Google Inc.

Jason Mars

Robert Hundt

Lingjia Tang

Neil A Vachharajani

Systems and methods for mapping applications onto system resource of a computing platform are discussed. The computing platform may receive, using control circuitry, a request to run a plurality of applications on a computing platform having a plurality of system resources. The computing platform may determine a plurality of mapping configurations for the plurality of applications onto the plurality of system resources. The computing platform may execute the plurality of applications with each of the plurality of mapping configurations. The computing platform may determine at least one performance metric based on the executed plurality of applications for each of the plurality of mapping configurations. The computing platform may select a selected mapping configuration among the plurality of mapping configurations based on at least one determined performance metric.

System and methods for sharing memory subsystem resources among datacenter applications

Aspects of the invention may be used to allocate tasks among computing machines in large scale computing systems. In one aspect, the method includes executing a first task in the plurality of tasks on a first computing machine and determining a performance degradation threshold for the first task. The method further includes calculating a predicted performance degradation of the first task when a second task is executed on the first computing machine, wherein the predicted performance degradation is determined by comparing a performance interference score of the second task with a performance sensitivity curve of the first task. The method further includes executing the second task on the first computing machine when the predicted performance degradation of the first task is below the performance degradation threshold.

Allocation of tasks in large scale computing systems

A first indicator of a first number of cache misses to a cache memory of a multicore processor for a first application over a first time period is received. The first application executes on a first core of the processor and a second application simultaneously executes on a second core of the processor during the first time period. The first and second cores share the cache memory. A second indicator of a second number of cache misses to the cache memory for the first application over a second time period is received. During the second time period, the first application executes on the first core and the second application does not execute on the second core. A degree of contention among the first and second applications is determined based on the first and second indicators, and execution of the second application is adjusted based on the determined degree of contention.

Cache contention management on a multicore processor based on the degree of contention exceeding a threshold

Techniques and systems for scenario based optimization can include generating multiple different versions of a program segment based on different respective execution scenarios associated with an execution of a program, the program operable to use the program segment versions. In another aspect, techniques and systems can include executing a program executable associated with multiple different versions of a program segment, analyzing the execution for an indication of at least one of the execution scenarios to select one of the program segment versions based on the indication, and causing the execution to use the selected program segment version during at least a portion of the execution.

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Charlottesville, VA, United States of America

Jason Mars