Abstract: Techniques for managing big data include tagging of documents and subsequent retrieval using per-subject dictionaries having entries with subject-determining-power scores. The subject-determining-power scores provide an indication of the descriptive power of the term with respect to the subject of the dictionary containing the term. The same term may have entries in multiple dictionaries with different subject-determining-power scores in each of the dictionaries. A retrieval request for one or more documents containing search terms descriptive of the one or more documents can be processed identifying a set of candidate documents tagged with subjects and optional terms, and then applying subject-determining-power scores from the multiple dictionaries for the search term to determine a subject for the search term. The method then selects the one or more documents from the candidate documents according to the subject.

Abstract: Techniques for managing big data include tagging of documents and subsequent retrieval using per-subject dictionaries having entries with some entries specially designated as entities. An entity indicates that the term in the entry has special meaning, e.g., brands (trademarks/service marks), trade names, geographic identifiers or other classes of terms. A dictionary may include a non-entity entry for a term and one or more entity entries, for different entity types. The entries may also include subject-determining-power scores. The subject-determining-power scores provide an indication of the descriptive power of the term with respect to the subject of the dictionary containing the term. The same term may have entries in multiple dictionaries with different subject-determining-power scores in each of the dictionaries. The entity distinctions for a term can then be used in tagging documents and processing retrieval requests.

Abstract: Techniques for managing big data include retrieval using per-subject dictionaries having and hierarchical information indicating affinity between the dictionaries. A retrieval request for one or more documents pertaining to one or more subjects is performed by specifying the subjects, selecting dictionaries associated with the subjects, matching the subjects to documents in the collection according to a strength of relationship between the documents and the subjects and also using the hierarchical information, to obtain a subset of the collection of documents.

Abstract: Techniques for managing big data include retrieval using per-subject dictionaries having multiple levels of sub-classification hierarchy within the subject. Entries may include subject-determining-power (SDP) scores that provide an indication of the descriptive power of the entry term with respect to the subject of the dictionary containing the term. The same term may have entries in multiple dictionaries with different SDP scores in each of the dictionaries. A retrieval request for one or more documents containing search terms descriptive of the one or more documents can be processed by identifying a set of candidate documents tagged with subjects, i.e., identifiers of per-subject dictionaries having entries corresponding to a search term, then using affinity values to adjust the aggregate score for the terms in the dictionaries. Documents are then selected for best match to the subject based on the adjusted scores.

Abstract: Techniques for managing big data include tagging of documents and subsequent retrieval using per-subject dictionaries having entries with subject-determining-power scores. The subject-determining-power scores provide an indication of the descriptive power of the term with respect to the subject of the dictionary containing the term. The same term may have entries in multiple dictionaries with different subject-determining-power scores in each of the dictionaries. A retrieval request for one or more documents containing search terms descriptive of the one or more documents can be processed identifying a set of candidate documents tagged with subjects and optional terms, and then applying subject-determining-power scores from the multiple dictionaries for the search term to determine a subject for the search term. The method then selects the one or more documents from the candidate documents according to the subject.

Abstract: Techniques for managing big data include tagging of documents and subsequent retrieval using per-subject dictionaries having entries with subject-determining-power scores. The subject-determining-power scores provide an indication of the descriptive power of the term with respect to the subject of the dictionary containing the term. The same term may have entries in multiple dictionaries with different subject-determining-power scores in each of the dictionaries. A retrieval request for one or more documents containing search terms descriptive of the one or more documents can be processed identifying a set of candidate documents tagged with subjects and optional terms, and then applying subject-determining-power scores from the multiple dictionaries for the search term to determine a subject for the search term. The method then selects the one or more documents from the candidate documents according to the subject.

Abstract: Techniques for managing big data include tagging of documents and subsequent retrieval using per-subject dictionaries having entries with some entries specially designated as entities. An entity indicates that the term in the entry has special meaning, e.g., brands (trademarks/service marks), trade names, geographic identifiers or other classes of terms. A dictionary may include a non-entity entry for a term and one or more entity entries, for different entity types. The entries may also include subject-determining-power scores. The subject-determining-power scores provide an indication of the descriptive power of the term with respect to the subject of the dictionary containing the term. The same term may have entries in multiple dictionaries with different subject-determining-power scores in each of the dictionaries. The entity distinctions for a term can then be used in tagging documents and processing retrieval requests.

Abstract: Techniques for managing big data include tagging of documents and subsequent retrieval using per-subject dictionaries having entries with some entries specially designated as entities. An entity indicates that the term in the entry has special meaning, e.g., brands (trademarks/service marks), trade names, geographic identifiers or other classes of terms. A dictionary may include a non-entity entry for a term and one or more entity entries, for different entity types. The entries may also include subject-determining-power scores. The subject-determining-power scores provide an indication of the descriptive power of the term with respect to the subject of the dictionary containing the term. The same term may have entries in multiple dictionaries with different subject-determining-power scores in each of the dictionaries. The entity distinctions for a term can then be used in tagging documents and processing retrieval requests.

Abstract: Techniques for managing big data include retrieval using per-subject dictionaries having multiple levels of sub-classification hierarchy within the subject. Entries may include subject-determining-power (SDP) scores that provide an indication of the descriptive power of the entry term with respect to the subject of the dictionary containing the term. The same term may have entries in multiple dictionaries with different SDP scores in each of the dictionaries. A retrieval request for one or more documents containing search terms descriptive of the one or more documents can be processed by identifying a set of candidate documents tagged with subjects, i.e., identifiers of per-subject dictionaries having entries corresponding to a search term, then using affinity values to adjust the aggregate score for the terms in the dictionaries. Documents are then selected for best match to the subject based on the adjusted scores.

Abstract: Techniques for managing big data include retrieval using per-subject dictionaries having multiple levels of sub-classification hierarchy within the subject. Entries may include subject-determining-power (SDP) scores that provide an indication of the descriptive power of the entry term with respect to the subject of the dictionary containing the term. The same term may have entries in multiple dictionaries with different SDP scores in each of the dictionaries. A retrieval request for one or more documents containing search terms descriptive of the one or more documents can be processed by identifying a set of candidate documents tagged with subjects, i.e., identifiers of per-subject dictionaries having entries corresponding to a search term, then using affinity values to adjust the aggregate score for the terms in the dictionaries. Documents are then selected for best match to the subject based on the adjusted scores.

Abstract: Techniques for managing big data include retrieval using per-subject dictionaries having multiple levels of sub-classification hierarchy within the subject. Entries may include subject-determining-power (SDP) scores that provide an indication of the descriptive power of the entry term with respect to the subject of the dictionary containing the term. The same term may have entries in multiple dictionaries with different SDP scores in each of the dictionaries. A retrieval request for one or more documents containing search terms descriptive of the one or more documents can be processed by identifying a set of candidate documents tagged with subjects, i.e., identifiers of per-subject dictionaries having entries corresponding to a search term, then using affinity values to adjust the aggregate score for the terms in the dictionaries. Documents are then selected for best match to the subject based on the adjusted scores.

Abstract: Techniques for managing big data include tagging of documents and subsequent retrieval using per-subject dictionaries having entries with some entries specially designated as entities. An entity indicates that the term in the entry has special meaning, e.g., brands (trademarks/service marks), trade names, geographic identifiers or other classes of terms. A dictionary may include a non-entity entry for a term and one or more entity entries, for different entity types. The entries may also include subject-determining-power scores. The subject-determining-power scores provide an indication of the descriptive power of the term with respect to the subject of the dictionary containing the term. The same term may have entries in multiple dictionaries with different subject-determining-power scores in each of the dictionaries. The entity distinctions for a term can then be used in tagging documents and processing retrieval requests.

Abstract: An integrated memory system with a spiral cache responds to requests for values at a first external interface coupled to a particular storage location in the cache in a time period determined by the proximity of the requested values to the particular storage location. The cache supports multiple outstanding in-flight requests directed to the same address using an issue table that tracks multiple outstanding requests and control logic that applies the multiple requests to the same address in the order received by the cache memory. The cache also includes a backing store request table that tracks push-back write operations issued from the cache memory when the cache memory is full and a new value is provided from the external interface, and the control logic to prevent multiple copies of the same value from being loaded into the cache or a copy being loaded before a pending push-back has been completed.

Abstract: A method, system and computer program product for generating device fingerprints and authenticating devices uses initial states of internal storage cells after each of a number multiple power cycles for each of a number of device temperatures to generate a device fingerprint. The device fingerprint may include pairs of expected values for each of the internal storage cells and a corresponding probability that the storage cell will assume the expected value. Storage cells that have expected values varying over the multiple temperatures may be excluded from the fingerprint. A device is authenticated by a similarity algorithm that uses a match of the expected values from a known fingerprint with power-up values from an unknown device, weighting the comparisons by the probability for each cell to compute a similarity measure.

Abstract: A method and test circuit provide measurements to accurately characterize threshold voltage changes due to negative bias temperature instability (NBTI) and positive bias temperature instability (PBTI). Both the bias temperature instability recovery profile and/or the bias temperature shifts due to rapid repetitions of stress application can be studied. In order to provide accurate measurements when stresses are applied at intervals on the order of tens of nanoseconds while avoiding unwanted recovery, and/or to achieve recovery profile sampling resolutions in the nanosecond range, multiple delay or ring oscillator frequency measurements are made using a delay line that is formed from delay elements that have delay variation substantially caused only by NBTI or PBTI effects. Devices in the delay elements are stressed, and then the delay line/ring oscillator is operated to measure a threshold voltage change for one or more measurement periods on the order of nanoseconds.

Abstract: An integrated memory system with a spiral cache responds to requests for values at a first external interface coupled to a particular storage location in the cache in a time period determined by the proximity of the requested values to the particular storage location. The cache supports multiple outstanding in-flight requests directed to the same address using an issue table that tracks multiple outstanding requests and control logic that applies the multiple requests to the same address in the order received by the cache memory. The cache also includes a backing store request table that tracks push-back write operations issued from the cache memory when the cache memory is full and a new value is provided from the external interface, and the control logic to prevent multiple copies of the same value from being loaded into the cache or a copy being loaded before a pending push-back has been completed.

Abstract: A method, system and computer program product for generating device fingerprints and authenticating devices uses initial states of internal storage cells after each of a number multiple power cycles for each of a number of device temperatures to generate a device fingerprint. The device fingerprint may include pairs of expected values for each of the internal storage cells and a corresponding probability that the storage cell will assume the expected value. Storage cells that have expected values varying over the multiple temperatures may be excluded from the fingerprint. A device is authenticated by a similarity algorithm that uses a match of the expected values from a known fingerprint with power-up values from an unknown device, weighting the comparisons by the probability for each cell to compute a similarity measure.

Abstract: Systolic networks within a tiled storage array provide for movement of requested values to a front-most tile, while making space for the requested values at the front-most tile by moving other values away. A first and second information pathway provide different linear pathways through the tiles. The movement of other values, requests for values and responses to requests is controlled according to a clocking logic that governs the movement on the first and second information pathways according to a systolic duty cycle. The first information pathway may be a move-to-front network of a spiral cache, crossing the spiral push-back network which forms the push-back network. The systolic duty cycle may be a three-phase duty cycle, or a two-phase duty cycle may be provided if the storage tiles support a push-back swap operation.

Abstract: A method, system and computer program product for generating device fingerprints and authenticating devices uses initial states of internal storage cells after each of a number multiple power cycles for each of a number of device temperatures to generate a device fingerprint. The device fingerprint may include pairs of expected values for each of the internal storage cells and a corresponding probability that the storage cell will assume the expected value. Storage cells that have expected values varying over the multiple temperatures may be excluded from the fingerprint. A device is authenticated by a similarity algorithm that uses a match of the expected values from a known fingerprint with power-up values from an unknown device, weighting the comparisons by the probability for each cell to compute a similarity measure.

Abstract: A design structure tangibly embodied in a machine readable medium for designing, manufacturing, or testing an integrated circuit includes a plurality of bit line structures, a plurality of word line structures intersecting said plurality of bit line structures to form a plurality of cell locations, and a plurality of cells located at said plurality of cell locations, each of said cells being selectively coupled to a corresponding bit line structure under control of a corresponding word line structure, each of said cells comprising a logical storage element having at least a first n-type field effect transistor and at least a first p-type field effect transistor, wherein said at least first n-type field effect transistor is formed with a relatively thick buried oxide layer sized to reduce capacitance of said bit line structures, and said at least first p-type field effect transistor is formed with a relatively thin buried oxide layer.