rollback recovery. There are two important features of the system. First, it reduces checkpoint overhead by only saving application-specific data that cannot be recreated at recovery time. Second, by integrating thread migration capability both at running and recovery, it allows the addition or removal of computing resources from a running application, while adding little or no additional burden on the SDSM application programmer.