Abstract: A queued, byte addressed system and method for accessing flash memory and other non-volatile storage class memory, and potentially other types of non-volatile memory (NVM) storage systems. In a host device, e.g., a standalone or networked computer, having attached NVM device storage integrated into a switching fabric wherein the NVM device appears as an industry standard OFED™ RDMA verbs provider. The verbs provider enables communicating with a ‘local storage peer’ using the existing OpenFabrics RDMA host functionality. User applications issue RDMA Read/Write directives to the ‘local peer (seen as a persistent storage) in NVM enabling NVM memory access at byte granularity. The queued, byte addressed system and method provides for Zero copy NVM access. The methods enables operations that establish application private Queue Pairs to provide asynchronous NVM memory access operations at byte level granularity.

Abstract: A method includes comparing a number of memory blocks in a first pool of free memory blocks in a memory to a threshold. The memory includes memory blocks that are logically divided into the first pool, a second pool, and a third pool of memory blocks. The first pool of free memory blocks is expanded based on determining that the number of memory blocks in the first pool of free memory blocks is less than the threshold. The expanding includes: selecting a first memory block from the second pool of memory blocks, the first memory block comprising active and non-active content; selecting a second memory block from the third pool of memory blocks; copying the active content of the first memory block to the second memory block; erasing the first memory block; and adding the first memory block to the first pool of free memory blocks.

Abstract: A method and system are provided for implementing enhanced flash storage control using reinforcement learning to provide enhanced performance metrics. A flash controller, such as a Reinforcement Learning (RL) flash controller, is coupled to a flash storage. The flash controller defines a feature set of flash parameters determined by a predefined one of a plurality of optimization metrics. The optimization metric is adapted dynamically based upon system workload and system state. The flash controller employing the feature set including at least one feature responsive to erase operations; computes a current system state responsive to the employed feature set; selects actions at each time step by sensing the computed current system state for performing an action to maximize a long term reward, and moves to another state in the system while obtaining a short-term reward for the performed action.

Abstract: According to an aspect, searching, recommending, and exploring documents through conceptual associations includes a method for receiving a plurality of documents and extracting concepts from each of the documents. A degree of relation between each of the documents and concepts in a knowledge base is calculated. The method also includes, in response to receiving a query, determining one or more concepts from the query. For each of the concepts, a list of documents having a highest degree of relation to the concept is retrieved. The method also includes outputting a list that is responsive to the one or more retrieved lists.

Abstract: According to an aspect, searching, recommending, and exploring documents through conceptual associations includes receiving a plurality of documents and extracting concepts from each of the documents. A degree of relation between each of the documents and concepts in a knowledge base is calculated. An aspect also includes, in response to receiving a query, determining one or more concepts from the query. For each of the concepts, a list of documents having a highest degree of relation to the concept is retrieved. An aspect also includes outputting a list that is responsive to the one or more retrieved lists.

Abstract: According to an aspect, storing and querying conceptual indices (CIs) includes creating a conceptual inverted index (CII) from the CIs. The CII includes CII entries, each of which corresponds to a concept in a concept graph. Creating the CII includes populating each entry with pointers to documents selected from the CIs having likelihoods of being related to the concept that are greater than a threshold value, and the corresponding likelihoods. An aspect also includes receiving a query that includes a concept in the concept graph, and generating query results from a search that include at least a subset of the pointers to documents. Each of the CIs is associated with a corresponding document and includes a CI entry for each concept in the concept graph, and each of the CI entries specifies a value indicating a likelihood that the document is related to the concept in the concept graph.

Abstract: According to an aspect, automatically adding new concepts to a concept graph includes receiving a string of text, searching a corpus of data to locate additional text related to the string of text, and extracting concepts from the additional text. The extracted concepts include a subset of concepts in the concept graph. The adding new concepts also includes determining whether the string of text should be linked to an existing concept in the concept graph, performing the linking based on determining that the string of text should be linked to the existing concept in the concept graph and, based on determining that the string of text should not be linked to an existing concept in the concept graph, adding a new concept to the concept graph. The new concept is associated with the string of text.

Abstract: According to an aspect, automatically linking text to concepts in a knowledge base using differential analysis includes receiving a text string and selecting, based on contents of the text string, a plurality of data sources that correspond to concepts in the knowledge base. In a further aspect, automatically linking the text to the concepts includes calculating, for each of the selected data sources, a probability that the text string is output by a language model built using the selected data source, calculating a probability that the text string is output by a generic language model, calculating link confidence scores for each concept based on a differential analysis of the probabilities, and creating a link from the text string to one of the concepts in the knowledge base. The creating is based on a link confidence score of the concept being more than a threshold value away from a prescribed threshold.

Abstract: According to an aspect, automatically adding new concepts to a concept graph includes receiving a string of text, searching a corpus of data to locate additional text related to the string of text, and extracting concepts from the additional text. The extracted concepts include a subset of concepts in the concept graph. The adding new concepts also includes determining whether the string of text should be linked to an existing concept in the concept graph, performing the linking based on determining that the string of text should be linked to the existing concept in the concept graph and, based on determining that the string of text should not be linked to an existing concept in the concept graph, adding a new concept to the concept graph. The new concept is associated with the string of text.

Abstract: According to an aspect, summarizing relevance of a document to a conceptual query includes receiving the conceptual query, accessing concepts extracted from the document, and computing a degree to which the conceptual query is related to each of the extracted concepts. The computing is responsive to a metric that measures a relevance between the concepts in the conceptual query and the extracted concepts. An aspect also includes creating a summary by selecting a threshold number of the concepts having a greatest degree of relation to the conceptual query, and outputting the summary including the selected threshold number of concepts.

Abstract: According to an aspect, storing and querying conceptual indices (CIs) includes creating a conceptual inverted index (CII) from the CIs. The CII includes CII entries, each of which corresponds to a concept in a concept graph. Creating the CII includes populating each entry with pointers to documents selected from the CIs having likelihoods of being related to the concept that are greater than a threshold value, and the corresponding likelihoods. An aspect also includes receiving a query that includes a concept in the concept graph, and generating query results from a search that include at least a subset of the pointers to documents. Each of the CIs is associated with a corresponding document and includes a CI entry for each concept in the concept graph, and each of the CI entries specifies a value indicating a likelihood that the document is related to the concept in the concept graph.

Abstract: According to an aspect, automatically linking text to concepts in a knowledge base using differential analysis includes receiving a text string and selecting, based on contents of the text string, a plurality of data sources that correspond to concepts in the knowledge base. In a further aspect, automatically linking the text to the concepts includes calculating, for each of the selected data sources, a probability that the text string is output by a language model built using the selected data source, calculating a probability that the text string is output by a generic language model, calculating link confidence scores for each concept based on a differential analysis of the probabilities, and creating a link from the text string to one of the concepts in the knowledge base. The creating is based on a link confidence score of the concept being more than a threshold value away from a prescribed threshold.

Abstract: According to an aspect, summarizing relevance of a document to a conceptual query includes receiving the conceptual query, accessing concepts extracted from the document, and computing a degree to which the conceptual query is related to each of the extracted concepts. The computing is responsive to a metric that measures a relevance between the concepts in the conceptual query and the extracted concepts. The method also includes creating a summary by selecting a threshold number of the concepts having a greatest degree of relation to the conceptual query, and outputting the summary including the selected threshold number of concepts.

Abstract: According to an aspect, conceptual analysis of a document includes accessing a concept graph that includes a plurality of nodes and edges. Each node represents a concept and each edge represents a known relation between two concepts. Conceptual analysis of the document further includes computing a relevance of the document to concepts in the concept graph. The computing includes receiving a priori information about the document including concepts extracted from the document. The concepts extracted from the document include a subset of the concepts in the concept graph. The computing also includes combining the a priori information and the concept graph to generate a posteriori information that indicates a likelihood that the document is related to each of the concepts in the concept graph.

Abstract: According to an aspect, conceptual analysis of a document includes accessing a concept graph that includes a plurality of nodes and edges. Each node represents a concept and each edge represents a known relation between two concepts. Conceptual analysis of the document further includes computing a relevance of the document to concepts in the concept graph. The computing includes receiving a priori information about the document including concepts extracted from the document. The concepts extracted from the document include a subset of the concepts in the concept graph. The computing also includes combining the a priori information and the concept graph to generate a posteriori information that indicates a likelihood that the document is related to each of the concepts in the concept graph.

Abstract: A hybrid encryption scheme for storing data lines in a memory includes identifying data lines determined to be frequently accessed, and encrypting the data lines using a first encryption scheme. The hybrid encryption scheme also includes encrypting data lines determined not to be frequently accessed using a second encryption scheme.

Abstract: Defining an active region of a phase change memory (PCM) cell including depositing a first layer of material having a first chemical composition. A second layer of material having a second chemical composition is deposited on top of the first layer of material. An electrical current pulse is applied to locally heat a region of the first layer of material and the second layer of material to cause at least one of an inter-diffusion and a liquid mixing of the first layer of material and the second layer of material. This results in in the PCM cell containing a self-aligned region that includes a phase change material that is a mixture of the first chemical composition and the second chemical composition.

Abstract: An aspect of this invention is a method for providing a PreSET region in a memory device wherein the PreSET region includes one or more lines of the memory device which have been PreSET; performing a write operation on one or more out of place lines of the memory device by writing to the PreSET region instead of writing to an in place line of the memory device; and storing in an indirection table a mapping of each of a respective plurality of logical pages of the memory device to a corresponding physical page of a plurality of physical pages of the memory device, wherein the indirection table keeps track of the one or more out of place lines.

Abstract: A memory device may be equipped with quick erase capability to secure the contents of the memory device. The quick erase capability may effectively permanently disable access to data stored in the memory device instantaneously upon a command being issued, making all previous data written to the memory device unreadable. The quick erase capability may allow use of the memory device for new write operations and for reading the newly written data immediately once the erase command is received and executed. The quick erase capability may begin a physical erase process of data not newly written without altering other aspects of the quick erase. Aspects may be accomplished with one or more bits per row in a memory device.

Abstract: A memory device may be equipped with quick erase capability to secure the contents of the memory device. The quick erase capability may effectively permanently disable access to data stored in the memory device instantaneously upon a command being issued, making all previous data written to the memory device unreadable. The quick erase capability may allow use of the memory device for new write operations and for reading the newly written data immediately once the erase command is received and executed. The quick erase capability may begin a physical erase process of data not newly written without altering other aspects of the quick erase. Aspects may be accomplished with one or more bits per row in a memory device.