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As multicore processors with expanding core counts continue to dominate the server market, the overall utilization of the class of datacenters known as <i>warehouse scale computers</i> (WSCs) depends heavily on colocation of multiple workloads on each server to take advantage of the computational power provided by modern processors. However, many of the(More)
—For higher processing and computing power, chip multiprocessors (CMPs) have become the new mainstream architecture. This shift to CMPs has created many challenges for fully utilizing the power of multiple execution cores. One of these challenges is managing contention for shared resources. Most of the recent research address contention for shared resources(More)
—With the shift to chip multiprocessors, managing shared resources has become a critical issue in realizing their full potential. Previous research has shown that thread mapping is a powerful tool for resource management. However, the difficulty of simultaneously managing multiple hardware resources and the varying nature of the workloads have impeded the(More)
To utilize the full potential of modern chip multiprocessors and obtain scalable performance improvements, it is critical to mitigate resource contention created by multithreaded workloads. In this article, we describe ReSense, the first runtime system that uses application characteristics to dynamically map multithreaded applications from dynamic(More)
With the shift to many-core chip multiprocessors (CMPs), a critical issue is how to effectively coordinate and manage the execution of applications and hardware resources to overcome performance, power consumption, and reliability challenges stemming from hardware and application variations inherent in this new computing environment. Effective resource and(More)
Memory bandwidth severely limits the scalability and performance of today's multi-core systems. Because of this limitation , many studies that focused on improving multi-core scalability rely on bandwidth usage predictions to achieve the best results. However, existing bandwidth prediction models have low accuracy, causing these studies to have inaccurate(More)
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