Search NASA⌕ Search

SEARCH · Search NASA

Results for “Long memory”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

NLR HPC Eagle Jobs Data and Additional Energy Metrics

Overview: Anonymized job-level records from the Eagle high-performance computing (HPC) system at the National Laboratory of the Rockies (NLR). Each record represents a Slurm batch job with scheduling metadata, resource requests, resource utilization, CPU/GPU energy consumption, and efficiency metrics. Sensitive fields (user, account, job name) are replaced with cryptographic hashes. System & Timeframe: Eagle was a 2,000-node, 8-petaflop system operated at NLR from 2019–2024. Data covers the full operational lifetime of the system. Slurm data was processed nightly; timestamps are in Mountain Time. Funding provided by the U.S. Department of Energy, EERE. Files: esif.hpc.eagle.job-anon.zip — Core anonymized job records (Hive-partitioned Parquet) esif.hpc.eagle.job-anon-energy-metrics.zip — Same records with additional iLO and Ganglia energy metrics datacard.md — Full dataset documentation ~13.8 million rows, 62 variables. Readable with PyArrow, pandas, DuckDB, Apache Spark, or any Parquet-compatible tool. Data Collection: Jobs collected via sacct through a pipeline: Eagle Jobs API → Redpanda → StreamSets → HPCMON API → PostgreSQL. Node-level power from iLO (HP Integrated Lights-Out); GPU power from Ganglia monitoring, joined to jobs via node lists and time ranges. Preprocessing: Anonymization of name, user, and account fields via cryptographic hashing Derived columns: queue_wait, cpu_eff, max_mem_eff Simplified job state mapping (e.g., "CANCELLED BY 12345" → "CANCELLED") QoS accounting rules (buy-in, standby, or Slurm QoS value) CPU energy estimated from TDP (200W, Intel Xeon Gold 6154, 18 cores) Timezone-aware columns (_tz) sourced from LEX accounting database to correctly handle DST transitions Key Variables: Scheduling: job_id, partition, state_simple, submit_time_tz, start_time_tz, end_time_tz, queue_waitResources: nodes_req/used, processors_req/used, memory_req, wallclock_req/used, gpus_requested Efficiency: cpu_eff, max_mem_eff Energy: cpu_energy_tdp_estimated_max/used_watt_hours, node_energy_total_watt_hours (iLO), gpu0/1_energy_total_watt_hours (Ganglia) Partitions: bigmem, bigmem-8600, bigscratch, csc, dav, ddn, debug, gpu, haswell, long, mono, short, standard Job States: CANCELLED, COMPLETED, FAILED, NODE_FAIL, OUT_OF_MEMORY, PENDING, RUNNING, TIMEOUT QoS Levels: Unknown, normal, buy-in, debug, penalty, high, standby Important Notes: Non-_tz timestamp columns may be off by one hour across DST boundaries; use _tz columns for time difference calculations Energy fields are null for jobs without monitoring coverage Job step records and raw Slurm JSONB fields are excluded from this extract Do not attempt to re-identify individuals from hashed fields

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1984

Time scales for the decay of induced large-scale magnetic fields in the Venus ionosphere

Observations made with the aid of a magnetometer on the Pioneer Venus Orbiter have shown large-scale horizontal magnetic fields in the dayside ionosphere of Venus. According to Cloutier and Daniell (1981), the observed magnetic structures may be quasi-steady features produced by an ionospheric current system driven by solar wind interaction. Russell et al. (1983) have suggested that the altitude profiles of the horizontal field on different orbits exhibit a pattern which can be interpreted as phases in the temporal evolution of an initial state in which the ionosphere was permeated with magnetosheath-like fields. The present investigation is concerned with the argument in favor of a temporal versus spatial explanation for some of the observed field structure. A calculation indicates that the diffusion time for ionospheric fields is long enough to justify attributing the observed fields to the 'memory' of the Venus ionosphere in certain regions.

Luhmann, J. G.↗
NASA NTRS1987

System architecture of a gallium arsenide one-gigahertz digital IC tester

The design for a 1-GHz digital integrated circuit tester for the evaluation of custom GaAs chips and subsystems is discussed. Technology-related problems affecting the design of a GaAs computer are discussed, with emphasis on the problems introduced by long printed-circuit-board interconnect. High-speed interface modules provide a link between the low-speed microprocessor and the chip under test. Memory-multiplexer and memory-shift register architectures for the storage of test vectors are described in addition to an architecture for local data storage consisting of a long chain of GaAs shift registers. The tester is constructed around a VME system card cage and backplane, and very little high-speed interconnect exists between boards. The tester has a three part self-test consisting of a CPU board confidence test, a main memory confidence test, and a high-speed interface module functional test.

Fouts, Douglas J.↗
DOE OSTI2025

Dual-ion ECRAM as a stable and accurate analog synapse

Electrochemical random-access memory (ECRAM) works by tuning the bulk electronic conductance of functional materials via reversible, electrochemical insertion of ions, resulting in stable analog resistive switching, attractive for analog in-memory and neuromorphic computing. However, achieving fast programming for training and long retention for inference has been elusive. Protonic ECRAM demonstrates fast programming but insufficient retention, while oxygen-based ECRAM with excellent retention requires elevated programming temperatures. Cu-based ECRAM offers a compromise, with an activation energy (E A ) of ≈0.76 eV between protons (E A ≈ 0.4 eV) and oxygen (E A > 1 eV), enabling extensive retention and room temperature programming. Combining Cu 2+ ions with protons to form a dual-ion ECRAM, we demonstrate two distinct switching behaviors: fast switching at ≤5 V, (E A ≈ 0.45 eV) via protons, and nonvolatile, room temperature switching at ≥8 V, with E A ≈ 0.76 eV via Cu 2+ ions. In conclusion, the Cu-based state exhibits a wide conductance range, with excellent retention, low noise, and linear current-voltage behavior, achieving digital-equivalent ImageNet inference accuracy.

analog in-memory computing↗
NASA NTRS2001

Highly Survivable Avionics Systems for Long-Term Deep Space Exploration

The design of highly survivable avionics systems for long-term (> 10 years) exploration of space is an essential technology for all current and future missions in the Outer Planets roadmap. Long-term exposure to extreme environmental conditions such as high radiation and low-temperatures make survivability in space a major challenge. Moreover, current and future missions are increasingly using commercial technology such as deep sub-micron (0.25 microns) fabrication processes with specialized circuit designs, commercial interfaces, processors, memory, and other commercial off the shelf components that were not designed for long-term survivability in space. Therefore, the design of highly reliable, and available systems for the exploration of Europa, Pluto and other destinations in deep-space require a comprehensive and fresh approach to this problem. This paper summarizes work in progress in three different areas: a framework for the design of highly reliable and highly available space avionics systems, distributed reliable computing architecture, and Guarded Software Upgrading (GSU) techniques for software upgrading during long-term missions. Additional information is contained in the original extended abstract.

Alkalai, L.↗
DOE OSTI2025

Spin-Photon Entanglement of a Single Er 3 + Ion in the Telecom Band

Entanglement between photons and a quantum memory is a key component of quantum repeaters, which allow long-distance quantum entanglement distribution in the presence of fiber losses. Spin-photon entanglement has been implemented with a number of different atomic and solid-state qubits with long spin coherence times, but none directly emit photons into the 1.5 − μ m telecom band where losses in optical fibers are minimized. Here, we demonstrate spin-photon entanglement using a single rare earth ion in the solid-state Er 3 + coupled to a silicon nanophotonic cavity, which directly emits photons at 1532.6 nm. We infer an entanglement fidelity of 73(3)% after propagating through 15.6 km of optical fiber. This work opens the door to large-scale quantum networks based Er 3 + ions, leveraging scalable silicon device fabrication and spectral multiplexing. Published by the American Physical Society 2025

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS1987

Resistive synaptic interconnects for electronic neural networks

The use of the alpha-Ge(1-x):Al(x) and alpha-Ge(1-x):Cu(x) alloys and Pt/Al2O3 cermet thin films as resistive interconnects for binary synaptic memory arrays is evaluated. The fabrication of the 10-20 microns long, 10 microns wide, and 0.1 micron thick interconnects from the alloys and cermet is described. The current-voltage and switching characteristics of the as-deposited films and the patterned test structure are studied. The resistivity, uniformity, stability, and compatibility of the interconnects are examined. It is observed that alpha-Ge(1-x):Cu(x) alloys have a wide resistivity range and low temperature coefficients of resistance; however, their long-term stability is limited due to their low crystallization temperature. It is detected that the alpha-Ge(1-x):Al(x) alloys have higher crystallization temperatures and their resistivity is not greatly affected by large changes in metal content. The Pt/Al2O3 samples display excellent stability, easy fabrication, and control of resistivity with metal content.

Lamb, J. L.↗
NASA NTRS1990

Contour-map encoding of shape for early vision

Contour maps provide a general method for recognizing 2-D shapes. All but blank images give rise to such maps, and people are good at recognizing objects and shapes from them. The maps are encoded easily in long feature vectors that are suitable for recognition by an associative memory. These properties of contour maps suggest a role for them in early visual perception. The prevalence of direction sensitive neurons in the visual cortex of mammals supports this view.

Kanerva, Pentti↗
NASA NTRS2003

Pressure-Sensor Assembly Technique

Nielsen Engineering & Research (NEAR) recently developed an ultrathin data acquisition system for use in turbomachinery testing at NASA Glenn Research Center. This system integrates a microelectromechanical- systems- (MEMS-) based absolute pressure sensor [0 to 50 psia (0 to 345 kPa)], temperature sensor, signal-conditioning application-specific integrated circuit (ASIC), microprocessor, and digital memory into a package which is roughly 2.8 in. (7.1 cm) long by 0.75 in. (1.9 cm) wide. Each of these components is flip-chip attached to a thin, flexible circuit board and subsequently ground and polished to achieve a total system thickness of 0.006 in. (0.15 mm). Because this instrument is so thin, it can be quickly adhered to any surface of interest where data can be collected without disrupting the flow being investigated. One issue in the development of the ultrathin data acquisition system was how to attach the MEMS pressure sensor to the circuit board in a manner which allowed the sensor s diaphragm to communicate with the ambient fluid while providing enough support for the chip to survive the grinding and polishing operations. The technique, developed by NEAR and Jabil Technology Services Group (San Jose, CA), is described below. In the approach developed, the sensor is attached to the specially designed circuit board, see Figure 1, using a modified flip-chip technique. The circular diaphragm on the left side of the sensor is used to actively measure the ambient pressure, while the diaphragm on the right is used to compensate for changes in output due to temperature variations. The circuit board is fabricated with an access hole through it so that when the completed system is installed onto a wind tunnel model (chip side down), the active diaphragm is exposed to the environment. After the sensor is flip-chip attached to the circuit board, the die is underfilled to support the chip during the subsequent grinding and polishing operations. To prevent this underfill material from getting onto the sensor s diaphragms, the circuit board is fabricated with two 25- micrometer-tall polymer rings, sized so that the diaphragms fit inside the rings once the chip is attached.

Pruzan, Daniel A.↗
DOE OSTI2024

Method and apparatus for providing thermal wear leveling

Exemplary embodiments provide thermal wear spreading among a plurality of thermal die regions in an integrated circuit or among dies by using die region wear-out data that represents a cumulative amount of time each of a number of thermal die regions in one or more dies has spent at a particular temperature level. In one example, die region wear-out data is stored in persistent memory and is accrued over a life of each respective thermal region so that a long term monitoring of temperature levels in the various die regions is used to spread thermal wear among the thermal die regions. In one example, spreading thermal wear is done by controlling task execution such as thread execution among one or more processing cores, dies and/or data access operations for a memory.

Roberts, David A.↗
NASA NTRS1997

Algorithms for Performance, Dependability, and Performability Evaluation using Stochastic Activity Networks

Modeling tools and technologies are important for aerospace development. At the University of Illinois, we have worked on advancing the state of the art in modeling by Markov reward models in two important areas: reducing the memory necessary to numerically solve systems represented as stochastic activity networks and other stochastic Petri net extensions while still obtaining solutions in a reasonable amount of time, and finding numerically stable and memory-efficient methods to solve for the reward accumulated during a finite mission time. A long standing problem when modeling with high level formalisms such as stochastic activity networks is the so-called state space explosion, where the number of states increases exponentially with size of the high level model. Thus, the corresponding Markov model becomes prohibitively large and solution is constrained by the the size of primary memory. To reduce the memory necessary to numerically solve complex systems, we propose new methods that can tolerate such large state spaces that do not require any special structure in the model (as many other techniques do). First, we develop methods that generate row and columns of the state transition-rate-matrix on-the-fly, eliminating the need to explicitly store the matrix at all. Next, we introduce a new iterative solution method, called modified adaptive Gauss-Seidel, that exhibits locality in its use of data from the state transition-rate-matrix, permitting us to cache portions of the matrix and hence reduce the solution time. Finally, we develop a new memory and computationally efficient technique for Gauss-Seidel based solvers that avoids the need for generating rows of A in order to solve Ax = b. This is a significant performance improvement for on-the-fly methods as well as other recent solution techniques based on Kronecker operators. Taken together, these new results show that one can solve very large models without any special structure.

Deavours, Daniel D.↗
NASA NTRS2013

Low Temperature Creep of Hot-Extruded Near-Stoichiometric NiTi Shape Memory Alloy: Isothermal Creep - Part I

This two-part paper is the first published report on the long term, low temperature creep of hot-extruded near-stoichiometric NiTi. Constant load tensile creep tests were conducted on hot-extruded near-stoichiometric NiTi at 300, 373 and 473 K under initial applied stresses varying between 200 and 350 MPa as long as 15 months. These temperatures corresponded to the martensitic, two-phase and austenitic phase regions, respectively. Normal primary creep lasting several months was observed under all conditions indicating dislocation activity. Although steady-state creep was not observed under these conditions, the estimated creep rates varied between 10(exp -10) and 10(exp -9)/s. The creep behavior of the two phases showed significant differences. The martensitic phase exhibited a large strain on loading followed by a primary creep region accumulating a small amount of strain over a period of several months. The loading strain was attributed to the detwinning of the martensitic phase whereas the subsequent strain accumulation was attributed to dislocation glide-controlled creep. An "incubation period" was observed before the occurrence of detwinning. In contrast, the austenitic phase exhibited a relatively smaller loading strain followed by a primary creep region, where the creep strain continued to increase over several months. It is concluded that the creep of the austenitic phase occurs by a dislocation glide-controlled creep mechanism as well as by the nucleation and growth of deformation twins.

Raj, S. V.↗
NASA NTRS1982

The effects of electron and gamma radiation on epoxy-based materials

Specimens of graphite/epoxy composites and epoxy resins were exposed to electron and gamma radiation, followed by mechanical property and fundamental measurements. Measurement techniques included: scanning electron microscopy, X-ray diffraction analysis, and electron spin resonance spectroscopic analysis. Results indicate little or no change in flexural properties of miniature specimens of a graphite/epoxy composite and no change in failure mode at the fiber-resin interface and in the crystallinity of the fiber and the resin. Some doubt in the observation of stable flexural properties is cast by electron paramagnetic resonance spectra of a relatively large number of radiation-generated radicals. These generally lead to a change in cross-linking and in chain-scissioning which should alter mechanical properties.

Fornes, R. E.↗
NASA NTRS2020

High Temperature Electronics for Venus Surface Applications: A Summary of Recent Technical Advances

This white paper has a technical focus meant to provide background to those unfamiliar with the challenges of high temperature electronics, and an understanding of why new surface mission concepts are now viable for Venus and other applications. It describes that, for the first time, high temperature electronics have been developed to enable a paradigm change in extended duration Venus surface exploration. This white paper concentrates on the advances made in Silicon Carbide (SiC) integrated circuit (IC) electronics that have matured to a state where a simple long-life scientific probe is feasible for Venus surface operations. These electronics have been demonstrated for more than a year at 500˚C, 60 days in high-fidelity simulated Venus surface conditions chamber, and have been integrated and demonstrated with prototype long-lived scientific observation sensor technology. Continued maturation of these needed high temperature electronics and sensors is ongoing in the Long-Lived In-Situ Solar System Explorer (LLISSE) project to provide an operational system including sensor control and operation, signal processing, power management, and communications in the early part of the 2020’s. A key focus of this work includes increasing the complexity and decreasing the power consumption of the ICs which will pave the way to enhanced capabilities, such as long-duration Venus seismic measurements. Other IC development efforts include high temperature memory, terrestrial based characterization of volcanic magma, and development of a simple microprocessor. This electronics has also shown to have exceptionally high radiation tolerance, and thus have relevance for a broad range of solar system exploration. Although presently at the level of complexity of 1970-1980 silicon-based electronics, such electronics can enable breakthroughs in Venus planetary exploration akin to 1970s-launched planetary exploration successes (such as Viking and Voyager).

High temperature Electronics↗
NASA NTRS1989

Variation in SEU sensitivity of dose-imprinted CMOS SRAMs

The authors report on an experimental study of dose-induced changes in SEU (single-event-upset) sensitivity of CMOS static RAMs. Two time regimes were investigated following exposure of memories to cobalt-60 gamma rays: the near term, within a few hours after exposure, and the long term, after many days. Samples were irradiated both at room and at liquid nitrogen temperatures. The latter procedure was used in order to freeze in the damage state until SEU measurements could be made prior to annealing. Results show that memories damaged by dose are more sensitive to upsets by heavy ions. The induced changes are substantial: threshold linear energy transfer (LET) values decreased by as much as 46 percent and asymptotic cross sections increased by factors of two to four (unannealed samples).

Stassinopoulos, E. G.↗
DOE OSTI2025

LLRF System Analysis for the Fermilab PIP-II LINAC

Developing long-lived quantum processing units (QPUs) capable of supporting high-fidelity quantum operations is a crucial challenge on the path toward fault-tolerant quantum computing. TESLA-shaped superconducting RF (SRF) cavities, known for photon relaxation times on the order of seconds, provide an excellent foundation for 3D QPUs and quantum memory. This talk presents a novel design that leverages TESLA cavity modes coupled to ancillary transmon qubits, optimized to preserve coherence and control. By carefully engineering the package geometry, optimizing Hamiltonian parameters, and minimizing lossy participation ratios, we achieve photon relaxation times of over 16 ms and 20 ms for the two cavity modes, representing a significant improvement over previous multimode quantum memories. Despite the reduced coupling between the qubit and cavity modes, which is necessary to preserve long lifetimes, the platform supports robust and universal control schemes that are not limited by low coupling strength. We will also discuss how this architecture can lead to scalable, modular quantum computing systems.

Varghese, P. [Fermilab]↗
NASA NTRS1998

Boreal Winter Predictions with the GEOS-2 GCM: The Role of Boundary Forcing and Initial Conditions

Ensembles of atmospheric General Circulation Model (GCM) seasonal forecasts and long-term simulations (1980-94) are analyzed to assess the controlling influences of boundary forcing and memory of the initial conditions. Both the forecasts and simulations are carried out with version 2 of the Goddard Earth Observing System (GEOS-2) GCM forced with observed sea surface temperatures (SSTs). While much of the focus is on the seasonal time scale (January- March) and the Pacific North American (PNA) region, we also present results for other regions, shorter time scales, and other known modes of variability in the northern hemisphere extratropics. Forecasts of indices of some of the key large-scale modes of variability show that there is considerable variability in skill between different regions of the Northern Hemisphere. The eastern North Atlantic region has the poorest long lead forecast skill showing no skill beyond about 10 days. Skillful seasonal forecasts are primarily confined to the wave-like ENSO response emanating from the tropical Pacific. In the Northern Hemisphere, this is associated with the well-known Pacific/North American (PNA) pattern. Memory of the initial conditions is the major factor leading to skillful extratropical forecasts of lead time less than one month, while SST forcing is the only factor at the seasonal time scale. SST forcing contributes to skillful forecasts at sub- seasonal time scales only over the PNA region. The GEOS-2 GCM produces average (1980-94) signal to noise ratios which are less than one everywhere in the extratropics, except for the subtropical Pacific where they approach 1.5. When confined to the ENSO years, the maximum signal to noise ratios occur in the PNA region where they exceed three. An assessment of the sampling distribution of the forecasts suggests the model's ENSO response is very likely too weak. These results show some sensitivity to the uncertainties in the estimates of the SST forcing fields. In the North Pacific region, the sensitivity to SST forcing manifests itself primarily as changes in the variability of the PNA response, underscoring the need for an ensemble approach to the seasonal prediction problem.

Chang, Yehui↗
NASA NTRS1993

A petabyte size electronic library using the N-Gram memory engine

A model library containing petabytes of data is proposed by Triada, Ltd., Ann Arbor, Michigan. The library uses the newly patented N-Gram Memory Engine (Neurex), for storage, compression, and retrieval. Neurex splits data into two parts: a hierarchical network of associative memories that store 'information' from data and a permutation operator that preserves sequence. Neurex is expected to offer four advantages in mass storage systems. Neurex representations are dense, fully reversible, hence less expensive to store. Neurex becomes exponentially more stable with increasing data flow; thus its contents and the inverting algorithm may be mass produced for low cost distribution. Only a small permutation operator would be recalled from the library to recover data. Neurex may be enhanced to recall patterns using a partial pattern. Neurex nodes are measures of their pattern. Researchers might use nodes in statistical models to avoid costly sorting and counting procedures. Neurex subsumes a theory of learning and memory that the author believes extends information theory. Its first axiom is a symmetry principle: learning creates memory and memory evidences learning. The theory treats an information store that evolves from a null state to stationarity. A Neurex extracts information data without a priori knowledge; i.e., unlike neural networks, neither feedback nor training is required. The model consists of an energetically conservative field of uniformly distributed events with variable spatial and temporal scale, and an observer walking randomly through this field. A bank of band limited transducers (an 'eye'), each transducer in a bank being tuned to a sub-band, outputs signals upon registering events. Output signals are 'observed' by another transducer bank (a mid-brain), except the band limit of the second bank is narrower than the band limit of the first bank. The banks are arrayed as n 'levels' or 'time domains, td.' The banks are the hierarchical network (a cortex) and transducers are (associative) memories. A model Neurex was built and studied. Data were 50 MB to 10 GB samples of text, data base, and images: black/white, grey scale, and high resolution in several spectral bands. Memories at td, S(m(sub td)), were plotted against outputs of memories at td-1. S(m(sub td)) was Boltzman distributed, and memory frequencies exhibited self-organized criticality (SOC); i.e., 'l/f(sup beta)' after long exposures to data. Whereas output signals from level n may be encoded with B(sub output) = O(-log(2)f(sup beta)) bits, and input data encoded with B(sub input) = O((S(td)/S(td-1))(sup n)), B(sup output)/B(sub input) is much less than 1 always, the Neurex determines a canonical code for data and it is a lossless data compressor. Further tests are underway to confirm these results with more data types and larger samples.

Bugajski, Joseph M.↗