SCHEDULE: NOV 15-20, 2015

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.

ENTIRE WEEK SUNDAY MONDAY TUESDAY WEDNESDAY THURSDAY FRIDAY

Parallel Execution of Workflows Driven by a Distributed Database Management System

SESSION: Regular & ACM Student Research Competition Poster Reception

EVENT TYPE: Posters, Receptions, ACM Student Research Competition

EVENT TAG(S): HPC Beginner Friendly, Regular Poster

TIME: 5:15PM - 7:00PM

SESSION CHAIR(S): Michela Becchi, Manish Parashar, Dorian C. Arnold

AUTHOR(S):Renan Souza, Vítor Silva, Daniel de Oliveira, Patrick Valduriez, Alexandre A. B. Lima, Marta Mattoso

ROOM:Level 4 - Lobby

ABSTRACT:

Scientific Workflow Management Systems (SWfMS) that execute large-scale simulations need to manage many task computing in high performance environments. With the scale of tasks and processing cores to be managed, SWfMS require efficient distributed data structures to manage data related to scheduling, data movement and provenance data gathering. Although related systems store these data in multiple log files, some existing approaches store them using a Database Management System (DBMS) at runtime, which provides powerful analytical capabilities, such as execution monitoring, anticipated result analyses, and user steering. Despite these advantages, approaches relying on a centralized DBMS introduce a point of contention, jeopardizing performance in large-scale executions. In this paper, we propose an architecture relying on a distributed DBMS to both manage the parallel execution of tasks and store those data at runtime. Our experiments show an efficiency of over 80% on 1,000 cores without abdicating the analytical capabilities at runtime.

Chair/Author Details:

Michela Becchi, Manish Parashar, Dorian C. Arnold (Chair) - University of Missouri|Rutgers University|University of New Mexico|

Renan Souza - Federal University of Rio de Janeiro

Vítor Silva - Federal University of Rio de Janeiro

Daniel de Oliveira - Fluminense Federal University

Patrick Valduriez - French Institute for Research in Computer Science and Automation