4.7 Article

Democratizing digital design and manufacturing using high performance cloud computing: Performance evaluation and benchmarking

Journal

JOURNAL OF MANUFACTURING SYSTEMS
Volume 43, Issue -, Pages 316-326

Publisher

ELSEVIER SCI LTD
DOI: 10.1016/j.jmsy.2016.09.005

Keywords

Digital design and manufacturing; Cloud computing; High performance computing; Performance evaluation; Benchmark; Finite element analysis

Funding

  1. NSF [IIP-1238335]

Ask authors/readers for more resources

Cloud computing is an innovative computing paradigm that can bridge the gap between increasing computing demands in computationally intensive tasks for digital design and manufacturing applications and limited resources, scalability, flexibility, and agility in traditional computing paradigms. In light of the benefits of cloud computing, cloud-based high performance computing (HPC) has the potential to enable users to not only accelerate computationally expensive tasks, but also to reduce costs by utilizing on-demand, ubiquitous, seamless, and user-friendly access to remote engineering application packages as well as remote HPC resources. However, due to uncertainty about computing performance on the cloud, many manufacturers find it challenging to justify and adopt Cloud-Based Design and Manufacturing (CBDM). Therefore, the objective of this research is to evaluate the performance of solving a large-scale engineering problem using finite element analysis on several public HPC clouds as well as introduce a new workflow for CBDM. A set of experiments is conducted to compare the performance of the public HPC clouds with that of a standard workstation and a dedicated in-house supercomputer. The performance metrics include elapsed time, speedup, scalability, and stability. Experimental results have shown that the Azure Cloud with 32 cores and the Nimbix Cloud with 16 nodes speed up the finite element analysis over a workstation with 8 cores by more than seven-fold and eight-fold. A dedicated in-house supercomputer speeds up the finite element analysis over cloud computing by approximately two-fold because of better I/O performance and larger memory. In addition, considerable variations of elapsed time for solving the finite element model with multiple nodes in the cloud were observed due to resource sharing in cloud computing. (C) 2016 The Society of Manufacturing Engineers. Published by Elsevier Ltd. All rights reserved.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.7
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available