Abstract: Volatile organic compounds classification by receiving test data associated with detecting volatile organic compounds (VOCs), analyzing the test data according to a set of data features associated with known VOCs, determining a match between each feature of the test data and a corresponding feature of the set of data features, yielding a set of matches, defining a first degree of anomaly for the test data according to the set of matches, and classifying the test data according to the first degree of anomaly.

Abstract: Core utilization optimization by dividing computational blocks across neurosynaptic cores is provided. In some embodiments, a neural network description describing a neural network is read. The neural network comprises a plurality of functional units on a plurality of cores. A functional unit is selected from the plurality of functional units. The functional unit is divided into a plurality of subunits. The plurality of subunits are connected to the neural network in place of the functional unit. The plurality of functional units and the plurality of subunits are reallocated between the plurality of cores. One or more unused cores are removed from the plurality of cores. An optimized neural network description is written based on the reallocation.

Abstract: Volatile organic compounds classification by receiving test data associated with detecting volatile organic compounds (VOCs), analyzing the test data according to a set of data features associated with known VOCs, determining a match between each feature of the test data and a corresponding feature of the set of data features, yielding a set of matches, defining a first degree of anomaly for the test data according to the set of matches, and classifying the test data according to the first degree of anomaly.

Abstract: A method for multiplying two binary numbers includes configuring, in an integrated circuit, a plurality of lookup tables based on a known binary number (w). The lookup tables can be configured in three layers. The method further includes receiving, by the integrated circuit, an input binary number (d). The method further includes determining, by the integrated circuit, a multiplication result (p) of the known binary number w and the input binary number d by determining each bit (pi) from p using the lookup tables based on specific combinations of bits from the known binary number w and from the input binary number d, wherein a notation jx represents the xth bit of j from the right, with bit j0 being the rightmost bit of j.

Abstract: A computer-implemented method includes receiving characteristic information of a container registry. The container registry includes a plurality of container images. The method includes selecting at least two container images in the container registry and selecting parameters for optimization based on the characteristic information. The method also includes generating a cost function based on the parameters for optimization and optimizing the at least two container images in the container registry based on the cost function. A computer-implemented method includes receiving a composition of each of at least two layers in a container image. The composition of each of the at least two layers includes at least one file. The method includes mapping overlap between the composition of the at least two layers and estimating a redundancy in the container image based on the overlap. The method also includes calculating new layers which reduce the redundancy in the container image.

Abstract: A method for multiplying two binary numbers includes configuring, in an integrated circuit, a plurality of lookup tables based on a known binary number (w). The lookup tables can be configured in three layers. The method further includes receiving, by the integrated circuit, an input binary number (d). The method further includes determining, by the integrated circuit, a multiplication result (p) of the known binary number w and the input binary number d by determining each bit (pi) from p using the lookup tables based on specific combinations of bits from the known binary number w and from the input binary number d, wherein a notation jx represents the xth bit of j from the right, with bit j0 being the rightmost bit of j.

Abstract: The embodiments relate to assigning data to processors of a file system. Metadata associated with respective blocks of data, and an initial batch of the blocks is assigned to nodes of a file system based on the metadata. Unassigned blocks are selectively assigned to one or more of the nodes. The selective assignment includes constructing a linear regression model based on node data, and determining a value for each node based on the linear regression model. Each value is associated with a predicted load corresponding to a new assignment of one or more unassigned blocks.

Abstract: A method, computerized apparatus and a computer program product for anomaly detection in a distributed system. The method comprises obtaining measurements of metrics of the distributed system within a timeframe. Each measurement comprises a time-series of values to a metric associated with an action of a component of the distributed system that was measured within the timeframe. A set of percentiles of the measurements is computed, whereby a dimensionality of the sets of percentiles is larger than a dimensionality of the metrics. A multivariate anomaly detection is performed based on the weights of the percentiles to determine an anomaly in the sets of percentiles. In response to detecting an anomaly, a source of the anomaly is identified based on a subset of the percentiles having weights above a threshold, by determining common components or actions that are common to at least a portion of the subset of the percentiles.

Abstract: A method, computerized apparatus and a computer program product for anomaly detection in a distributed system. The method comprises obtaining measurements of metrics of the distributed system within a timeframe. Each measurement comprises a time-series of values to a metric associated with an action of a component of the distributed system that was measured within the timeframe. A set of percentiles of the measurements is computed, whereby a dimensionality of the sets of percentiles is larger than a dimensionality of the metrics. A multivariate anomaly detection is performed based on the weights of the percentiles to determine an anomaly in the o sets of percentiles. In response to detecting an anomaly, a source of the anomaly is identified based on a subset of the percentiles having weights above a threshold, by determining common components or actions that are common to at least a portion of the subset of the percentiles.

Abstract: A computer-implemented method includes receiving characteristic information of a container registry. The container registry includes a plurality of container images. The method includes selecting at least two container images in the container registry and selecting parameters for optimization based on the characteristic information. The method also includes generating a cost function based on the parameters for optimization and optimizing the at least two container images in the container registry based on the cost function. A computer-implemented method includes receiving a composition of each of at least two layers in a container image. The composition of each of the at least two layers includes at least one file. The method includes mapping overlap between the composition of the at least two layers and estimating a redundancy in the container image based on the overlap. The method also includes calculating new layers which reduce the redundancy in the container image.

Abstract: In one embodiment, a computer program product for optimizing core utilization in a neurosynaptic network includes a computer readable storage medium having program instructions embodied therewith, where the computer readable storage medium is not a transitory signal per se, and where the program instructions are executable by a processor to cause the processor to perform a method including identifying, by the processor, one or more unused portions of a neurosynaptic network, and for each of the one or more unused portions of the neurosynaptic network, disconnecting, by the processor, the unused portion from the neurosynaptic network.

Abstract: Core utilization optimization by dividing computational blocks across neurosynaptic cores is provided. In some embodiments, a neural network description describing a neural network is read. The neural network comprises a plurality of functional units on a plurality of cores. A functional unit is selected from the plurality of functional units. The functional unit is divided into a plurality of subunits. The plurality of subunits are connected to the neural network in place of the functional unit. The plurality of functional units and the plurality of subunits are reallocated between the plurality of cores. One or more unused cores are removed from the plurality of cores. An optimized neural network description is written based on the reallocation.

Abstract: Embodiments of the invention relate to a storage system organized into a hierarchy of storage tiers, with at least one tier reflecting a high performance tier and at least one tier reflecting a lower performance tier. The high performance tier has a capacity restriction and has a limited quantity of blocks and pages may be placed in the tier. Assessments are conducted and a preferred selection of blocks and pages are recommended for placement; the recommendation is based on the assessment. The recommendation is converted to an actual placement, resulting in placement of at least one block, an in one embodiment at least one page, in the high performance tier.

Abstract: Core utilization optimization by dividing computational blocks across neurosynaptic cores is provided. In some embodiments, a neural network description describing a neural network is read. The neural network comprises a plurality of functional units on a plurality of cores. A functional unit is selected from the plurality of functional units. The functional unit is divided into a plurality of subunits. The plurality of subunits are connected to the neural network in place of the functional unit. The plurality of functional units and the plurality of subunits are reallocated between the plurality of cores. One or more unused cores are removed from the plurality of cores. An optimized neural network description is written based on the reallocation.

Abstract: In one embodiment, a computer program product for optimizing core utilization in a neurosynaptic network includes a computer readable storage medium having program instructions embodied therewith, where the computer readable storage medium is not a transitory signal per se, and where the program instructions are executable by a processor to cause the processor to perform a method including identifying, by the processor, one or more unused portions of a neurosynaptic network, and for each of the one or more unused portions of the neurosynaptic network, disconnecting, by the processor, the unused portion from the neurosynaptic network.

Abstract: Embodiments relate to host-side cache migration. An aspect is a method that includes determining pre-fetch hints associated with a source cache that is local to a source host machine. The source cache includes pages of cache data for a virtual machine. The pre-fetch hints are sent to a pre-fetch planner to create a pre-fetch plan. The pre-fetch hints are sent based on migration of the virtual machine to a target host machine including a target cache that is local. At the source host machine, a cache migration request is received based on the pre-fetch plan. A first subset of the pages is sent from the source cache through a host-to-host communication channel to the target cache based on the cache migration request. A second subset of the pages is sent from the source cache through a host-storage communication channel to a shared storage to be relayed to the target cache.

Abstract: A computer-implemented method is provided for optimizing core utilization in a neurosynaptic network. The computer-implemented method comprises identifying one or more unused portions of a neurosynaptic network. Additionally, the computer-implemented method comprises, for each of the one or more unused portions of the neurosynaptic network, disconnecting the unused portion from the neurosynaptic network.

Abstract: One embodiment of a method, executed by one or more processors, includes receiving a request from a client for a network resource, selecting a previously-serviced client as a proxy client, forwarding the request to the proxy client, receiving the network resource from the proxy client, and forwarding the network resource to the client. In another embodiment, the method includes receiving a request from a client for a network resource, selecting a proxy client from a dynamic pool of proxy clients that are each capable of requesting the network resource, and directing the request from the client to the proxy client. The selected proxy client may be the client whose request immediately preceded the current request. A computer system and computer program product corresponding to the method are also disclosed herein.

Abstract: The embodiments relate to assigning data to processors of a file system. Metadata associated with respective blocks of data, and an initial batch of the blocks is assigned to nodes of a file system based on the metadata. Unassigned blocks are selectively assigned to one or more of the nodes. The selective assignment includes constructing a linear regression model based on node data, and determining a value for each node based on the linear regression model. Each value is associated with a predicted load corresponding to a new assignment of one or more unassigned blocks.

Abstract: The present invention provides a method, system, and computer program product of managing telephone interactions of a user and an agent. In an embodiment, the present invention includes determining when a user telecommunications device is no longer in an on-hold state based on electronic signals transmitted from an agent telecommunications device, in response to the determining, receiving speech of an agent from the agent telecommunications device, in response to the receiving, transmitting an alert message to the user telecommunications device, in response to the receiving, monitoring for at least one indication that the user is about to speak with the agent, in response to the monitoring not resulting in the at least one indication, transmitting at least one utterance corresponding to the user to the agent telecommunications device, and in response to the monitoring resulting in the at least one indication, conducting a smooth transition to the user.