Weighted Locality Sensitive Scheduling for Mitigating Noise on Multicore Clusters
IEEE International Conference on High Performance Computing (HiPC) 2011
Publication Type: Paper
Repository URL: papers/201101_NoiseLdb
Abstract
Recent studies have shown that noise can be a significant problem as we scale
to a large number of processors. One solution for mitigating noise is to turn
off certain operating system services on the machine. However, this is
typically infeasible because full-scale OS services may be needed for some
applications. Furthermore, it is not a choice that an end user can make. Thus,
we need an application-level solution. Building upon previous work which
demonstrated the utility of within-node light-weight load balancing, we provide
a more in-depth study of this technique, and provide insight based on
experimentation for two different machines with very different noise
signatures. Through careful enumeration of the search space of scheduler
parameters, we allow our light-weight load balancer to be tunable as well as
adaptive for a specific application running on a specific architecture. By
doing this, we show how we can enable running scientific applications on very
large number of processors.
TextRef
Vivek Kale, Abhinav Bhatele and William D. Gropp, Weighted locality sensitive scheduling for mitigating noise on multicore clusters, In Proceedings of 18th annual IEEE International Conference on High Performance Computing (HiPC), 2011.
People
- Vivek Kale
- Abhinav Bhatele
- William Gropp
Research Areas