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Key to understanding and optimizing complex applications is our ability to dynamically monitor executing programs with low overhead and high accuracy. Toward this end, we present HPS, a hybrid profiling support system. HPS employs a hardware/software approach to program sampling that transparently, efficiently, and dynamically samples an executing(More)
The widespread use of ubiquitous, mobile, and continuously connected computing agents has inspired software developers to change the way they test, debug, and optimize software. Users now play an active role in the software evolution cycle by dynamically providing valuable feedback about the execution of a program to developers. Software developers can use(More)
In this paper, we present VIProf, a full-system, performance sampling system capable of extracting runtime behavior across an entire software stack. Our long-term goal is to employ VIProf profiles to guide online optimization of programs and their execution environments according to the dynamically changing execution behavior and resource availability.(More)
—As data centers and end users become increasingly reliant on virtualization technology, more efficient and accurate methods of profiling such systems are needed. However, under virtualization the virtual machine and OS each try to manage the same resources independently, the underlying hardware is now multiplexed between many streams of execution, and(More)
Workload execution in virtualized machines is rapidly becoming commonplace while support for self-virtualization is already available in mass market processors. From a performance analysis and prediction standpoint, virtualization introduces new sources of uncertainty in reasoning about the factors that impact overall system performance and efficiency. This(More)
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