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Results for “Microprocessor Soft Errors”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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Accelerated Nuclear Radiation Effects on the Raspberry Pi 3B+ and Pi 4

Raspberry Pi™ computers running Linux and embedded benchmarks are subjected to radiation testing in the neutron beam at LANSCE. The ARM® Cortex®-A53 in the Raspberry Pi 3B+ versus ARM® Cortex®-A72 in the Raspberry Pi 4, single-core versus multi-core, and small versus large array SBU cross sections are compared. Results for the A53 and the A72 are similar. The results of one process on one of four cores and four identical processes on four cores are presented. The results of the array size show that there is more going on than just an increase in size. Linux is helpful in relating some errors that would have been classified as SEFI to an upset in a single bit.

36 MATERIALS SCIENCE↗

Single Event Effects in Highly Scaled Devices for Space Applications

This paper discusses single-event upset (SEU) in memories and microprocessors that are the "drivers" of highly scaled commercial integrated circuits. Despite the decrease in critical charge that occurs for highly scaled CMOS devices, recent test data has shown that SEU rates are actually somewhat lower for scaled devices compared to older devices with larger feature size. Hard errors, which are increasingly important for memories, are discussed along with conventional soft errors. Functional errors in memories and microprocessors are particularly significant, and tend to dominate the response of highly scaled devices from an application standpoint. Predictions for future devices are made using the Semiconductor Industry Roadmap along with recent modeling and radiation test results.

microelectronics↗

Full temperature single event upset characterization of two microprocessor technologies

Data for the 9450 I3L bipolar microprocessor and the 80C86 CMOS/epi (vintage 1985) microprocessor are presented, showing single-event soft errors for the full MIL-SPEC temperature range of -55 to 125 C. These data show for the first time that the soft-error cross sections continue to decrease with decreasing temperature at subzero temperatures. The temperature dependence of the two parts, however, is very different.

Nichols, Donald K.↗

Annual Conference on Nuclear and Space Radiation Effects, 18th, University of Washington, Seattle, WA, July 21-24, 1981, Proceedings

Single event upset phenomena are discussed, taking into account cosmic ray induced errors in IIL microprocessors and logic devices, single event upsets in NMOS microprocessors, a prediction model for bipolar RAMs in a high energy ion/proton environment, the search for neutron-induced hard errors in VLSI structures, soft errors due to protons in the radiation belt, and the use of an ion microbeam to study single event upsets in microcircuits. Basic mechanisms in materials and devices are examined, giving attention to gamma induced noise in CCD's, the annealing of MOS capacitors, an analysis of photobleaching techniques for the radiation hardening of fiber optic data links, a hardened field insulator, the simulation of radiation damage in solids, and the manufacturing of radiation resistant optical fibers. Energy deposition and dosimetry is considered along with SGEMP/IEMP, radiation effects in devices, space radiation effects and spacecraft charging, EMP/SREMP, and aspects of fabrication, testing, and hardness assurance.

Tasca, D. M.↗

Latest trends in parts SEP susceptibility from heavy ions

JPL and Aerospace have collected a third set of heavy-ion single-event phenomena (SEP) test data since their last joint IEEE publications in December 1985 and December 1987. Trends in SEP susceptibility (e.g., soft errors and latchup) for state-of-the-art parts are presented. Results of the study indicate that hard technologies and unacceptably soft technologies can be flagged. In some instances, specific tested parts can be taken as candidates for key microprocessors or memories. As always with radiation test data, specific test data for qualified flight parts is recommended for critical applications.

Nichols, Donald K.↗

Reconfigurable Processing Module

To accommodate a wide spectrum of applications and technologies, NASA s Exploration System's Missions Directorate has called for reconfigurable and modular technologies to support future missions to the moon and Mars. In response, Langley Research Center is leading a program entitled Reconfigurable Scaleable Computing (RSC) that is centered on the development of FPGA-based computing resources in a stackable form factor. This paper details the architecture and implementation of the Reconfigurable Processing Module (RPM), which is the key element of the RSC system. The RPM is an FPGA-based, space-qualified printed circuit assembly leveraging terrestrial/commercial design standards into the space applications domain. The form factor is similar to, and backwards compatible with, the PCI-104 standard utilizing only the PCI interface. The size is expanded to accommodate the required functionality while still better than 30% smaller than a 3U CompactPCI(TradeMark)card and without the overhead of the backplane. The architecture is built around two FPGA devices, one hosting PCI and memory interfaces, and another hosting mission application resources; both of which are connected with a high-speed data bus. The PCI interface FPGA provides access via the PCI bus to onboard SDRAM, flash PROM, and the application resources; both configuration management as well as runtime interaction. The reconfigurable FPGA, referred to as the Application FPGA - or simply "the application" - is a radiation-tolerant Xilinx Virtex-4 FX60 hosting custom application specific logic or soft microprocessor IP. The RPM implements various SEE mitigation techniques including TMR, EDAC, and configuration scrubbing of the reconfigurable FPGA. Prototype hardware and formal modeling techniques are used to explore the performability trade space. These models provide a novel way to calculate quality-of-service performance measures while simultaneously considering fault-related behavior due to SEE soft errors.

Somervill, Kevin↗