SC is the International Conference for
High Performance Computing, Networking,
Storage and Analysis



SCHEDULE: NOV 12-18, 2011

When viewing the Technical Program schedule, on the far righthand side is a column labeled "PLANNER." Use this planner to build your own schedule. Once you select an event and want to add it to your personal schedule, just click on the calendar icon of your choice (outlook calendar, ical calendar or google calendar) and that event will be stored there. As you select events in this manner, you will have your own schedule to guide you through the week.

You can also create your personal schedule on the SC11 app (Boopsie) on your smartphone. Simply select a session you want to attend and "add" it to your plan. Continue in this manner until you have created your own personal schedule. All your events will appear under "My Event Planner" on your smartphone.

Virtual I/O Caching: Effective Storage Cache Management for Concurrent Workloads

SESSION: Storage and Memory

EVENT TYPE: Paper

TIME: 10:30AM - 11:00AM

AUTHOR(S):Michael R. Frasca, Ramya Prabhakar, Padma Raghavan, Mahmut Kandemir

ROOM:TCC 305

ABSTRACT:
A leading cause of reduced or unpredictable application performance in distributed systems is contention at the storage layer, where resources are multiplexed among many concurrent data intensive workloads. We target the shared storage cache, used to alleviate disk I/O bottlenecks, and propose a new caching paradigm to both improve performance and reduce memory requirements for HPC storage systems. We present the virtual I/O cache, a dynamic scheme to manage a limited storage cache resource. Application behavior and the corresponding performance of a chosen replacement policy are observed at run time, and a mechanism is designed to avoid suboptimal caching. We further use the virtual I/O cache to isolate concurrent workloads and globally manage physical resource allocation towards system level performance objectives. We evaluate our scheme using twenty I/O intensive applications and benchmarks. Average hit rate gains over 17% were observed for isolated workloads, and 23% for our largest concurrent workload.

Chair/Author Details:

Michael R. Frasca - Pennsylvania State University

Ramya Prabhakar - Pennsylvania State University

Padma Raghavan - Pennsylvania State University

Mahmut Kandemir - Pennsylvania State University

Add to iCal  Click here to download .ics calendar file

Add to Outlook  Click here to download .vcs calendar file

Add to Google Calendarss  Click here to add event to your Google Calendar

The full paper can be found in the ACM Digital Library

   Sponsors    ACM    IEEE