Guest Speaker: Anshul Gandhi
480 Dreese Labs
2015 Neil Ave, Columbus, Ohio 43210
Elastic Memory Caches
Memory caches, such as Memcached, are a critical component of online applications as they help maintain low latencies by alleviating the load at the database. However, memory caches are expensive, both in terms of power and operating costs. It is thus important to dynamically scale such caches in response to workload variations. Unfortunately, stateful systems, such as Memcached, are not elastic in nature. The performance loss that follows a scaling action can severely impact latencies and lead to SLO violations.
In this talk, I will present ElMem, an elastic Memcached system that we designed to mitigate post-scaling performance loss by proactively migrating hot data between nodes. The key enabler of our work is an efficient algorithm, FuseCache, that migrates the optimal amount of hot data to minimize performance loss. Our experimental results on OpenStack, across several workload traces, show that ElMem elastically scales Memcached while reducing the postscaling performance degradation by about 90%. Our ElMem work received the Best Student Paper award at ICDCS 2018.
Bio: Anshul Gandhi is an Assistant Professor in the Computer Science Department at Stony Brook University. He received his Ph.D. from Carnegie Mellon University in 2013 and then spent an year as a post-doc at the IBM T. J. Watson Research Center. His current research focuses on performance modeling in distributed systems, and is funded by an NSF Career award, an IBM Faculty award, a Google Research award, and an Azure Research award.
Host: Chris Stewart