The RAD750/sup TM/-a radiation hardened PowerPC/sup TM/ processor for high performance spaceborne applications

Berger, Richard W.; Bayles, D.; Brown, R. D.; Doyle, S.; Kazemzadeh, A.; Knowles, K.A.; Moser, David; Rodgers, J.; Saari, Brian; Stanley, Daniel; Grant, Braden

doi:10.1109/aero.2001.931184

Cited by 30 publications

(14 citation statements)

References 2 publications

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“…An example is the elimination of all dynamic logic [116]. Because of its passive and highly charge-sensitive mode of operation, dynamic logic is highly vulnerable to SEEs, both space and terrestrial.…”

Section: B Circuit-and System-level Hardeningmentioning

confidence: 99%

Basic mechanisms and modeling of single-event upset in digital microelectronics

Dodd

Massengill

2003

IEEE Trans. Nucl. Sci.

901

427

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Physical mechanisms responsible for nondestructive single-event effects in digital microelectronics are reviewed, concentrating on silicon MOS devices and integrated circuits. A brief historical overview of single-event effects in space and terrestrial systems is given, and upset mechanisms in dynamic random access memories, static random access memories, and combinational logic are detailed. Techniques for mitigating single-event upset are described, as well as methods for predicting device and circuit single-event response using computer simulations. The impact of technology trends on single-event susceptibility and future areas of concern are explored.

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Section: B Circuit-and System-level Hardeningmentioning

confidence: 99%

Basic mechanisms and modeling of single-event upset in digital microelectronics

Dodd

Massengill

2003

IEEE Trans. Nucl. Sci.

901

427

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“…While they will be designed compatible to the rest of the standard cell library found in the RH15 150nm technology, they will be employed only for the RAD6000 and possibly BAE Systems' RAD750 TM microprocessor chip [3]. There are also several memory arrays that will be designed explicitly for the RAD6000 core, including the unified data and instruction cache, the tag memory that stores the addresses from main memory that are currently in the cache, and possibly others.…”

Section: Rad6000 Circuitrymentioning

confidence: 99%

The RAD6000MC System-on-Chip Microcontroller for Spacecraft Avionics and Instrument Control

Berger

Burcin

Hutcheson

et al. 2008

2008 IEEE Aerospace Conference

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“…However these tools are aimed at terrestrial hardware; desktop computers, mobile phones, and embedded computers. These targets are significantly more powerful than the current generation of radiation hardened space processors, LEON 3 & RAD 750 [2], [3], meaning these tools are not able to target these processors.…”

Section: Introductionmentioning

confidence: 99%

Rapid Prototyping of Deep Learning Models on Radiation Hardened CPUs

Blacker

Bridges

Hadfield

2019

2019 NASA/ESA Conference on Adaptive Hardware and Systems (AHS)

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Interest is increasing in the use of neural networks and deep-learning for on-board processing tasks in the space industry [1]. However development has lagged behind terrestrial applications for several reasons: space qualified computers have significantly less processing power than their terrestrial equivalents, reliability requirements are more stringent than the majority of applications deep-learning is being used for. The long requirements, design and qualification cycles in much of the space industry slows adoption of recent developments.GPUs are the first hardware choice for implementing neural networks on terrestrial computers, however no radiation hardened equivalent parts are currently available. Field Programmable Gate Array devices are capable of efficiently implementing neural networks and radiation hardened parts are available, however the process to deploy and validate an inference network is non-trivial and robust tools that automate the process are not available.We present an open source tool chain that can automatically deploy a trained inference network from the TensorFlow framework directly to the LEON 3, and an industrial case study of the design process used to train and optimise a deep-learning model for this processor. This does not directly change the three challenges described above however it greatly accelerates prototyping and analysis of neural network solutions, allowing these options to be more easily considered than is currently possible.Future improvements to the tools are identified along with a summary of some of the obstacles to using neural networks and potential solutions to these in the future.

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The RAD750/sup TM/-a radiation hardened PowerPC/sup TM/ processor for high performance spaceborne applications

Cited by 30 publications

References 2 publications

Basic mechanisms and modeling of single-event upset in digital microelectronics

Basic mechanisms and modeling of single-event upset in digital microelectronics

The RAD6000MC System-on-Chip Microcontroller for Spacecraft Avionics and Instrument Control

Rapid Prototyping of Deep Learning Models on Radiation Hardened CPUs

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