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.
ABSTRACT: MapReduce has been very successful in implementing large-scale data-intensive applications. Because of its simple programming model, MapReduce has also begun being utilized as a programming tool for more general distributed and parallel HPC applications.
However, its applicability is often limited due to relatively inefficient runtime performance and hence insufficient support for flexible workflows. In particular, the performance problem is not negligible in iterative MapReduce applications.
We implemented new MapReduce framework SSS based on distributed key-value store, that supports flexible workflows. Mappers and reducers read key-values only from its local storage enjoying high throughput and low latency.
We evaluated SSS comparing with Hadoop using synthetic benchmark and real application. The result showed that SSS is significantly faster than Hadoop, especially for shuffle-intensive jobs and iterative jobs.
Bernd Mohr (Chair) - Juelich Supercomputing Centre
Hidemoto Nakada - National Institute of Advanced Industrial Science & Technology
Hirotaka Ogawa - National Institute of Advanced Industrial Science & Technology
Tomohiro Kudoh - National Institute of Advanced Industrial Science & Technology