System-Level Characterization of Datacenter Applications

In recent years, a number of benchmark suites have been created for the “Big Data ” domain, and a number of such applications fit the client-server paradigm. A large volume of recent literature in characterizing “Big Data ” applications have largely focused on two extremes of the characterization spectrum. On one hand, multiple studies have focused on client-side performance. These involve fine-tuning server-side parameters for an application to get the best client-side performance. On the other extreme, characterization fo-cuses on picking one set of client-side parameters and then reporting the server microarchitectural statistics under those assumptions. While the two ends of the spectrum present in-teresting results, this paper argues that they are not enough, and in some cases, undesirable, to drive system-wide archi-tectural decisions in datacenter design. This paper shows that for the purposes of designing an efficient datacenter, detailed microarchitectural characteri-zation of “Big Data ” applications is an overkill. It identi-fies four main system-level macro-architectural features and shows that these features are more representative of an ap-plication’s system level behavior. To this end, a number of datacenter applications from a variety of benchmark suites are evaluated and classified into these previously identified macro-architectural features. Based on this analysis, the paper further shows that each application class will benefit from a very different server configuration leading to a highly efficient, cost-effective datacenter

Performance analysis of NVMe SSDs and their implication on real world databases

The storage subsystem has undergone tremendous innova-tion in order to keep up with the ever-increasing demand for throughput. Non Volatile Memory Express (NVMe) based solid state devices are the latest development in this do-main, delivering unprecedented performance in terms of la-tency and peak bandwidth. NVMe drives are expected to be particularly beneficial for I/O intensive applications, with databases being one of the prominent use-cases. This paper provides the first, in-depth performance analy-sis of NVMe drives. Combining driver instrumentation with system monitoring tools, we present a breakdown of access times for I/O requests throughout the entire system. Fur-thermore, we present a detailed, quantitative analysis of all the factors contributing to the low-latency, high-throughput characteristics of NVMe drives, including the system soft-ware stack. Lastly, we characterize the performance of mul-tiple cloud databases (both relational and NoSQL) on state-of-the-art NVMe drives, and compare that to their perfor-mance on enterprise-class SATA-based SSDs. We show that NVMe-backed database applications deliver up to 8 × su-perior client-side performance over enterprise-class, SATA-based SSDs