Search

We propose Intelligent Watcher (iWatcher), a combination of hardware and software support that can detect large variations of software bugs with only modest hardware changes to current processor implementations. iWatcher lets programmers associate specified functions to "watched" memory locations or objects. Access to any such location automatically triggers the monitoring function in the hardware. Relative to other approaches, iWatcher detects many real bugs at a fraction of the execution-time overhead

Energy consumption has become an important issue in the design of battery-operated mobile devices and sophisticated data centers. The storage hierarchy, which includes memory and disks, is a major energy consumer in such systems; especially for high-end servers at data centers. Much work has focused on energy control algorithms for storage systems that transition a device into a low power mode when a certain usage function exceeds a specified threshold. These algorithms are difficult to use in real systems, however, because designers must painstakingly and manually tune threshold values, and even then a performance guarantee is difficult. To address these limitations, we develop three algorithms: 1) a performance guarantee technique that designers can use with any underlying energy-control algorithm 2) a performance-directed control algorithm that periodically assigns a static configuration to different devices by solving an optimization problem 3) another performance-directed control algorithm that dynamically self-tunes according to an optimal set of thresholds