CLOUD COMPUTING FOR THE AUTOMATED ASSIGNMENT OF BROADBAND ROTATIONAL SPECTRA: PORTING AUTOFIT TO AMAZON EC2
Olinger, Aaron C
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https://hdl.handle.net/2142/79275
Description
Title
CLOUD COMPUTING FOR THE AUTOMATED ASSIGNMENT OF BROADBAND ROTATIONAL SPECTRA: PORTING AUTOFIT TO AMAZON EC2
Author(s)
Olinger, Aaron C
Contributor(s)
Shipman, Steven
Issue Date
23-Jun-15
Keyword(s)
Instrument/Technique Demonstration
Abstract
Recent developments in instrumentation have made it possible to collect broadband rotational spectra far faster than those spectra can be assigned. As such, we have been working to develop automated assignment algorithms so that the analysis can catch up with the data acquisition. The AUTOFIT programfootnote{Seifert, N.A., Finneran, I.A., Perez, C., Zaleski, D.P., Neill, J.L., Steber, A.L., Suenram, R.D., Lesarri, A., Shipman, S.T., Pate, B.H., J. Mol. Spec., in press} has made strides in this direction, but it is still quite slow on spectra with high line densities, such as those collected near room temperature. Given that the AUTOFIT algorithm is highly parallelizable, we have used Amazon's EC2 webservice to run a modified version of AUTOFIT simultaneously across a large number of cores, allowing us to obtain results in a fraction of the time normally required by a typical desktop computer. In this talk, we will describe how AUTOFIT was modified to run on EC2 and present some benchmark results.
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