Abstract: In one exemplary embodiment, a DSM is used to store the data structures in a cluster shared memory, such that updates, deletions and insertions are applied to both the persistent data set and the DSM, and search, list and retrieval operations are processed directly from the DSM. A data structure in the persistent data set is stored in two separate DSM pages: a first page includes an identifying search key of the data structure, the search key also pointing to a location of the data structure in the storage. A second page includes the updatable properties of the data structure. A DSM storing the data structures' pages is organized as a two-row matrix.

Abstract: A dynamic layer above a sequential deduplication file system (denoted as DFS) implements the rewrite functionality. A user file is composed of one or more DFS files. As incoming data is written into a user file, the data is written by the dynamic layer sequentially into DFS files, created one by one. For each user file this dynamic layer creates and maintains a dynamic metadata file, in a regular, non deduplicated file system. This metadata file contains entries pointing to sections of DFS files.

Abstract: Various embodiments for rewriting data in a deduplication storage environment by a processor device are provided. A dynamic layer above a sequential deduplication file system (denoted as DFS) implements the rewrite functionality. A user file is composed of one or more DFS files. As incoming data is written into a user file, the data is written by the dynamic layer sequentially into DFS files, created one by one. For each user file this dynamic layer creates and maintains a dynamic metadata file, in a regular, non deduplicated file system. This metadata file contains entries pointing to sections of DFS files.

Abstract: Various embodiments for capacity management in a deduplication computing storage environment by a processor device are provided. A deduplication storage capacity is estimated as a function of an expected deduplication ratio, the expected deduplication ratio being a combined average of a current deduplication ratio and a configured deduplication ratio, the current deduplication ratio depending on the data currently stored in the deduplication storage, and the configured deduplication ratio being an estimate made at a configuration stage of the deduplication computing storage environment.

Abstract: Various embodiments for reducing communication between cluster nodes and optimizing failover processing in a distributed shared memory (DSM)-based application by at least one processor device are provided. In one embodiment, for a data structure operable on a DSM, a read-mostly portion is maintained in a single copy sharable between the cluster nodes while an updatable portion is maintained in multiple copies, each of the multiple copies dedicated to a single cluster node.

Abstract: Various embodiments for facilitating search, list and retrieval operations on a persistent data set using a distributed shared memory (DSM) by a processor device are provided. In one exemplary embodiment, a DSM is used to store the data structures in a cluster shared memory, such that updates, deletions and insertions are applied to both the persistent data set and the DSM, and search, list and retrieval operations are processed directly from the DSM. A data structure in the persistent data set is stored in two separate DSM pages: a first page includes an identifying search key of the data structure, the search key also pointing to a location of the data structure in the storage. A second page includes the updatable properties of the data structure. A DSM storing the data structures' pages is organized as a two-row matrix.

Abstract: Various embodiments for deduplicated data processing congestion control in a computing environment are provided. In one such embodiment, a single congestion metric is determined from a sampling of a plurality of combined deduplicated data processing congestion statistics in a number of active deduplicated data processes. The congestion limit is calculated from a comparison of the single congestion metric to a congestion target setpoint, the congestion target setpoint being a virtual dimension setpoint and the congestion limit being a manipulated variable. The number of active deduplicated data processes is compared to the congestion limit. If the number of active deduplicated data processes is less than the congestion limit, a new deduplicated data process is spawned.

Abstract: The invention relates to methods for detecting an altered susceptibility to breast and ovarian cancer in a subject carrying a BRCA mutation, comprising determining the nucleic acid sequence of a polymorphism of a microRNA-related gene.