Abstract: Disclosed are techniques for processing user profiles using data structures that are specialized for processing by a GPU. More particularly, the disclosed techniques relate to systems and methods for evaluating characteristics of user profiles to determine whether to offload certain user profiles to the GPU for processing or to process the user profiles locally by one or more central processing units (CPUs). Processing user profiles may include comparing the interest tags included in the user profiles with logic trees, for example, logic trees representing marketing campaigns, to identify user profiles that match the campaigns.

Abstract: Disclosed are techniques for processing user profiles using data structures that are specialized for processing by a GPU. More particularly, the disclosed techniques relate to systems and methods for evaluating characteristics of user profiles to determine whether to offload certain user profiles to the GPU for processing or to process the user profiles locally by one or more central processing units (CPUs). Processing user profiles may include comparing the interest tags included in the user profiles with logic trees, for example, logic trees representing marketing campaigns, to identify user profiles that match the campaigns.

Abstract: Disclosed are techniques for processing user profiles using data structures that are specialized for processing by a GPU. More particularly, the disclosed techniques relate to systems and methods for evaluating characteristics of user profiles to determine whether to offload certain user profiles to the GPU for processing or to process the user profiles locally by one or more central processing units (CPUs). Processing user profiles may include comparing the interest tags included in the user profiles with logic trees, for example, logic trees representing marketing campaigns, to identify user profiles that match the campaigns.

Abstract: Disclosed are techniques for processing user profiles using data structures that are specialized for processing by a GPU. More particularly, the disclosed techniques relate to systems and methods for evaluating characteristics of user profiles to determine whether to offload certain user profiles to the GPU for processing or to process the user profiles locally by one or more central processing units (CPUs). Processing user profiles may include comparing the interest tags included in the user profiles with logic trees, for example, logic trees representing marketing campaigns, to identify user profiles that match the campaigns.

Abstract: Disclosed are techniques for processing user profiles using data structures that are specialized for processing by a GPU. More particularly, the disclosed techniques relate to systems and methods for evaluating characteristics of user profiles to determine whether to offload certain user profiles to the GPU for processing or to process the user profiles locally by one or more central processing units (CPUs). Processing user profiles may include comparing the interest tags included in the user profiles with logic trees, for example, logic trees representing marketing campaigns, to identify user profiles that match the campaigns.

Abstract: Disclosed are techniques for processing user profiles using data structures that are specialized for processing by a GPU. More particularly, the disclosed techniques relate to systems and methods for evaluating characteristics of user profiles to determine whether to offload certain user profiles to the GPU for processing or to process the user profiles locally by one or more central processing units (CPUs). Processing user profiles may include comparing the interest tags included in the user profiles with logic trees, for example, logic trees representing marketing campaigns, to identify user profiles that match the campaigns.

Abstract: Disclosed are techniques for processing user profiles using data structures that are specialized for processing by a GPU. More particularly, the disclosed techniques relate to systems and methods for evaluating characteristics of user profiles to determine whether to offload certain user profiles to the GPU for processing or to process the user profiles locally by one or more central processing units (CPUs). Processing user profiles may include comparing the interest tags included in the user profiles with logic trees, for example, logic trees representing marketing campaigns, to identify user profiles that match the campaigns.

Abstract: A delayed shutoff device comprises a conduit configured to allow a fluid to flow through, wherein the conduit includes a conduit start and a conduit end. The device further comprises a plug configured to be placed inside the conduit at the conduit start; move inside the conduit from the conduit start toward the conduit end when the fluid flows through the conduit; and reduce the fluid flow upon reaching the conduit end. The device is configured to allow a pass-through quantity of the fluid to pass through the conduit while the plug moves from the conduit start to the conduit end. The conduit end may form a seat, the plug being configured to stop moving upon reaching the seat. The plug may be configured to fit the seat imperfectly, to allow a seepage of the fluid after reaching the seat.

Abstract: A delayed shutoff device comprises a conduit configured to allow a fluid to flow through, wherein the conduit includes a conduit start and a conduit end. The device further comprises a plug configured to be placed inside the conduit at the conduit start; move inside the conduit from the conduit start toward the conduit end when the fluid flows through the conduit; and reduce the fluid flow upon reaching the conduit end. The device is configured to allow a pass-through quantity of the fluid to pass through the conduit while the plug moves from the conduit start to the conduit end. The conduit end may form a seat, the plug being configured to stop moving upon reaching the seat. The plug may be configured to fit the seat imperfectly, to allow a seepage of the fluid after reaching the seat.

Abstract: An insurance company issues a property policy to a customer for property encumbered with an obligation to a creditor. The policy is to be issued to include an encumbrance clause as specified by the creditor. An identification of the creditor is provided to a clause database owned and maintained by a third party agent of the insurance company. The clause database determines that the identified creditor has an entry therein, retrieves from the entry the encumbrance clause as specified by the creditor, and returns the retrieved clause, which is received and inserted into the policy to be issued.

Abstract: Embodiments include methods and apparatus for mixing feedgases and producing synthesis gas. The apparatus includes a vessel containing a mixing system comprising one or more channels and a reaction zone downstream of the mixing system. A first feedgas and a second feedgas are separately injected into different injection portions of each channel, such that the second feedgas is injected in an acute direction into the first feedgas flowstream. The injected feedgases thereafter mix in a mixing portion of the channel. The mixing portion of each channel may have a reduced cross-sectional area so as to increase the total velocity of the feedgases while they mix. A feedgas mixture exits each channel of the mixing system to feed the reaction zone where it gets converted. Preferred embodiments include mixing O2 with a hydrocarbon gas and converting the mixture in a catalytic reaction zone to produce synthesis gas.

Abstract: A massively-parallel computer includes a plurality of processing nodes and at least one control node interconnected by a network. The network faciliates the transfer of data among the processing nodes and of commands from the control node to the processing nodes. Each processing node includes an interface for transmitting data over, and receiving data and commands from, the network, at least one memory module for storing data, a node processor and an auxiliary processor. The node processor receives commands received by the interface and processes data in response thereto, in the process generating memory access requests for facilitating the retrieval of data from or storage of data in the memory module. The node processor further controlling the transfer of data over the network by the interface. The auxiliary processor is connected to the memory module and the node processor.

Abstract: A massively-parallel computer includes a plurality of processing nodes and at least one control node interconnected by a network. The network faciliates the transfer of data among the processing nodes and of commands from the control node to the processing nodes. Each each processing node includes an interface for transmitting data over, and receiving data and commands from, the network, at least one memory module for storing data, a node processor and an auxiliary processor. The node processor receives commands received by the interface and processes data in response thereto, in the process generating memory access requests for facilitating the retrieval of data from or storage of data in the memory module. The node processor further controlling the transfer of data over the network by the interface. The auxiliary processor is connected to the memory module and the node processor.

Abstract: An apparatus and method for efficiently mapping elements of an array to processing elements (PEs) of a parallel data computer. Axis lengths and weights are received from a compiler (if invoked at compile time) or an application program (if invoked at run time). A physical grid is generated by expanding the axis lengths so that their product is integrally divisible by "machine.sub.-- bits" (i.e., log.sub.2 (number of PEs on the data parallel computer)). The physical grid is divided into subgrids of equal size by dividing each expanded axis length into subgrid lengths of equal length. The lengths and numbers of subgrid lengths in each axis are then output to the compiler or the application program. From the subgrid lengths, the compiler or application program can identify a unique location in one of the subgrids given any location of an element in the array.