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Symbiotic Scheduling for Shared Caches in Multi-core Systems Using Memory Footprint Signature

机译:使用内存足迹签名的多核系统中共享缓存的共生调度

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As the trend of more cores sharing common resources on a single die and more systems crammed into enterprise computing space continue, optimizing the economies of scale for a given compute capacity is becoming more critical. One major challenge in performance scalability 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 particular processor core. Unfortunately, this simple method can easily lead to destructive performance effect due to conflicts in common resources, 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 interference of applications, and then perform job scheduling based on symbiosis. Our scheme integrates hardware-level counting Bloom filters in caches to efficiently summarize cache usage behavior on a per-core, per-process or per-VM basis. We then proposed and studied three resource allocation algorithms to determine the optimal process-to-core mapping to minimize interference in the L2. We executed 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 applications run natively, and an averaged 9.5% improvement (up to 26%)when running inside VMs.
机译:随着越来越多的内核在单个裸片上共享公共资源的趋势以及越来越多的系统挤入企业计算空间的趋势,针对给定计算能力优化规模经济变得越来越关键。性能可伸缩性中的一个主要挑战是,本机或虚拟机环境下,在多核处理器上运行的多个上下文导致的二级缓存争用不断增长。当前,OS充其量只能依靠基于历史的亲和力信息来将进程或线程分派到特定的处理器内核上。不幸的是,由于公共资源之间的冲突,这种简单的方法很容易导致破坏性的性能影响,从而减慢了所有过程的速度。为了改善多核上共享缓存的分配/管理策略,在本文中,我们提出了布隆过滤器签名,这是一种低复杂性的架构支持,可允许OS或虚拟机监视器推断缓存占用空间特征和干扰。应用程序,然后根据共生关系执行作业调度。我们的方案将硬件级别的计数布隆过滤器集成到缓存中,以基于每个内核,每个进程或每个VM高效地总结缓存使用行为。然后,我们提出并研究了三种资源分配算法,以确定最佳的进程到核心的映射,以最大程度地减少L2中的干扰。我们在Intel Core 2 Duo机器上使用由新过程生成的分配给核心映射算法的分配执行应用程序,当应用程序在本机运行时,平均改善了22%(最高54%),平均改善了9.5%(最高26)。 %)在虚拟机内部运行时。

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