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

SCHEDULE: NOV 13-19, 2010

JAWS: Job-Aware Workload Scheduling for the Exploration of Turbulence Simulations

SESSION: Runtime Resource Allocation and Scheduling


TIME: 3:30PM - 4:00PM


AUTHOR(S):Xiaodan Wang, Eric Perlman, Randal Burns, Tanu Malik, Tamas Budavari, Charles Meneveau, Alexander Szalay


We present JAWS, a job-aware, data-driven batch scheduler that improves query throughput for data-intensive scientific database clusters. As datasets reach petabyte-scale, workloads that scan through vast amounts of data to extract features are gaining importance in the sciences. However, acute performance bottlenecks result when multiple queries execute simultaneously and compete for I/O resources. Our solution, JAWS, divides queries into I/O-friendly sub-queries for scheduling. It then identifies overlapping data requirements within the workload and executes sub-queries in batches to maximize data sharing and reduce redundant I/O. JAWS extends our previous work by supporting workflows in which queries exhibit data dependencies, exploiting workload knowledge to coordinate caching decisions, and combating starvation through adaptive and incremental trade-offs between query throughput and response time. Instrumenting JAWS in the Turbulence Database Cluster yields nearly three-fold improvement in query throughput when contention in the workload is high.

Chair/Author Details:

Joel Saltz (Chair) - Emory University

Xiaodan Wang - Johns Hopkins University

Eric Perlman - Johns Hopkins University

Randal Burns - Johns Hopkins University

Tanu Malik - Purdue University

Tamas Budavari - Johns Hopkins University

Charles Meneveau - Johns Hopkins University

Alexander Szalay - Johns Hopkins University

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The full paper can be found in the ACM Digital Library and IEEE Computer Society

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