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https://hdl.handle.net/2142/97873
Description
Title
Fine grained parallel computation in the cloud
Author(s)
Miron, Justin
Contributor(s)
Kale, Laxmikant
Issue Date
2017-05
Keyword(s)
high performance computing
cloud
replication
lock-free
concurrent queue
Date of Ingest
2017-08-22T14:15:46Z
Abstract
The divergence of priorities between high performance computing (HPC) and
cloud infrastructure has made scaling tightly coupled parallel applications in
the cloud less viable than their supercomputer counterparts. As a result,
many potential benefits -- elasticity, job virtualization, and cost-effectiveness
-- of cloud computing remain underutilized by the HPC community. Through
analysis and benchmarking of cloud compute services we see that network
overhead on cloud applications leads to scalability issues in fine grained parallel
computations. Our approaches seek to improve scalability of a parallel
runtime system and develop new runtime system methods to hide latency
within cloud scale applications. To improve scalability of communication
within a node, we developed a new concurrent lock-free queue that supports
a large memory bound and efficiently reclaims memory without a need for an
external memory reclamation scheme. Additionally, we implement a replication system
for parallel compute objects to reduce latency of requests.
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