Abstract: A network device, system, and method are provided. The network device includes a processor. The processor is configured to store a local estimate and a dual variable maintaining an accumulated subgradient for the network device. The processor is further configured to collect values of the dual variable of neighboring network devices. The processor is also configured to form a convex combination with equal weight from the collected dual variable of neighboring network devices. The processor is additionally configured to add a most recent local subgradient for the network device, scaled by a scaling factor, to the convex combination to obtain an updated dual variable. The processor is further configured to update the local estimate by projecting the updated dual variable to a primal space.

Abstract: A machine learning method includes connecting machines in a data-center using a network aware model consistency for stochastic applications; ensuring a communication graph of all machines in the data-center is connected; propagating all updates uniformly across the cluster without update; and preferring connections to a machine with first network throughput over machines with second network throughput smaller than the first network throughput.

Abstract: Methods and systems for adaptive compression include compressing input data according to a first compression ratio; pausing compression after a predetermined amount of input data is compressed; estimating which of a set of ranges a compressed output size will fall within using current settings; and performing compression on a remainder of the input data according to a second compression ratio based on the estimated range.

Abstract: Systems and methods for generating and storing a data structure for maintaining cache supporting compression and cache-wide deduplication, including generating data structures with fixed size memory regions configured to hold multiple signatures as keys, wherein the number of the fixed size memory regions is bounded. A first mapping is generated from short-length signatures to a storage location and a quantized length measure on a cache storage device; and unused contiguous regions on the cache device are allocated. Metadata and cache page content is retrieved using a single input/output operation; a correctness of a full value of hash functions of uncompressed cache page content is validated; a second mapping is generated from short-length signatures to entries in the first mapping; and verification of whether the cached page content corresponds to a full-length original logical block address using the metadata is performed.

Abstract: Systems and methods are disclosed for parallel machine learning with a cluster of N parallel machine network nodes by determining k network nodes as a subset of the N network nodes to update learning parameters, wherein k is selected to disseminate the updates across all nodes directly or indirectly and to optimize predetermined goals including freshness, balanced communication and computation ratio in the cluster; sending learning unit updates to fewer nodes to reduce communication costs with learning convergence; and sending reduced learning updates and ensuring that the nodes send/receive learning updates in a uniform fashion.

Abstract: Systems and methods are disclosed for providing distributed learning over a plurality of parallel machine network nodes by allocating a per-sender receive queue at every machine network node and performing distributed in-memory training; and training each unit replica and maintaining multiple copies of the unit replica being trained, wherein all unit replicas train, receive unit updates and merge in parallel in a peer-to-peer fashion, wherein each receiving machine network node merges updates at later point in time without interruption and wherein the propagating and synchronizing unit replica updates are lockless and asynchronous.

Abstract: Methods and systems for adaptive compression include compressing input data according to a first compression ratio; pausing compression after a predetermined amount of input data is compressed; estimating which of a set of ranges a compressed output size will fall within using current settings; and performing compression on a remainder of the input data according to a second compression ratio based on the estimated range.

Abstract: Systems and methods for generating and storing a data structure for maintaining cache supporting compression and cache-wide deduplication, including generating data structures with fixed size memory regions configured to hold multiple signatures as keys, wherein the number of the fixed size memory regions is bounded. A first mapping is generated from short-length signatures to a storage location and a quantized length measure on a cache storage device; and unused contiguous regions on the cache device are allocated. Metadata and cache page content is retrieved using a single input/output operation; a correctness of a full value of hash functions of uncompressed cache page content is validated; a second mapping is generated from short-length signatures to entries in the first mapping; and verification of whether the cached page content corresponds to a full-length original logical block address using the metadata is performed.

Abstract: A system for providing block layout in a distributed storage system. A request receiver receives requests to perform a read or write operation for a data block. A memory device stores ordered replica lists and a swap policy. Each list is for a respective stored data block and has one or more entries specifying prioritized replica location information associated with storage devices and priorities there for. A load balancer scores and selects an original location for the data block specified in a request responsive to the information and a policy favoring fully operational storage devices having higher priority locations. The swap policy evaluates the original location responsive to the information and estimated workload at storage device locations to decide upon at least one alternate location responsive to the write operation, and to decide to place the data block at the at least one alternate location responsive to the read operation.

Abstract: A method is provided for sequential discrete event simulation for a distributed system having a set of nodes. A priority queue is constructed that includes events to be executed by a processor at a given node in the set. A first subset of nodes is identified. Each node in the first subset is associated with a respective subset of events and includes a highest priority event whose priority must be unconditionally re-evaluated during a next time step. A second subset of nodes is identified. Each node in the second subset is associated with a respective other subset of events and includes a highest priority event whose priority must be re-evaluated when a re-evaluation condition depending upon an external state is satisfied. A next one of the plurality of events in the priority queue is selected to be executed by the processor using the first and second subsets of nodes.

Abstract: System(s) and method(s) are provided for data management and data processing. For example, various embodiments may include systems and methods relating to relatively larger groups of data being selected with comparable or better performing selection results (e.g., high data redundancy elimination and/or average chunk size). In various embodiments, the system(s) and method(s) may include, for example a data group, block, or chunk combining technique or/and a data group, block, or chunk splitting technique. Various embodiments may include a first standard or typical data grouping, blocking, or chunking technique and/or data group, block, or chunk combining technique or/and a data group, block, or chunk splitting technique. Exemplary system(s) and method(s) may relate to data hashing and/or data elimination. Embodiments may include a look-ahead buffer and determine whether to emit small chunks or large chunks based on characteristics of underlying data and/or particular application of the invention (e.g.

Abstract: Systems and methods for data management and data processing are provided. Embodiments may include systems and methods relating to fast data selection with reasonably high quality results, and may include a faster data selection function and a slower data selection function. Various embodiments may include systems and methods relating to data hashing and/or data redundancy identification and elimination for a data set or a string of data. Embodiments may include a first selection function is used to pre-select boundary points or data blocks/windows from a data set or data stream and a second selection function is used to refine the boundary points or data blocks/windows. The second selection function may be better at determining the best places for boundary points or data blocks/windows in the data set or data stream. In various embodiments, data may be processed by a first faster hash function and slower more discriminating second hash function.

Abstract: A region of a node is searched to find a content-defined split point. A split point of a node is determined based at least in part on hashes of entries in the node and the node is split based on the determined split point. The search region is searched for the first encountered split point and the node is split based on that split point. That split point is based on a predetermined bitmask of the hashes of the entries in the node satisfying a predetermined condition.

Abstract: Systems and methods for data management and data processing are provided. Embodiments may include systems and methods relating to fast data selection with reasonably high quality results, and may include a faster data selection function and a slower data selection function. Various embodiments may include systems and methods relating to data hashing and/or data redundancy identification and elimination for a data set or a string of data. Embodiments may include a first selection function is used to pre-select boundary points or data blocks/windows from a data set or data stream and a second selection function is used to refine the boundary points or data blocks/windows. The second selection function may be better at determining the best places for boundary points or data blocks/windows in the data set or data stream. In various embodiments, data may be processed by a first faster hash function and slower more discriminating second hash function.

Abstract: System(s) and method(s) are provided for data management and data processing. For example, various embodiments may include systems and methods relating to relatively larger groups of data being selected with comparable or better performing selection results (e.g., high data redundancy elimination and/or average chunk size). In various embodiments, the system(s) and method(s) may include, for example a data group, block, or chunk combining technique or/and a data group, block, or chunk splitting technique. Various embodiments may include a first standard or typical data grouping, blocking, or chunking technique and/or data group, block, or chunk combining technique or/and a data group, block, or chunk splitting technique. Exemplary system(s) and method(s) may relate to data hashing and/or data elimination. Embodiments may include a look-ahead buffer and determine whether to emit small chunks or large chunks based on characteristics of underlying data and/or particular application of the invention (e.g.

Abstract: Composite materials particularly suitable in the dental art as a tooth filling material including a polymer matrix, a metal, metal alloy, metal oxide particulate, or combinations thereof, in the presence or absence of colloidal silica, and a coupling agent to adhere the particulate to the polymer matrix. Adhesion can also be facilitated by cleaning and/or coating the particulates prior to incorporation into the polymer matrix. One or two paste systems of the composition with suitable initiators, accelerators, etc. can be formulated.