Loaf: a framework and infrastructure for creating online adaptive solutions

Achieving effective online adaptation for natively executed applications has proved quite challenging and to date has not been widely adopted. Traditionally, to enable online adaptation for native binary applications, a run-time layer is added that virtualizes the execution of the application by performing dynamic binary to binary translation. This virtual layer injects trampolines and instrumentation into the translated code to maintain control of the application. This approach adds significant overhead and complexity to the application, discouraging its use for online adaptation in commercial deployments and particularly in the modern datacenter computing domain. In this work we present a new lightweight paradigm for online adaptation that leverages current microarchitectural advances to efficiently enable online monitoring and adaptation without the complexity of binary translation or fine-grain instrumentation. Our methodology takes advantage of the ubiquitous hardware performance monitors present in modern chip micro-architectures to dynamically monitor micro-architectural events and application behavior with negligible overhead. By leveraging these capabilities to develop an innovative lightweight online adaptation framework (Loaf) we are able to address a number of important real-world online adaptation problems.