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GPU Accelerated Prognostics
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Author and Affiliation:
Gorospe, George E., Jr.(SGT, Inc., Moffett Field, CA, United States)
Daigle, Matthew J.(NIO, San Jose, CA, United States)
Sankararaman, Shankar(SGT, Inc., Moffett Field, CA, United States)
Kulkarni, Chetan S.(SGT, Inc., Moffett Field, CA, United States)
Ng, Eley(Universities Space Research Association, Moffett Field, CA, United States)
Abstract: Prognostic methods enable operators and maintainers to predict the future performance for critical systems. However, these methods can be computationally expensive and may need to be performed each time new information about the system becomes available. In light of these computational requirements, we have investigated the application of graphics processing units (GPUs) as a computational platform for real-time prognostics. Recent advances in GPU technology have reduced cost and increased the computational capability of these highly parallel processing units, making them more attractive for the deployment of prognostic software. We present a survey of model-based prognostic algorithms with considerations for leveraging the parallel architecture of the GPU and a case study of GPU-accelerated battery prognostics with computational performance results.
Publication Date: Oct 02, 2017
Document ID:
20170012211
(Acquired Dec 19, 2017)
Subject Category: COMPUTER SYSTEMS
Report/Patent Number: ARC-E-DAA-TN46389
Document Type: Conference Paper
Meeting Information: 9th Annual Conference of the Prognostics and Health Management Society 2017; 2-5 Oct. 2017; Saint Petersburg, FL; United States
Meeting Sponsor: PHM Society; New York, NY, United States
Contract/Grant/Task Num: NNA14AA60C
Financial Sponsor: NASA Ames Research Center; Moffett Field, CA, United States
Organization Source: NASA Ames Research Center; Moffett Field, CA, United States
Description: 6p; In English
Distribution Limits: Unclassified; Publicly available; Unlimited
Rights: Copyright; Public use permitted
NASA Terms: REAL TIME OPERATION; PARALLEL PROCESSING (COMPUTERS); COMPUTER SYSTEMS PERFORMANCE; ALGORITHMS; ARCHITECTURE (COMPUTERS); PERFORMANCE PREDICTION; ELECTRIC BATTERIES
Other Descriptors: GPU; PROGNOSTICS; BATTERIES
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Last Modified: December 19, 2017
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