Towards Cloud-based Asynchronous Elasticity for Iterative HPC Applications

15th Brazilian Symposium on High Performance Computational Systems

计算机科学

Righi, Rodrigo Da Rosa^1 ; Rodrigues, Vinicius Facco^1 ; Da Costa, Cristiano André^1 ; Kreutz, Diego^2 ; Heiss, Hans-Ulrich^3

Applied Computing Graduate Program Unisinos, Av. Unisinos, 950, São Leopoldo, RS, Brazil^1

SnT, University of Luxembourg - 4, rue Alphonse Weicker, Luxembourg City

L-2721, Luxembourg^2

Technische Universität Berlin, Sekretariat EN 6, Einsteinufer 17, Berlin

D-10587, Germany^3

关键词: Cloud elasticities;    Cloud infrastructures;    Computing resource;    Dynamic resource provisioning;    High performance computing (HPC);    Message passing interface;    Numerical integrations;    Storage resources;   

Others  :  https://iopscience.iop.org/article/10.1088/1742-6596/649/1/012006/pdf
DOI  :  10.1088/1742-6596/649/1/012006

学科分类：计算机科学（综合）

来源: IOP

【 摘 要 】

Elasticity is one of the key features of cloud computing. It allows applications to dynamically scale computing and storage resources, avoiding over- and under-provisioning. In high performance computing (HPC), initiatives are normally modeled to handle bag-of-tasks or key-value applications through a load balancer and a loosely-coupled set of virtual machine (VM) instances. In the joint-field of Message Passing Interface (MPI) and tightly-coupled HPC applications, we observe the need of rewriting source codes, previous knowledge of the application and/or stop-reconfigure-and-go approaches to address cloud elasticity. Besides, there are problems related to how profit this new feature in the HPC scope, since in MPI 2.0 applications the programmers need to handle communicators by themselves, and a sudden consolidation of a VM, together with a process, can compromise the entire execution. To address these issues, we propose a PaaS-based elasticity model, named AutoElastic. It acts as a middleware that allows iterative HPC applications to take advantage of dynamic resource provisioning of cloud infrastructures without any major modification. AutoElastic provides a new concept denoted here as asynchronous elasticity, i.e., it provides a framework to allow applications to either increase or decrease their computing resources without blocking the current execution. The feasibility of AutoElastic is demonstrated through a prototype that runs a CPU-bound numerical integration application on top of the OpenNebula middleware. The results showed the saving of about 3 min at each scaling out operations, emphasizing the contribution of the new concept on contexts where seconds are precious.