Abstract: Response latencies in a system are reduced by performing a plurality of auctions in parallel using respective processing threads. An ad call associated with an impression for a webpage requested by a user computer is received by the system. Impression information is obtained based on the ad call, which is then used to determine a subset of multiple potential impression providers that are to participate in an auction for the impression. Behavior models may be used to determine the subset, while floor or reserve price models are used to set a floor/reserve price for each potential impression provider in the subset. Bid requests are sent out in parallel to the subset of potential impression providers using the respective floor/reserve prices, with a thread allocated to each bid request. The models can be further trained on information obtained from the received bid responses and impression information.

Abstract: Response latencies in a system are reduced by performing a plurality of auctions in parallel using respective processing threads. An ad call associated with an impression for a webpage requested by a user computer is received by the system. Impression information is obtained from the ad call, which is then used to determine a subset of multiple potential impression providers that are to participate in an auction for the impression. Behavior models are used to determine the subset, while floor or reserve price models are used to set a floor/reserve price for each potential impression provider in the subset. Bid requests are sent out in parallel to the subset of potential impression providers using the respective floor/reserve prices, with a thread allocated to each bid request. The models can be further trained on information obtained from the received bid responses and impression information.