Are ARM Cloud Servers Ready for Database Workloads? an Experimental Study

被引:1
作者
Loghin, Dumitrel [1 ]
机构
[1] Natl Univ Singapore, Sch Comp, Singapore 119077, Singapore
基金
新加坡国家研究基金会;
关键词
Cloud computing; Program processors; Servers; Reduced instruction set computing; Computer architecture; Software; Benchmark testing; Performance; cost; benchmarking; cloud computing; ARM; database; data management;
D O I
10.1109/TCC.2024.3393895
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Almost all major cloud providers offer virtual machines running on servers with 64-bit ARM CPUs. For example, Amazon Web Services (AWS) designed custom ARM-based CPUs named Graviton2 and Graviton3. Other cloud providers, such as Microsoft Azure and Google Cloud Platform (GCP), employ servers with Ampere Altra CPUs. In this context, we conduct a comprehensive experimental study covering in-memory key-value stores, relational databases, enterprise blockchains, and Machine Learning inference. We cover all the available types of ARM cloud processors, including Graviton2 (AWS), Graviton3 (AWS), Ampere Altra (Azure and GCP), Yitian 710 (Alibaba Cloud), and Kunpeng 920 (Huawei Cloud). Our analysis shows that Yitian and Graviton3 are serious competitors for servers with Intel Xeon CPUs, achieving similar or better results with in-memory workloads. However, the performance of OLAP, ML inference, and blockchain on ARM-based servers is below that of Xeon. The reasons are mainly threefold 1) un-optimized software, 2) lower clock frequency, and 3) lower performance at core level. Surprisingly, ARM servers spend 2X more time in Linux kernel system calls compared to Xeon servers. Nonetheless, ARM-based servers show great potential. Given their lower cloud computing price, ARM servers could be the ideal choice when the performance is not critical.
引用
收藏
页码:818 / 829
页数:12
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