Benchmarking and Testing of Qualcomm Snapdragon System-on-Chip for JPL Space Applications and Missions

Towfic, Zaid J.; Ogbe, Dennis; Sauvageau, Joe; Sheldon, Douglas; Jongeling, Andre; Chien, Steve; Mirza, Faiz; Dunkel, Emily; Swope, Jason; Cretu, Vlad; Pagnotta, Chris

doi:10.1109/aero53065.2022.9843518

Cited by 10 publications

(3 citation statements)

References 10 publications

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“…Landauer and Lovelly evaluated the CPU and GPU performance of a radiation tolerant NVIDIA TK1 [45] using SHREC Space Bench. Towfic et al presented results of benchmarking at the ISS Qualcomm's Snapdragon [46] used in Mars Ingenuity Helicopter. A set of full Fig.…”

Section: Related Workmentioning

confidence: 99%

Evaluation of the Multicore Performance Capabilities of the Next Generation Flight Computers

Solé,

Wolf,

Rodriguez

et al. 2023

2023 IEEE/AIAA 42nd Digital Avionics Systems Conference (DASC)

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Multicore architectures are currently under adoption in the aerospace domain, however their software remains single-threaded. In this paper we argue about the benefits offered by homogeneous parallel processing, both in terms of performance, which is necessary for the implementation of advanced functionalities, as well as in terms of certification and in particular about mastering multicore interference.We discuss the implementation details of this programming paradigm in avionics and space real-time operating systems. We experimentally evaluate the performance benefits offered by several high-performance multicore platforms which are considered good candidates for next generation flight computers, using homogeneous parallel processing under a qualifiable realtime operating system used in the aerospace domain. Our results indicate near to linear speed-ups compared to traditional sequential processing, showing the benefits of this approach.

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Section: Related Workmentioning

confidence: 99%

Evaluation of the Multicore Performance Capabilities of the Next Generation Flight Computers

Solé,

Wolf,

Rodriguez

et al. 2023

2023 IEEE/AIAA 42nd Digital Avionics Systems Conference (DASC)

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“…Similar to our work, the implementation is open source [20], however it only supports this device. Towfic et al [18] evaluated SAR on the radiation tolerant Snapdragon multicore and GPU platform which is used on Mars Ingenuity technology.…”

Section: Related Workmentioning

confidence: 99%

Acceleration of Synthetic Aperture Radar for On-board Space Systems

Solé,

Rodriguez-Ferrandez,

Steenari

et al. 2023

2023 IEEE High Performance Extreme Computing Conference (HPEC)

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There is an increasing trend in modern space systems to move processing that until now was transmitted to ground for processing, on board the satellite. Synthetic Aperture Radar (SAR) is an example of such processing. However, such a computationally intensive task requires high performance hardware. In this paper we present the CPU and GPU acceleration of an on-board SAR processing application, part of ESA's open source benchmarking suite OBPMark.We benchmark several embedded multicore and GPU platforms which are promising candidates for future on-board systems. Our results show that both embedded multicores and especially GPUs can provide significant speedups in this type of processing, and can achieve performance level similar to the ones of high performance ground stations.

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“…Equipped with HyperSouct2 flight model, they evaluated the AI-based system in the real satellite environment, Φ-Sat1 mission. In addition, NASA and Qualcomm [12], [13] cooperate the development of onboard AI HW with Qualcomm Snapdragon and Intel Movidius Myriad X Processor for NASA jet propolusion laboratory (JPL) application. They evaluate SAR image processing with the U-Net model [14] and mars image analysis with AlexNet [15] and DeepLabv3 architecture [16].…”

Section: Related Work and Problem Description A Onboard Computing Sys...mentioning

confidence: 99%

Federated Onboard-Ground Station Computing With Weakly Supervised Cascading Pyramid Attention Network for Satellite Image Analysis

et al. 2022

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Benchmarking and Testing of Qualcomm Snapdragon System-on-Chip for JPL Space Applications and Missions

Cited by 10 publications

References 10 publications

Evaluation of the Multicore Performance Capabilities of the Next Generation Flight Computers

Evaluation of the Multicore Performance Capabilities of the Next Generation Flight Computers

Acceleration of Synthetic Aperture Radar for On-board Space Systems

Federated Onboard-Ground Station Computing With Weakly Supervised Cascading Pyramid Attention Network for Satellite Image Analysis

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