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At least 361 records · Page 20

Analyzing a 35-Year Hourly Data Record: Why So Difficult?

At the Goddard Distributed Active Archive Center, we have recently added a 35-Year record of output data from the North American Land Assimilation System (NLDAS) to the Giovanni web-based analysis and visualization tool. Giovanni (Geospatial Interactive Online Visualization ANd aNalysis Infrastructure) offers a variety of data summarization and visualization to users that operate at the data center, obviating the need for users to download and read the data themselves for exploratory data analysis. However, the NLDAS data has proven surprisingly resistant to application of the summarization algorithms. Algorithms that were perfectly happy analyzing 15 years of daily satellite data encountered limitations both at the algorithm and system level for 35 years of hourly data. Failures arose, sometimes unexpectedly, from command line overflows, memory overflows, internal buffer overflows, and time-outs, among others. These serve as an early warning sign for the problems likely to be encountered by the general user community as they try to scale up to Big Data analytics. Indeed, it is likely that more users will seek to perform remote web-based analysis precisely to avoid the issues, or the need to reprogram around them. We will discuss approaches to mitigating the limitations and the implications for data systems serving the user communities that try to scale up their current techniques to analyze Big Data.

computational performance↗

Holographic recording materials development

Developments in the area of organic cis-trans isomerization systems for holographic memory applications are reported. The chemical research effort consisted of photochemical studies leading to the selection of a stilbene derivative and a polymer matrix system which have greatly improved refractive index differences between the cis and trans isomers as well as demonstrated efficiency of the photoisomerization process. In work on lithium niobate effects of sample stoichiometry and of read and write beam polarizations on recording efficiency were investigated. LiNbO3 was used for a study of angular sensitivity and of capability for simultaneous recording of extended objects without interference. The current status of LiNbO3 as a holographic recording material is summarized.

Source record↗

L'Arlesienne de ROOT

Over many years, ROOT users have repeatedly stumbled over—and loudly rediscovered—the infamous 1 GB limit on individual I/O operations, a constraint that somehow survived long past the era when anyone thought a gigabyte was “a lot.” As experiments embraced ever-larger objects and collections, this limit became an increasingly unavoidable rite of passage. This contribution recounts the sustained, multi-year quest by ROOT I/O developers to finally retire this relic, navigating a maze of legacy APIs, memory-management assumptions, and integer boundaries that seemed determined to preserve the status quo. We describe how internal interfaces were carefully modernized to introduce fully 64-bit–capable code paths without breaking the mountains of existing user code that would definitely have noticed. With the limit now lifted, ROOT can finally handle multi-gigabyte objects in a single read or write operation, even when splitting them into an RNTuple is not an option (we’re looking at you, large RooWorkspaces and giant histograms), liberating users from yet another “fun” debugging adventure and clearing the way for the massive analyses of the HL-LHC and beyond.

Canal, Philippe G. [Fermilab] (ORCID:0000000277487↗

L'Arlesienne de ROOT

Over many years, ROOT users have repeatedly stumbled over—and loudly rediscovered—the infamous 1 GB limit on individual I/O operations, a constraint that somehow survived long past the era when anyone thought a gigabyte was “a lot.” As experiments embraced ever-larger objects and collections, this limit became an increasingly unavoidable rite of passage. This contribution recounts the sustained, multi-year quest by ROOT I/O developers to finally retire this relic, navigating a maze of legacy APIs, memory-management assumptions, and integer boundaries that seemed determined to preserve the status quo. We describe how internal interfaces were carefully modernized to introduce fully 64-bit–capable code paths without breaking the mountains of existing user code that would definitely have noticed. With the limit now lifted, ROOT can finally handle multi-gigabyte objects in a single read or write operation, even when splitting them into an RNTuple is not an option (we’re looking at you, large RooWorkspaces and giant histograms), liberating users from yet another “fun” debugging adventure and clearing the way for the massive analyses of the HL-LHC and beyond.

Canal, Philippe G. [Fermilab] (ORCID:0000000277487↗

Method for Veterbi decoding of large constraint length convolutional codes

A new method of Viterbi decoding of convolutional codes lends itself to a pipline VLSI architecture using a single sequential processor to compute the path metrics in the Viterbi trellis. An array method is used to store the path information for NK intervals where N is a number, and K is constraint length. The selected path at the end of each NK interval is then selected from the last entry in the array. A trace-back method is used for returning to the beginning of the selected path back, i.e., to the first time unit of the interval NK to read out the stored branch metrics of the selected path which correspond to the message bits. The decoding decision made in this way is no longer maximum likelihood, but can be almost as good, provided that constraint length K in not too small. The advantage is that for a long message, it is not necessary to provide a large memory to store the trellis derived information until the end of the message to select the path that is to be decoded; the selection is made at the end of every NK time unit, thus decoding a long message in successive blocks.

Hsu, In-Shek↗

Digital command system

The correct processing of the Digital Command System (DCS), which provides a limited real-time means of controlling specific flight program functions, was verified. The ability of the flight program to correctly read and process DCS commands was verified. Tests made by the flight program after reading the contents of the command decoder register to establish the validity of the received data were verified through the following: DCS mode command verification, DCS data command verification, DCS data validation, and DCS error message. The operation of the following DCS commands accepted and processed by the flight program was tested: time base update, navigation update, generalized switch selector, memory dump, terminate, execute generalized maneuver, return to nominal timeline, ECS water control valve logic inhibit, execute maneuver, execute alternate sequence, targeting load, ladder magnitude limit, S-IVB/IU de-orbit, compressed data dump, and remove inhibit on the extraction maneuver.

Source record↗

Stimulated electronic transition concept for an erasable optical memory

A new concept for an erasable optical memory is demonstrated using stimulated electronic transition (SET). Large bandgap semiconductors are suitable materials for the SET medium. The properties of MgS:Eu,Sm and SrS:Eu,Sm as possible media for the SET process are investigated. Quantum storage is achieved in the form of charges in deep levels in the medium and stimulated radiative recombination is used as the reading process. Unlike magneto-optic (M-O) and phase change (PC) processes, optical writing, reading and erasing are achieved without localized heating. The SET process will have an inherently faster data transfer rate and a higher storage density, and the medium will be more durable than the M-O and PC media. A possible application of the SET process in neural networks is also discussed.

Albin, Sacharia↗

Fast and accurate metagenotyping of the human gut microbiome with GT-Pro

Single nucleotide polymorphisms (SNPs) in metagenomics are used to quantify population structure, track strains and identify genetic determinants of microbial phenotypes. However, existing alignment-based approaches for metagenomic SNP detection require high-performance computing and enough read coverage to distinguish SNPs from sequencing errors. To address these issues, we developed the GenoTyper for Prokaryotes (GT-Pro), a suite of methods to catalog SNPs from genomes and use unique k-mers to rapidly genotype these SNPs from metagenomes. Compared to methods that use read alignment, GT-Pro is more accurate and two orders of magnitude faster. Here, using high-quality genomes, we constructed a catalog of 104 million SNPs in 909 human gut species and used unique k-mers targeting this catalog to characterize the global population structure of gut microbes from 7,459 samples. GT-Pro enables fast and memory-efficient metagenotyping of millions of SNPs on a personal computer.

59 BASIC BIOLOGICAL SCIENCES↗

Kanerva's sparse distributed memory with multiple hamming thresholds

If the stored input patterns of Kanerva's Sparse Distributed Memory (SDM) are highly correlated, utilization of the storage capacity is very low compared to the case of uniformly distributed random input patterns. We consider a variation of SDM that has a better storage capacity utilization for correlated input patterns. This approach uses a separate selection threshold for each physical storage address or hard location. The selection of the hard locations for reading or writing can be done in parallel of which SDM implementations can benefit.

Pohja, Seppo↗

Calibration and Lag of a Friez Type Cup Anemometer

Tests on a Friez type cup anemometer have been made in the variable density wind tunnel of the Langley Memorial Aeronautical Laboratory to calibrate the instrument and to determine its suitability for velocity measurements of wind gusts. The instrument was calibrated against a Pitot-static tube placed directly above the anemometer at air densities corresponding to sea level, and to an altitude of approximately 6000 feet. Air-speed acceleration tests were made to determine the lag in the instrument reading. The calibration results indicate that there should be an altitude correction. It is concluded that the cup anemometer is too sluggish for velocity measurements of wind gusts.

INSTRUMENTS - ANEMOMETERS - FRIEZ↗

Latency hiding for caches

A technique for accessing a memory having a high latency portion and a low latency portion is provided. The technique includes detecting a promotion trigger to promote data from the high latency portion to the low latency portion, in response to the promotion trigger, copying cache lines associated with the promotion trigger from the high latency portion to the low latency portion, and in response to a read request, providing data from either or both of the high latency portion or the low latency portion, based on a state associated with data in the high latency portion and the low latency portion.

97 MATHEMATICS AND COMPUTING↗

Optimized self-designing key-value storage engine

Embodiments of the invention utilize an optimized key-value storage engine to strike the optimal balance between cloud-cost and performance and supports queries, including updates, lookups, range queries, inserts, and read-modify-writes. Cloud cost is manifested in purchasing both storage and processing resources. The improved approach has the ability to self-design and instantiate holistic configurations given a workload, a cloud budget, and optionally performance goals and a set of Service Level Agreement (SLA) specifications. A configuration reflects an optimized storage engine design in terms of, for example, the individual data structures design (in-memory and on-disk) in the engine as well as their algorithms and interactions, a cloud provider, and the exact virtual machines to be used.

Idreos, Stratos↗

A single-board preprocessor and pulse generator

The Aeronomy Lab. of NOAA has designed and built a single board, programmable radar controller for use with VHF ST (stratosphere troposphere) radars. The controller consists of a coherent integrator preprocessor and a radar pulse generator, both of which are described, as well as interfaces to an antenna beam switch and a receiver bandwidth switch. The controller occupies a single slot in a Data General Nova of Eclipse computer. The integrator and pulse generator take advantage of high density, dual port FIFO chips such as the 512 x 9 Mostek MK 4501. These FIFOs have separate input and output ports and independent read and write cycles with cycle times of less than 200 ns, making them very fast and easy to interface. A simple block diagram of the coherent integrator is shown. The integrator is designed to handle inputs from one receiver (2 channels) with 1 sec sample spacing. The pulse generator is based on controllers designed by R. F. Woodman for the Arecibo and SOUSY radars us a recirculating memory scheme.

Carter, D. A.↗

An LSTM Deep Learning Network for ¿Background Radiation Prediction

Determination of appropriate background radiation is important in any measurement application. Environmental radiation monitors and monitors used to assess dose to individuals outside of controlled areas are particularly susceptible to changes in readings due to fluctuations in the environmental conditions. These fluctuations (e.g. radon progeny concentrations) lead to changes in the detector response in the actual radiation environment, and they need to be taken into account when extracting the net operational doses. Work has been ongoing to apply advances in Deep Learning and Artificial Intelligence to account for changes in detector responses based on environmental parameters; in particular, a Long-Short Term Memory (LSTM) Deep Learning architecture has been utilized to incorporate time-series data into a prediction model. In this work, we present the current status of the project to predict radiation measurements based on meteorological conditions and air packet trajectories extracted using the National Oceanic and Atmospheric Administration's (NOAA) Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT4) model.

Degtiarenko, Pavel↗

TuckerMPI: A Parallel C++/MPI Software Package for Large-scale Data Compression via the Tucker Tensor Decomposition

With this study, our goal is compression of massive-scale grid-structured data, such as the multi-terabyte output of a high-fidelity computational simulation. For such data sets, we have developed a new software package called TuckerMPI, a parallel C++/MPI software package for compressing distributed data. The approach is based on treating the data as a tensor, i.e., a multidimensional array, and computing its truncated Tucker decomposition, a higher-order analogue to the truncated singular value decomposition of a matrix. The result is a low-rank approximation of the original tensor-structured data. Compression efficiency is achieved by detecting latent global structure within the data, which we contrast to most compression methods that are focused on local structure. In this work, we describe TuckerMPI, our implementation of the truncated Tucker decomposition, including details of the data distribution and in-memory layouts, the parallel and serial implementations of the key kernels, and analysis of the storage, communication, and computational costs. We test the software on 4.5 and 6.7 terabyte data sets distributed across 100 s of nodes (1,000 s of MPI processes), achieving compression ratios between 100 and 200,000×, which equates to 99--99.999% compression (depending on the desired accuracy) in substantially less time than it would take to even read the same dataset from a parallel file system. Moreover, we show that our method also allows for reconstruction of partial or down-sampled data on a single node, without a parallel computer so long as the reconstructed portion is small enough to fit on a single machine, e.g., in the instance of reconstructing/visualizing a single down-sampled time step or computing summary statistics. The code is available at https://gitlab.com/tensors/TuckerMPI.

97 MATHEMATICS AND COMPUTING↗

GROWdb US River Systems - Samples

GROW Overview We developed the Genome Resolved Open Watersheds database (GROWdb), which aims to increase genomic sampling and understanding of global river microbiomes. An emphasis of GROWdb is to create a publicly available and ever-expanding microbial genome database that is focused on rivers while being interoperable with databases from other ecosystems. GROWdb is based on a network-of-networks approach to move beyond a small collection of well-studied rivers, towards a spatially distributed, global network of systematic observations. GROWdb represents the first microbial, river-focused resource parsed at various scales from genes to MAGs to community level including expression and potential based measurements that will be of interest to microbiologists, ecologists, geochemists, hydrologists, and modelers. Dataset Acknowledgement GROWdb contains data from various research campaigns, please acknowledge the following data generators, as appropriate: WHONDRS derived genomes or samples - include this statement in your acknowledgements: “This study used data from the Worldwide Hydrobiogeochemistry Observation Network for Dynamic River Systems (WHONDRS) under the River Corridor Science Focus Area (SFA) at the Pacific Northwest National Laboratory (PNNL) that was generated at the U.S. Department of Energy (DOE) Joint Genome Institute User Facility. PNNL is operated by Battelle Memorial Institute for the U.S. DOE under Contract No. DE-AC05-76RL01830. The SFA is supported by the U.S. DOE, Office of Biological and Environmental Research (BER), Environmental System Science (ESS) Program.” Total Samples loaded onto this Narrative: 178 Note: Not all GROW samples may be loaded into KBase Data Availability The data underlying GROWdb are accessible across various platforms to ensure all levels of data structure are widely available. First, all reads and MAGs are publicly hosted on National Center for Biotechnology (NCBI) under Bioproject PRJNA946291. Second, all data related data presented here including MAG annotations, extended data tables, phylogenetic tree files, antibiotic resistance gene database files, and MAG abundance tables are available in Zenodo (link). Beyond the flat database files listed above, our aim for GROWdb was to maximize data use by making the data available in searchable and interactive platforms including the National Microbiome Data Collaborative (NMDC) data portal, the Department of Energy’s Systems Biology Knowledgebase (KBase), and a GROW specific user interface released here, GROWdb Explorer. Each platform provides different ways to interact with GROWdb: NMDC GROWdb formed a pilot project for the NMDC. Specifically, individual GROWdb datasets (metagenomes, metatranscriptomes, etc) are easily accessible and searchable through the NMDC data portal, where they are systematically connected to each other and to a rich suite of sample information and standard analysis results, following Findable, Accessible, Interoperable, and Reusable (FAIR) data practices. KBase GROWdb is publicly available within KBase, including samples (this Narrative), MAGs, and corresponding genome scale metabolic models. Access within KBase allows for immediate access and reuse of data, including comparison to private data using KBase’s 500+ analysis tools. Other linked narratives in KBase: GROW Metagenome Assembled Genomes (MAGs) GROW Metabolic Models GROWdb Explorer GROWdb data is also explorable through a graphical user interface built through the Colorado State University Geospatial Centroid (https://geocentroid.shinyapps.io/GROWdatabase/), allowing users to search and graph microbial and spatial data simultaneously. In summary, this microbial genome resource represents the first publicly available genome collection from rivers and offers data that can be leveraged across microbiome studies. GROWdb is an expanding repository to incorporate and unify global river multi-omic data for the future.

59 BASIC BIOLOGICAL SCIENCES↗

Securing 3D NAND Without Density Loss via In-Situ Encryption Using a Single Transistor XOR Cell

In this article, we push lightweight XOR-based in-situ encryption to extreme density by proposing a singletransistor XOR memory cell and applying it to 3D NAND, enabling secure data storage without density loss. Using a ferroelectric field-effect transistor (FeFET) as an example technology, we demonstrate that: i) a single-transistor memory can realize the XOR function by exploiting the ability to charge the source and drain separately and control current flow direction, eliminating the need for conventional encrypted cells that rely on complementary devices; ii) with a XOR-based cipher, encryption and decryption can be mapped to in-situ array operations, where ciphertext is stored as the threshold voltage (VTH) states of FeFETs in a NAND string, and decryption is achieved through read operations using key-dependent complementary source/drain bias; iii) the proposed technique is scalable to multi-level cell (MLC) storage by encrypting and decrypting data bit by bit; iv) using an integrated NAND FeFET array, we experimentally demonstrate encryption and decryption operations for both single-level cell (SLC) and MLC storage; v) systemlevel benchmarking shows that the proposed technique achieves 48× and 278× improvements in encryption and decryption throughput, respectively, compared to AES.

36 MATERIALS SCIENCE↗