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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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At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
NASA NTRS2010

Impact of Spacecraft Shielding on Direct Ionization Soft Error Rates for Sub-130 nm Technologies

We use ray tracing software to model various levels of spacecraft shielding complexity and energy deposition pulse height analysis to study how it affects the direct ionization soft error rate of microelectronic components in space. The analysis incorporates the galactic cosmic ray background, trapped proton, and solar heavy ion environments as well as the October 1989 and July 2000 solar particle events.

Pellish, Jonathan A.↗
NASA NTRS1990

Asymmetric Memory Circuit Would Resist Soft Errors

Some nonlinear error-correcting codes more efficient in presence of asymmetry. Combination of circuit-design and coding concepts expected to make integrated-circuit random-access memories more resistant to "soft" errors (temporary bit errors, also called "single-event upsets" due to ionizing radiation). Integrated circuit of new type made deliberately more susceptible to one kind of bit error than to other, and associated error-correcting code adapted to exploit this asymmetry in error probabilities.

Buehler, Martin G.↗
DOE OSTI2017

Characterizing Temperature, Power, and Soft-Error Behaviors in Data Center Systems: Insights, Challenges, and Opportunities

GPUs have become part of the mainstream high performance computing facilities that increasingly require more computational power to simulate physical phenomena quickly and accurately. However, GPU nodes also consume significantly more power than traditional CPU nodes, and high power consumption introduces new system operation challenges, including increased temperature, power/cooling cost, and lower system reliability. This paper explores how power consumption and temperature characteristics affect reliability, provides insights into what are the implications of such understanding, and how to exploit these insights toward predicting GPU errors using neural networks.

Nie, Bin↗
NASA NTRS1985

Modeling "Soft" Errors in Bipolar Integrated Circuits

Mathematical models represent single-event upset in bipolar memory chips. Physics of single-event upset in integrated circuits discussed in theoretical paper. Pair of companion reports present mathematical models to predict critical charges for producing single-event upset in bipolar randomaccess memory (RAM) chips.

Zoutendyk, J.↗
NASA NTRS1984

Bipolar junction transistor models for circuit simulation of cosmic-ray-induced soft errors

This paper examines bipolar junction transistor models suitable for calculating the effects of large excursions of some of the variables determining the operation of a transistor. Both the Ebers-Moll and Gummel-Poon models are studied, and the junction and diffusion capacitances are evaluated on the basis of the latter model. The most interesting result of this analysis is that a bipolar junction transistor when struck by a cosmic particle may cause a single event upset in an electronic circuit if the transistor is operated at a low forward base-emitter bias.

Benumof, R.↗
NASA NTRS1991

Asymmetric soft-error resistant memory

A memory system is provided, of the type that includes an error-correcting circuit that detects and corrects, that more efficiently utilizes the capacity of a memory formed of groups of binary cells whose states can be inadvertently switched by ionizing radiation. Each memory cell has an asymmetric geometry, so that ionizing radiation causes a significantly greater probability of errors in one state than in the opposite state (e.g., an erroneous switch from '1' to '0' is far more likely than a switch from '0' to'1'. An asymmetric error correcting coding circuit can be used with the asymmetric memory cells, which requires fewer bits than an efficient symmetric error correcting code.

Buehler, Martin G.↗
DOE OSTI2021

Determining diagnostic coverage for memory using redundant execution

Memory, used by a computer to store data, is generally prone to faults, including permanent faults (i.e. relating to a lifetime of the memory hardware), and also transient faults (i.e. relating to some external cause) which are otherwise known as soft errors. Since soft errors can change the state of the data in the memory and thus cause errors in applications reading and processing the data, there is a desire to characterize the degree of vulnerability of the memory to soft errors. In particular, once the vulnerability for a particular memory to soft errors has been characterized, cost/reliability trade-offs can be determined, or soft error detection mechanisms (e.g. parity) may be selectively employed for the memory. In some cases, memory faults can be diagnosed by redundant execution and a diagnostic coverage may be determined.

Bramley, Richard Gavin↗
DOE OSTI2020

FPDetect: Efficient Reasoning About Stencil Programs Using Selective Direct Evaluation

We present FPDetect, a low-overhead approach for detecting logical errors and soft errors affecting stencil computations without generating false positives. We develop an offline analysis that tightly estimates the number of floating-point bits preserved across stencil applications. This estimate rigorously bounds the values expected in the data space of the computation. Violations of this bound can be attributed with certainty to errors. FPDetect helps synthesize error detectors customized for user-specified levels of accuracy and coverage. FPDetect also enables overhead reduction techniques based on deploying these detectors coarsely in space and time. Experimental evaluations demonstrate the practicality of our approach.

97 MATHEMATICS AND COMPUTING↗