Symbiotic scheduling for shared caches in multi-core systems using memory footprint signature

As the trend of more cores sharing common resources on a single die and more systems crammed into enterprise computing space con-tinue, optimizing the economies of scale for a given compute capacity is becoming more critical. One major challenge in performance scal-ability is the growing L2 cache contention caused by multiple contexts running on a multi-core processor either natively or under a virtual machine environment. Currently, an OS, at best, relies on history-based affinity information to dispatch a process or thread onto a par-ticular processor core. Unfortunately, this simple method can easily lead to destructive performance effect due to conflicts in common re-sources, thereby slowing down all processes. To ameliorate the allocation/management policy of a shared cache on a multi-core, in this paper, we propose Bloom filter signatures, a low-complexity architectural support to allow an OS or a Virtual Machine Monitor to infer cache footprint characteristics and inter-ference of applications, and then perform job scheduling based on symbiosis. Our scheme integrates hardware-level counting Bloom fil-ters in caches to efficiently summarize cache usage behavior on a per-core, per-process or per-VM basis. We then proposed and stud-ied three resource allocation algorithms to determine the optimal process-to-core mapping to minimize interference in the L2. We ex-ecuted applications using allocation generated by our new process-to-core mapping algorithms on an Intel Core 2 Duo machine and showed an averaged 22 % (up to 54%) improvement when applica-tions run natively, and an averaged 9.5 % improvement (up to 26%) when running inside VMs