Microsoft Technology Licensing, LLC

Sankar Sundaram

Manu Srivastava

Briton Zurcher

Louis Lafreniere

Curtis Man

Ritesh Rambhai Parikh

Arjun Bijanki

Sandeep Agarwal

A method for utilizing elastic resource pooling techniques to dynamically rebalance throughput includes determining, for each of multiple tenants leasing computing resources of a shared resource pool, a desired claim to resources in the shared resource pool. The desired claim is based on a number of resource access requests received in association with each of the multiple tenants. The method further includes determining, for each of the multiple tenants, a guaranteed claim and a maximum potential claim on the shared resource pool; and allocating a surplus resource pool among the multiple tenants based on the determined maximum potential claim and the desired claim for each one of the multiple tenants, the surplus resource pool representing a remainder of the shared resource pool after the guaranteed claim for each of the tenants is satisfied via an initial resource allocation from the shared resource pool.

Elastic resource pooling for dynamic throughput rebalancing

Systems, methods and computer program products are described herein for testing a system that is designed to optimize the execution of code within an application or other computer program based on profile data collected during the execution of such code. The embodiments described herein utilize what is referred to as a 'profile data mutator' to mutate or modify the profile data between the point when it is collected and the point when it is used to apply an optimization. By mutating the profile data at this point, testing of a system for optimized code execution can be significantly more thorough. Furthermore, such profile data mutation leads to a more scalable and efficient testing technique for profile-guided systems for optimized code execution.

Test strategy for profile-guided code execution optimizers

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Sankar Sundaram