Abstract: Embodiments are provided that related to a computer system, a computer program product, and a computer-implemented method for improving performance of a dialog system employing an automated virtual dialog agent. Embodiments involve utilizing an automated virtual agent to receive a natural language request and generate a corresponding response, automatically identifying and resolving a corresponding knowledge gap between the request and response, and refined the automated virtual agent with the resolved knowledge gap.

Abstract: Embodiments for optimizing dynamic resource allocations in a disaggregated computing environment. A new workload is assigned to a subset of a plurality of processors, the subset of processors assigned a subset of a plurality of cache devices. A determination is made that the new workload is categorized as a cache-friendly workload having a memory need which can be met primarily by the subset of cache devices by identifying that underlying data necessitated by the new workload resides primarily within the subset of cache devices. Pursuant to determining the new workload is the cache-friendly workload, a cache related action is performed to increase performance of the new workload executed by the subset of processors and commensurately executes additional workloads performed by other ones of the plurality of processors within the disaggregated computing environment.

Abstract: A new approach to resiliency management is provided in a data center wherein servers are constructed dynamically, on-demand and based on workload requirements and a tenant's resiliency requirements by allocating resources from these pools. In this approach, a set of functionally-equivalent “interchangeable compute units” (ICUs) are composed of resources from resource pools that have been extended to include not only different resource types (CPU, memory, accelerators), but also resources of different specifications (specs) and flavors. As a workload is being processed, the health or status of the resources are monitored. Upon a performance issue or failure event, a resiliency manager can swap out a current ICU and replace it with a functionally-equivalent ICU. Preferably, individual ICUs are hosted on one of: resources of a same type each with different specifications, and resources of a same type and specification and different flavors.

Abstract: Embodiments for preemptive substitution of resources in a disaggregated computing environment. Failure patterns and mitigation actions are analyzed for specific failures of respective resources within the disaggregated computing environment. Responsive to determining a failure threshold has been reached for a first resource of a first type of the respective resources, a mitigation action is performed according to the analyzed failure patterns. A result of the mitigation action is determined and the result is used to improve the failure pattern analyzation.

Abstract: Computer-implemented techniques for unsupervised event extraction are provided. In one instance, a computer implemented method can include parsing, by a system operatively coupled to a processor, unstructured text comprising event information to identify candidate event components. The computer implemented method can further include employing, by the system, one or more unsupervised machine learning techniques to generate structured event information defining events represented in the unstructured text based on the candidate event components.

Abstract: Given a skeleton knowledge graph including first terms in respective nodes, wherein first terms in connected nodes have a predetermined relationship, an augmented knowledge graph is formed by a first computing device by extracting a second term from a domain corpus to form a term cluster linked with a respective node of the knowledge graph. The second term is associated with the first term of a respective node in the domain corpus while not meeting the predetermined relationship. A semantic feature between the second term and the associated first term is identified in the domain corpus and linked to the pair of the second term and the first term in the augmented knowledge graph. The augmented knowledge graph is useable by a second computing device, which may or may not be the same as the first computing device, to drive a conversation between a chatbot and user.

Abstract: Embodiments are provided herein for efficient component communication and resource optimization in a disaggregated computing system. A general purpose link is provided between a plurality of devices in the disaggregated computing system. The general purpose link is used to connect the plurality of devices which respectively comprise different types of devices. A first data object is stored within one of the plurality of devices according to a past use or an expected use of the data object by at least a respective one of a set of processors within the disaggregated computing system, and the general purpose link is dynamically rewired according to a location of the first data object and a location of the at least one of the respective set of processors.

Abstract: For power management in a disaggregated computing system, upon detecting an electrical power reduction to the disaggregated computing system, respective workloads being performed by respective processors within a set of processors are prioritized according to a service level agreement (SLA) of the respective workloads. Backup electrical power is dynamically allocated to the respective processors performing the respective workloads based upon a priority of the SLA of the respective workloads.

Abstract: Embodiments are provided herein for efficient component communication and resource optimization in a disaggregated computing system. A general purpose link is provided to connect a computing element to a plurality of other computing elements of the disaggregated computing system. The general purpose link is dynamically switched between a plurality of different hardware protocols to communicate with the other computing elements, where respective ones of the other computing elements comprise different types of hardware elements.

Abstract: One embodiment of the invention provides a method for terminology ranking for use in natural language processing. The method comprises receiving a list of terms extracted from a corpus, where the list comprises a ranking of the terms based on frequencies of the terms across the corpus. The method further comprises accessing a domain ontology associated with the corpus, and re-ranking the list based on the domain ontology. The resulting re-ranked list comprises a different ranking of the terms based on relevance of the terms using knowledge from the domain ontology. The method further comprises generating clusters of terms via a trained model adapted to the corpus, and boosting a rank of at least one term of the re-ranked list based on the clusters to increase a relevance of the at least one term using knowledge from the trained model.

Abstract: Server resources in a data center are disaggregated into shared server resource pools. Servers are constructed dynamically, on-demand and based on workload requirements, by allocating from these resource pools. A disaggregated compute system of this type keeps track of resources that are available in the shared server resource pools, and it manages those resources based on that information. Each server entity built is assigned with a unique server ID, and each resource that comprises a component thereof is tagged with the identifier. As a workload is processed by the server entity, its composition may change, e.g. by allocating more resources to the server entity, or by de-allocating resources from the server entity. Workload requests are associated with the unique server ID for the server entity. When a workload request is received at a resource, it matches its unique server ID to that of the request before servicing the request.

Abstract: Various embodiments for performing hardware upgrades in a disaggregated computing environment. A workload is run on a disaggregated computing system while providing a new component to at least one of a plurality of component pools used by the disaggregated computing system. Point-to-point circuit wire level switching is used to switch the disaggregated system from an assigned component residing in a first of the plurality of component pools to the new component residing in a second of the plurality of component pools without interrupting the running workload.

Abstract: An embodiment parses request data representative of a request for proposal (RFP) and extracts attribute data representative of an RFP attribute that corresponds to an entity of interest in a qualification taxonomy using a cognitive process to evaluate the RFP using natural language processing. The embodiment generates answer data representative of an answer to a first question of a qualification questionnaire related to the entity of interest using the RFP attribute. The embodiment constructs the answer data based at least in part on a response pattern associated with the first question, and computes a score for the answer to the first question based at least in part on a confidence value generated by the cognitive process. The embodiment then outputs the qualification questionnaire, including the answer and the score, allowing for review by a Subject Matter Expert (SME), and allowing the cognitive process to learn from the SME review.

Abstract: Embodiments for component lifecycle optimization in a disaggregated computing environment. A monitoring and machine learning process is performed to learn a respective lifecycle of different resource types as the different resource types are assigned to respective workloads. The monitoring and machine learning process is used to develop a set of learned failure patterns for determining a mitigation action to perform as new faults are encountered within each of the different resource types while executing the respective workloads. The mitigation action is performed to optimize a remaining lifecycle of respective ones of the different resource types according to the set of learned failure patterns.

Abstract: Embodiments for disaster recovery in a disaggregated computing system. A memory pool is allocated including allocated memory elements at a secondary, disaster recovery site for data received from memory pool elements within the memory pool at a primary site. Data is continuously replicated to the allocated memory elements at the disaster recovery site. During a disaster recovery failover, a determination is made whether there are sufficient resources in the disaggregated computing system for performing workloads of a certain type. If insufficient resources are available, a disaster recovery process is initiated to re-allocate the resources for performing given workloads of the certain type.

Abstract: Identify individual machines of a multi-machine computing system. Construct a graph of dependencies among the machines. Obtain estimated total administration times and administration priorities for each of the machines. Identify availability of administration resources to assist in administration of one or more of the machines. Select a first set of machines for administration in response to the graph, administration priorities, estimated total administration times, and availability of the first set of administration resources, and administer the first set of machines in parallel using the first set of administration resources. Update the graph in response to administration of the first set of machines. Select a subsequent set of machines for administration in response to the updated graph, administration priorities, estimated total administration times, and availability of a subsequent set of administration resources.

Abstract: A group of processors in a processor pool comprise a secure “enclave” in which user code is executable and user data is readable solely with the enclave. This is facilitated through the key management scheme described that includes two sets of key-pairs, namely: a processor group key-pair, and a separate user key-pair (typically one per-user, although a user may have multiple such key-pairs). The processor group key-pair is associated with all (or some define subset of) the processors in the group. This key-pair is used to securely communicate a user private key among the processors. The user private key, however, is not transmitted to non-members of the group. Further, preferably the user private key is refreshed periodically or upon any membership change (in the group) to ensure that non-members or ex-members cannot decipher the encrypted user key.

Abstract: Embodiments are provided herein for maximizing resource utilization in a disaggregated computing system. A general purpose link is established between a first sub-plurality of computing elements and a second sub-plurality of computing elements. The first sub-plurality belongs to a first plurality of computing components of a first type and the second sub-plurality belongs to a second plurality of computing components of a second type in the disaggregated computing system. A determination is made that the first and second sub-pluralities of computing elements are assigned to a first tenant having first data communications. The general purpose link is secured to the first tenant while allowing second data communications of a second tenant to pass through the general purpose link concurrent with the first data communications of the first tenant.

Abstract: An example operation may include one or more of receiving, by a disaster recovery orchestrator, configuration changes independent from a disaster recovery test schedule, from one or more monitoring agents at each of an information technology system, analyzing incremental configuration changes since a previous disaster recovery test for potential to limit a need for unnecessary disaster recovery retest, determining component level changes at each information technology system that impact disaster recovery test readiness, initiating a partial disaster recovery retest without regard to periodic disaster recovery test schedules, in response to incremental configuration changes that are at the information technology system component-level, and invoking a blockchain service to generate blockchain transactions, the blockchain transactions committing configuration changes, disaster recovery testing actions, and disaster recovery testing results to a shared ledger of a blockchain network.

Abstract: Embodiments for disaster recovery in a disaggregated computing system. Memory resources are allocated at a secondary, disaster recovery site for data received from a primary site. The data from the primary site is continuously replicated to the allocated memory resources at the disaster recovery site without requiring any compute resources to be attached to the allocated memory resources. Responsive to determining a disaster recovery failover is in progress, the compute resources are assigned to the allocated memory resources for performing a failover workload, and the failover workload is executed at the disaster recovery site.