USENIX Technical Program - Abstract - USENIX Annual
Conference, General Session - June 2000
Dynamic Function Placement for Data-Intensive Cluster Computing
Khalil Amiri, David Petrou, Gregory R. Granger, and Garth A. Gibson,
Carnegie Mellon University
Abstract
Optimally partitioning application and filesystem functionality within a
cluster of clients and servers is a difficult problem due to dynamic
variations in application behavior resource availability, and workload
mixes. This paper presents ABACUS, a run-time system that monitors and
dynamically changes function placement for applications that manipulate
large data sets. Several examples of data-intensive workloads are used
to show the importance of proper function placement and its dependence
on dynamic run-time system behavior, including both long-term variation
(e.g., filter selectivity) and short-term variation (e.g., multi-phase
applications and inter-application resource contention). Our
experiments with ABACUS indicate that it is possible to adapt in all of
these situations and that the adaptation converges most quickly in those
cases where the performance impact is most significant
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