Performance Comparison of NVIDIA accelerators with SIMD, Associative, and Multi-core Processors for Air Traffic Management
Author:
Affiliation:
1. Kent State University, Kent, Ohio
2. Hefei University of Technology, Hefei, China
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3229710.3229757
Reference13 articles.
1. Johnnie W. Baker. 2018. www.cs.kent.edu/~jbaker/PRTS-F14 Johnnie W. Baker. 2018. www.cs.kent.edu/~jbaker/PRTS-F14
2. Giorgio C. Buttazzo. 2011. Hard Real-Time Computing Systems: Predictable Scheduling Algorithms and Applications (3rd ed.). Springer. Giorgio C. Buttazzo. 2011. Hard Real-Time Computing Systems: Predictable Scheduling Algorithms and Applications (3rd ed.). Springer.
3. MathWorks. 2018. https://www.mathworks.com/help/curvefit/evaluating-goodness-of-fit.html?requestedDomain=true MathWorks. 2018. https://www.mathworks.com/help/curvefit/evaluating-goodness-of-fit.html?requestedDomain=true
4. M. Nolan. 2010. Fundamentals of Air Traffic Control. Cengage Learning. M. Nolan. 2010. Fundamentals of Air Traffic Control. Cengage Learning.
5. NVIDIA. 2018. http://developer.download.nvidia.com/compute/DevZone/docs/html/C/doc/CUDA_C_Programming_Guide.pdf NVIDIA. 2018. http://developer.download.nvidia.com/compute/DevZone/docs/html/C/doc/CUDA_C_Programming_Guide.pdf
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