Abstract: In general, this disclosure is directed to determining an optimal markup policy for a third party delivery service. One aspect is a method for dynamically optimizing prices by a third party delivery service, the method comprising retrieving item information for a plurality of items including pricing data, the plurality of items being sold by a retailer and available for delivery by the third party delivery service, simulating a plurality of markup policies with a neural network trained to identify non-linear price-demand relationships between the plurality of items, determining, as part of simulating the plurality of markup policies, an optimal markup policy for the third party delivery service, and providing a user interface to a customer computing device, the user interface displaying at least some of the plurality of items for delivery by the third party delivery service with prices reflecting the optimal markup policy.

Abstract: In general, this disclosure is directed to determining an optimal markup policy for a third party delivery service. One aspect is a method for dynamically optimizing prices by a third party delivery service, the method comprising retrieving item information for a plurality of items including pricing data, the plurality of items being sold by a retailer and available for delivery by the third party delivery service, simulating a plurality of markup policies with a neural network trained to identify non-linear price-demand relationships between the plurality of items, determining, as part of simulating the plurality of markup policies, an optimal markup policy for the third party delivery service, and providing a user interface to a customer computing device, the user interface displaying at least some of the plurality of items for delivery by the third party delivery service with prices reflecting the optimal markup policy.

Abstract: A smart scheduler is provided to prepare a machine for a job, wherein the job has specific requirements, i.e., dimensions. One or more config jobs are identified to configure the machine to meet the dimensions of the job. Information concerning the machine's original configuration and groupings of config jobs that change the machine's configuration are cached in a central storage. The smart scheduler uses information in the central storage to identify a suitable machine and one or more config jobs to configure the machine to meet the dimensions of a job. The smart scheduler schedules a run for the config jobs on the machine.

Abstract: A system and method is provided for cooperative execution of distributed tasks by networked computers without the use of a centralized controller to coordinate the task execution. Each computer has an execution agent that cooperates with the execution agents of the other computers to carry out the execution of a given sequence of tasks. The execution instructions for the task sequence are provided to a first computer in the selected set of computers for task execution. The first computer processes the instructions and forwards them to its peer computers so that each of them knows the tasks it is to perform in connection with the tasks of the other computers. The computers then executes the tasks assigned to them and use peer-to-peer communications to provide status update to their peer computers to synchronize and coordinate the task execution.

Abstract: A system and method is provided for cooperative execution of distributed tasks by networked computers without the use of a centralized controller to coordinate the task execution. Each computer has an execution agent that cooperates with the execution agents of the other computers to carry out the execution of a given sequence of tasks. The execution instructions for the task sequence are provided to a first computer in the selected set of computers for task execution. The first computer processes the instructions and forwards them to its peer computers so that each of them knows the tasks it is to perform in connection with the tasks of the other computers. The computers then executes the tasks assigned to them and use peer-to-peer communications to provide status update to their peer computers to synchronize and coordinate the task execution.

Abstract: A mechanism dynamically allocates physical machines (computers) for satisfying requests for the machines, such as in the context of assigning test machines for running test cases. Each request specifies one or more logical machine sets it needs, and each logical machine set has specified requirements. The physical machines are organized into a hierarchical structure that includes groups and subgroups of machines. An allocation engine performs the function of allocating available machines from a selected group in the hierarchy for a request based on the requirements of each logical machine set of the request. A group or subgroup of machines may be marked as “allocate as one unit” and all machines in it will be reserved for one request. A job corresponding to a request may have sub-jobs, and machines allocated for the sub-job are selected from the machines allocated for the parent job.