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Comparative Analysis of Space-Grade Processors

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Comparative Analysis of Space-Grade Processors COMPARATIVE ANALYSIS OF SPACE-GRADE PROCESSORS By TYLER MICHAEL LOVELLY A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY UNIVERSITY OF FLORIDA 2017 © 2017 Tyler Michael Lovelly To my country ACKNOWLEDGMENTS This work was supported in part by the Industry/University Cooperative Research Center Program of the National Science Foundation under grant nos. IIP-1161022 and CNS-1738783, by the industry and government members of the NSF Center for High- Performance Reconfigurable Computing and the NSF Center for Space, High- Performance, and Resilient Computing, by the University of Southern California Information Sciences Institute for remote access to their systems, and by Xilinx and Microsemi for provided hardware and software. 4 TABLE OF CONTENTS page ACKNOWLEDGMENTS .................................................................................................. 4 LIST OF TABLES ............................................................................................................ 7 LIST OF FIGURES .......................................................................................................... 8 ABSTRACT ..................................................................................................................... 9 CHAPTER 1 INTRODUCTION .................................................................................................... 11 2 BACKGROUND AND RELATED RESEARCH ....................................................... 14 Metrics and Benchmarking Analysis ....................................................................... 15 Computational Dwarfs and Taxonomies ................................................................. 18 3 METRICS AND BENCHMARKING METHODOLOGIES ........................................ 20 Metrics Calculations for Fixed-Logic and Reconfigurable-Logic Processors........... 20 Benchmark Development, Optimization, and Testing for CPUs and FPGAs .......... 24 4 METRICS EXPERIMENTS, RESULTS, AND ANALYSIS ....................................... 27 Metrics Comparisons of Space-Grade CPUs, DSPs, and FPGAs .......................... 27 Performance Variations in Space-Grade CPUs, DSPs, and FPGAs ...................... 29 Overheads Incurred from Radiation Hardening of CPUs, DSPs, and FPGAs ......... 36 Projected Future Space-Grade CPUs, DSPs, FPGAs, and GPUs .......................... 39 5 BENCHMARKING EXPERIMENTS, RESULTS, AND ANALYSIS ......................... 44 Space-Computing Taxonomy and Benchmarks ...................................................... 44 Performance Analysis of Space-Grade CPUs ........................................................ 48 Performance Analysis of Space-Grade FPGAs ...................................................... 51 Benchmarking Comparisons of Space-Grade CPUs and FPGAs ........................... 53 Expanded Analysis of Space-Grade CPUs ............................................................. 55 6 CONCLUSIONS ..................................................................................................... 58 APPENDIX A METRICS DATA ..................................................................................................... 62 B BENCHMARKING DATA ........................................................................................ 65 5 LIST OF REFERENCES ............................................................................................... 68 BIOGRAPHICAL SKETCH ............................................................................................ 84 6 LIST OF TABLES Table page 2-1 UCB computational dwarfs. ................................................................................ 18 5-1 Space-computing taxonomy. .............................................................................. 45 5-2 Space-computing benchmarks. .......................................................................... 47 A-1 Metrics data for space-grade CPUs, DSPs, and FPGAs. ................................... 62 A-2 Performance variations in space-grade CPUs, DSPs, and FPGAs. ................... 62 A-3 Metrics data for closest COTS counterparts to space-grade CPUs, DSPs, and FPGAs. ........................................................................................................ 62 A-4 Radiation-hardening outcomes for space-grade CPUs, DSPs, and FPGAs. ...... 63 A-5 Percentages achieved by space-grade CPUs, DSPs, and FPGAs after radiation hardening. ............................................................................................ 63 A-6 Metrics data for low-power COTS CPUs, DSPs, FPGAs, and GPUs. ................ 64 A-7 Metrics data for projected future space-grade CPUs, DSPs, FPGAs, and GPUs (worst case). ............................................................................................ 64 A-8 Metrics data for projected future space-grade CPUs, DSPs, FPGAs, and GPUs (best case). .............................................................................................. 64 B-1 Parallelization data for space-grade CPUs. ........................................................ 65 B-2 Resource usage data for space-grade FPGAs. .................................................. 66 B-3 Benchmarking data for matrix multiplication on space-grade CPUs and FPGAs. ............................................................................................................... 66 B-4 Benchmarking data for Kepler’s equation on space-grade CPUs and FPGAs. .. 66 B-5 Performance data for additional benchmarks on space-grade CPUs. ................ 67 7 LIST OF FIGURES Figure page 4-1 Metrics data for space-grade CPUs, DSPs, and FPGAs. ................................... 28 4-2 Operations mixes of intensive computations. ..................................................... 30 4-3 Performance variations in space-grade CPUs, DSPs, and FPGAs. ................... 31 4-4 Metrics data for closest COTS counterparts to space-grade CPUs, DSPs, and FPGAs. ........................................................................................................ 37 4-5 Percentages achieved by space-grade CPUs, DSPs, and FPGAs after radiation hardening. ............................................................................................ 38 4-6 Metrics data for low-power COTS CPUs, DSPs, FPGAs, and GPUs. ................ 40 4-7 Metrics data for current and projected future space-grade CPUs, DSPs, FPGAs, and GPUs. ............................................................................................ 42 5-1 Parallelization data for matrix multiplication on space-grade CPUs. ................... 49 5-2 Parallelization data for Kepler’s equation on space-grade CPUs. ...................... 50 5-3 Resource usage data for matrix multiplication on space-grade FPGAs. ............. 51 5-4 Resource usage data for Kepler’s equation on space-grade FPGAs. ................ 52 5-5 Benchmarking data for matrix multiplication on space-grade CPUs and FPGAs. ............................................................................................................... 54 5-6 Benchmarking data for Kepler’s equation on space-grade CPUs and FPGAs. .. 54 5-7 Performance data for additional benchmarks on space-grade CPUs. ................ 56 8 Abstract of Dissertation Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy COMPARATIVE ANALYSIS OF SPACE-GRADE PROCESSORS By Tyler Michael Lovelly December 2017 Chair: Alan Dale George Major: Electrical and Computer Engineering Onboard computing demands for space missions are continually increasing due to the need for real-time sensor and autonomous processing combined with limited communication bandwidth to ground stations. However, creating space-grade processors that can operate reliably in environments that are highly susceptible to radiation hazards is a lengthy, complex, and costly process, resulting in limited processor options for space missions. Therefore, research is conducted into current, upcoming, and potential future space-grade processors to provide critical insights for progressively more advanced architectures that can better meet the increasing demands for onboard computing. Metrics and benchmarking data are generated and analyzed for various processors in terms of performance, power efficiency, memory bandwidth, and input/output bandwidth. Metrics are used to measure and compare the theoretical capabilities of a broad range of processors. Results demonstrate how onboard computing capabilities are increasing due to processors with architectures that support high levels of parallelism in terms of computational units, internal memories, and input/output resources; and how performance varies between applications, depending on the intensive computations 9 used. Furthermore, the overheads incurred by radiation hardening are quantified and used to analyze low-power commercial processors for potential use as future space- grade processors. Once the top-performing processors are identified using metrics, benchmarking is used to measure and compare their realizable capabilities. Computational dwarfs are established and a taxonomy is formulated to characterize the space-computing domain and identify computations for benchmark development, optimization, and testing. Results demonstrate how to optimize for the architectures of space-grade processors and how they compare to one another
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