Supporting storage configuration for I/O intensive workflows
Lauro Beltrão Costa, Samer Al-Kiswany, Hao Yang, Matei Ripeanu · 2014
System provisioning, resource allocation, and system configuration decisions for I/O-intensive workflow applications are complex even for expert users. Users face choices at multiple levels: allocating resources to individual sub-systems (e.g., the application layer, the storage layer) and configuring each of these optimally (e.g., replication level, chunk size, caching policies in case of storage) all having a large impact on overall application performance. This paper presents our progress on addressing the problem of supporting these provisioning, allocation and configuration decisions for workflow applications. To enable selecting a good choice in a reasonable time, we propose an approach that accelerates the exploration of the configuration space based on a low-cost performance predictor that estimates total execution time of a workflow application in a given setup. Our evaluation shows that: (i) the predictor is effective in identifying the desired system configuration, (ii) it can scale to model a workflow application run on an entire cluster, while (iii) using over 2000x less resources (machines x time) than running the actual application.