Towards Efficient Mapping, Scheduling, and Execution of HPC Applications on Platforms in Cloud
IPDPS PhD Forum (IPDPS PhD Forum) 2013
Publication Type: Paper
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Abstract
The advantages of pay-as-you-go model, elasticity,
and the flexibility and customization offered by virtualization
make cloud computing an attractive option for meeting the needs
of some High Performance Computing (HPC) users. However,
there is a mismatch between cloud environments and HPC re-
quirements. The poor interconnect and I/O performance in cloud,
HPC-agnostic cloud schedulers, and the inherent heterogeneity
and multi-tenancy in cloud are some bottlenecks for effective
HPC in cloud.
Our primary thesis is that cloud is suitable for some HPC
applications not all applications, and for those applications,
cloud can be more cost-effective compared to typical dedicated
HPC platforms using intelligent application-to-platform mapping,
HPC-aware cloud schedulers, and cloud-aware HPC execution
and parallel runtime system. To address the challenges, and to
exploit the opportunities offered by HPC-clouds, we make Open-
Stack Nova scheduler HPC-aware and Charm++ parallel runtime
system cloud-aware. We demonstrate that our techniques result
in significant improvement in cost (up to 60%), performance (up
to 45%), and throughput (up to 32%) for HPC in cloud; helping
cloud users gain confidence in the capabilities of cloud for HPC,
and cloud providers run a more profitable business.
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