Abstract: Methods, systems, and computer program products for auto-discovery of reasoning knowledge graphs in supply chains are provided herein. A computer-implemented method includes obtaining a spatiotemporal query related to a demand of at least one product in a supply chain; analyzing the spatiotemporal query to identify one or more parameters affecting the demand of the at least one product, wherein the one or more parameters comprise at least one of one or more climate parameters and one or more disruptive event parameters; generating a knowledge graph comprising information indicating an impact on the demand of the at least one product for at least a portion of the one or more parameters; and outputting, to a user interface, an explanation of a predicted demand forecast for the at least one product based at least in part on the knowledge graph.

Abstract: Computer-implemented systems and methods for updating a polygonal mesh representation of a model are provided. A model comprises a set of topologies, and a meshing state is maintained for each topology of the set of topologies. The meshing state indicates, for a given topology, whether a polygonal mesh exists and is valid. A change made to the model is determined, where the change comprises a modification to a geometry of the model or a modification to mesh settings of a polygonal mesh representation of the model. One or more topologies of the set of topologies that are affected by the change are determined, and the meshing state for the affected one or more topologies is updated. Based on the one or more updated meshing states, a set of meshing operations needed to bring the polygonal mesh representation of the model up-to-date is determined.

Abstract: A computing system includes: a storage interface configured to access an application code including a target code; a control unit, coupled to the storage interface, configured to: identify a consumption model corresponding to the target code, calculate a consumption estimate for the target code based on the consumption model, and generate a code-power analysis output based on the consumption estimate.

Abstract: String matching a first string to a string stored in a string dictionary is performed by k-way hashing the first string and locating corresponding k hash locations in a first memory. When any of the k hash locations has a zero Bloom bit, the first string is deemed to not match any of the strings in the string dictionary. Otherwise, a sub-set of the k hash locations identified as those k hash locations having non-zero Bloom bits and a unique bit set to 1 each include a pointer that points to a string in the string dictionary that is fetched and compared to the first string wherein the fetches from the string dictionary are interleaved over the addresses from the first memory. A match signal is issued when the first string matches at least one of the strings stored in the dictionary.

Abstract: An efficient finite state machine implementation of a string matching that relies upon a Content Addressable Memory (CAM) or a CAM-equivalent collision-free hash-based lookup architecture with zero false positives used as a method for implementing large FSMs in hardware using a collision-free hash-based look up scheme with low average case bandwidth and power requirements that overcomes prior art limitations by providing the ability to match an anchored or unanchored input stream against a large dictionary of long and arbitrary length strings at line speed. It should be noted that in the context of the described embodiments, a string could take many forms, such as a set of characters, bits, numbers or any combination thereof.