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The Galileo Command and Data Subsystems (CDS) is described. The CDS takes advantage of microprocessor technology which serves as the core of the distributed data system. The microprocessors are interconnected by a high speed data bus.
Just as “classical” information technology rests on a foundation built of interconnected information-processing systems, quantum information technology (QIT) must do the same. A critical component of such systems is the “interconnect,” a device or process that allows transfer of information between disparate physical media, for example, semiconductor electronics, individual atoms, light pulses in optical fiber, or microwave fields. While interconnects have been well engineered for decades in the realm of classical information technology, quantum interconnects (QuICs) present special challenges, as they must allow the transfer of fragile quantum states between different physical parts or degrees of freedom of the system. The diversity of QIT platforms (superconducting, atomic, solid-state color center, optical, etc.) that will form a “quantum internet” poses additional challenges. As quantum systems scale to larger size, the quantum interconnect bottleneck is imminent, and is emerging as a grand challenge for QIT. For these reasons, it is the position of the community represented by participants of the NSF workshop on “Quantum Interconnects” that accelerating QuIC research is crucial for sustained development of a national quantum science and technology program. Given the diversity of QIT platforms, materials used, applications, and infrastructure required, a convergent research program including partnership between academia, industry, and national laboratories is required.
Proposed processor architecture would have flexibility of a multi-processor and computational power of a lockstep array. Using an efficient interconnection network, it accomodates a large number of individual processors and memory modules. Array architecture would be suitable for very large scientific simulation problems and other applications.
In the case of complex industrial operations, the use of a multiprocessor for the control of a robotic system has a number of potential advantages over an employment of a single-processor design. In addition to the increased speed of parallel computation, multiprocessors can provide greater reliability. However, the control of a system with a multiprocessor is much more complicated, and requires resolution of a number of design criteria. The degree of coupling, the processor interconnection configuration, and the method of fault detection and correction are factors in the design of a multiprocessor which need to be considered for each particular application. In connection with the present investigation, a five-unit multiprocessor was built to experiment with the multiprocessor control of a robotic system. While the primary application of the multiprocessor involves the control of the Ohio State University (OSU) Hexapod, an 18-degree-of-freedom, motor-driven walking machine, the multiprocessor was designed to be versatile enough for a numbr of other uses.
The deep learning revolution has been enabled in large part by GPUs, and more recently accelerators, which make it possible to carry out computationally demanding training and inference in acceptable times. As the size of machine learning networks and workloads continues to increase, multi-GPU machines have emerged as an important platform offered on High Performance Computing and cloud data centers. Since these machines are shared among multiple users, it becomes increasingly important to protect applications against potential attacks. In this paper, we explore the vulnerability of Nvidia's DGX multi-GPU machines to covert and side channel attacks. These machines consist of a number of discrete GPUs that are interconnected through a combination of custom interconnect (NVLink) and PCIe connections. We reverse engineer the interconnected cache hierarchy and show that it is possible for an attacker on one GPU to cause contention on the L2 cache of another GPU. We use this observation to first develop a covert channel attack across two GPUs, achieving the best bandwidth of around 4 MB/s. We also develop a prime and probe attack on a remote GPU allowing an attacker to recover the cache access pattern of another workload. This access pattern can be used in any number of side channel attacks: we demonstrate a proof of concept attack that fingerprints the application running on the remote GPU, with high accuracy. We also develop a proof of concept attack to extract hyperparameters of a machine learning workload. Our work establishes for the first time the vulnerability of these machines to microarchitectural attacks and can guide future research to improve their security.
The prime driving force for using microsystem and micromachine technologies in transport vehicles, such as spacecraft, aircraft, and automobiles, is to reduce the weight, power consumption, and volume of components and systems to lower costs and increase affordability and reliability. However, a number of specific issues need to be addressed with respect to using microsystems and micromachines in aerospace applications--such as the lack of understanding of material characteristics; methods for producing and testing the materials in small batches; the limited proven durability and lifetime of current microcomponents, packaging, and interconnections; a cultural change with respect to system designs; and the use of embedded software, which will require new product assurance guidelines. In regards to material characteristics, there are significant adhesion, friction, and wear issues in using microdevices. Because these issues are directly related to surface phenomena, they cannot be scaled down linearly and they become increasingly important as the devices become smaller. When microsystems have contacting surfaces in relative motion, the adhesion and friction affect performance, energy consumption, wear damage, maintenance, lifetime and catastrophic failure, and reliability. Ceramics, for the most part, do not have inherently good friction and wear properties. For example, coefficients of friction in excess of 0.7 have been reported for ceramics and ceramic composite materials. Under Alternate Fuels Foundation Technologies funding, two-phase oxide ceramics developed for superior high-temperature wear resistance in NASA's High Operating Temperature Propulsion Components (HOTPC) project and new two-layered carbon nanotube (CNT) coatings (CNT topcoat/iron bondcoat/quartz substrate) developed in NASA's Revolutionary Aeropropulsion Concepts (RAC) project have been chosen as a materials couple for aerospace applications, including micromachines, in the nanotechnology lubrication task because of their potential for superior friction and wearf properties in air and in an ultrahigh vacuum, spacelike environment. At the NASA Glenn Research Center, two-phase oxide ceramic eutectics, Al2O3/ZrO2(Y2O3), were directionally solidified using the laser-float-zone process, and carbon nanotubes were synthesized within a high-temperature tube furnace at 800 C. Physical vapor deposition was used to coat all quartz substrates with 5-nm-thick iron as catalyst and bondcoat, which formed iron islands resembling droplets and serving as catalyst particles on the quartz. A series of scanning electron micrographs showing multiwalled carbon nanotubes directionally grown as aligned "nanograss" on quartz is presented. Unidirectional sliding friction eperiments were conducted at Glenn with the two-layered CNT coatings in contact with the two-phase Al2O3/ZrO2(Y2O3) eutectics in air and in ultrachigh vacuum. The main criteria for judging the performance of the materials couple for solid lubrication and antistick applications in a space environment were the coefficient of friction and the wear resistance (reciprocal of wear rate), which had to be less than 0.2 and greater than 10(exp 5) N(raised dot)/cubic millimetes, respectively, in ultrahigh vacuum. In air, the coefficient of friction for the CNT coatings in contact with Al2O3/ZrO2 (Y2O3) eutectics was 0.04, one-fourth of that for quartz. In an ultrahigh vacuum, the coefficient of friction for CNT coatings in contact with Al2O3/ZrO2 (Y2O3) was one-third of that for quartz. The two-phase Al2O3/ZrO2 (Y2O3) eutectic coupled with the two-layered CNT coating met the coefficient of friction and wear resistance criteria both in air and in an ultrahigh vacuum, spacelike environment. This material's couple can dramatically improve the stiction (or adhesion), friction, and wear resistance of the contacting surfaces, which are major issues for microdevices and micromachines.
Three-terminal (3T) GaInP/GaAs solar cells are fabricated from inverted-grown monolithic tandems and processed with external metal contacts suitable for easy interconnection. Prototype 3T tandems both with and without tunnel junctions are demonstrated. They are characterized as a function of two independent variables in a variety of configurations, with each configuration holding one of the contacts common to two source-meter units (SMUs). Each of these different measurement configurations completely characterizes the device by transforming the results into 6 unique device parameters and plotting the total power parametrically in two dimensions. The performance is fit using a 3T optoelectronic model that includes luminescent coupling as well as important resistances. Eight of these devices are interconnected in various voltage-constrained configurations to form voltage-matched (VM) strings. Measurement and analysis of these III-V devices and strings are generally applicable to all 3T photovoltaics.
A progress report, starting with November 1973, is given in the design, development, and performance of lightweight flexible FET (Fluorinated Ethylene Propylene) encapsulated solar cell modules intended to form standardized building blocks for large roll-up or fold-up solar cell blankets with performances on the order of 100 W/sq m and 80 W/kg in near space. It is shown that interconnected FEP encapsulated modules of advanced design can withstand all typical ground handling, assembly, storage, and launch conditions, and are well suited for high-power space applications.
The design of the computer operating system at Langley Research Center allows for concurrent support of time-critical simulations and background analytical computing on the same machine. Signal path interconnections between computing hardware and flight simulation hardware is provided to allow up to six simulation programs to be in operation at one time. Capabilities and research applications are discussed for the: (1) differential maneuvering simulator; (2) visual motion simulator; (3) terminal configured vehicle simulator; (4) general aviation aircraft simulator; (5) general purpose fixed based simulator; (6) transport simulator; (7) digital fly by wire simulator; (8) general purpose fighter simulator; and (9) the roll-up cockpit. The visual landing display system and graphics display system are described and their simulator support applications are listed.
Operation of electronic parts and circuits under extreme temperatures is anticipated in NASA space exploration missions as well as terrestrial applications. Exposure of electronics to extreme temperatures and wide-range thermal swings greatly affects their performance via induced changes in the semiconductor material properties, packaging and interconnects, or due to incompatibility issues between interfaces that result from thermal expansion/contraction mismatch. Electronics that are designed to withstand operation and perform efficiently in extreme temperatures would mitigate risks for failure due to thermal stresses and, therefore, improve system reliability. In addition, they contribute to reducing system size and weight, simplifying its design, and reducing development cost through the elimination of otherwise required thermal control elements for proper ambient operation. A large DC voltage gain (100 dB) operational amplifier with a maximum junction temperature of 150 C was recently introduced by STMicroelectronics [1]. This LM2904WH chip comes in a plastic package and is designed specifically for automotive and industrial control systems. It operates from a single power supply over a wide range of voltages, and it consists of two independent, high gain, internally frequency compensated operational amplifiers. Table I shows some of the device manufacturer s specifications.
Solar particle events (SPEs) pose the risk of acute radiation sickness (ARS) to astronauts, because organ doses from large SPEs may reach critical levels during extra vehicular activities (EVAs) or lightly shielded spacecraft. NASA has developed an organ dose projection model of Baryon transport code (BRYNTRN) with an output data processing module of SUMDOSE, and a probabilistic model of acute radiation risk (ARR). BRYNTRN code operation requires extensive input preparation, and the risk projection models of organ doses and ARR take the output from BRYNTRN as an input to their calculations. With a graphical user interface (GUI) to handle input and output for BRYNTRN, these response models can be connected easily and correctly to BRYNTRN in a user friendly way. The GUI for the Acute Radiation Risk and BRYNTRN Organ Dose (ARRBOD) projection code provides seamless integration of input and output manipulations required for operations of the ARRBOD modules: BRYNTRN, SUMDOSE, and the ARR probabilistic response model. The ARRBOD GUI is intended for mission planners, radiation shield designers, space operations in the mission operations directorate (MOD), and space biophysics researchers. Assessment of astronauts organ doses and ARS from the exposure to historically large SPEs is in support of mission design and operation planning to avoid ARS and stay within the current NASA short-term dose limits. The ARRBOD GUI will serve as a proof-of-concept for future integration of other risk projection models for human space applications. We present an overview of the ARRBOD GUI product, which is a new self-contained product, for the major components of the overall system, subsystem interconnections, and external interfaces.
Surface mount electronic package test boards have been assembled using tin/lead (Sn/Pb) and lead-free (Pb-free or SnAgCu or SAC305) solders. The soldered surface mount packages include ball grid arrays (BGA), flat packs, various sizes of passive chip components, etc. They have been optically inspected after assembly and subsequently subjected to extreme temperature thermal cycling to assess their reliability or future deep space, long-term, extreme temperature environmental missions. In this study, the employed temperature range (-185oC to +125oC) covers military specifications (-55oC to +100oC), extreme old Martian (-120oC to +115oC), asteroid Nereus (-180oC to +25oC) and JUNO (-150oC to +120oC) environments. The boards were inspected at room temperature and at various intervals as a function of extreme temperature thermal cycling and bake duration. Electrical resistance measurements made at room temperature are reported and the tests to date have shown some change in resistance as a function of extreme temperature thermal cycling and some showed increase in resistance. However, the change in interconnect resistance becomes more noticeable with increasing number of thermal cycles. Further research work will be carried out to understand the reliability of packages under extreme temperature applications (-185oC to +125oC) via continuously monitoring the daisy chain resistance for BGA, Flat-packs, lead less chip packages, etc. This paper will describe the experimental reliability results of miniaturized passive components (01005, 0201, 0402, 0603, 0805, and 1206) assembled using surface mounting processes with tin-lead and lead-free solder alloys under extreme temperature environments.
Housekeeping systems are essential to health monitoring of spacecraft and instruments. Typically, sensors are distributed across various sub-systems and data is collected using components such as analog-to-digital converters, analog multiplexers and amplifiers. In most cases programmable devices are used to implement the data acquisition control and storage, and the interface to higher level systems. Such discrete implementations require additional size, weight, power and interconnect complexity versus an integrated circuit solution, as well as the qualification of multiple parts. Although commercial devices are readily available, they are not suitable for space applications due the radiation tolerance and qualification requirements. The Housekeeping System-o n-A-Chip (HKSOC) is a low power, radiation hardened integrated solution suitable for spacecraft and instrument control and data collection. A prototype has been designed and includes a wide variety of functions including a 16-channel analog front-end for driving and reading sensors, analog-to-digital and digital-to-analog converters, on-chip temperature sensor, power supply current sense circuits, general purpose comparators and amplifiers, a 32-bit processor, digital I/O, pulse-width modulation (PWM) generators, timers and I2C master and slave serial interfaces. In addition, the device can operate in a bypass mode where the processor is disabled and external logic is used to control the analog and mixed signal functions. The device is suitable for stand-alone or distributed systems where multiple chips can be deployed across different sub-systems as intelligent nodes with computing and processing capabilities.
Lipid biosynthesis plays a vital role in living cells and has been increasingly engineered to overproduce various lipid-based chemicals. However, owing to the tightly constrained and interconnected nature of lipid biosynthesis, both understanding and engineering of lipid metabolism remain challenging, even with the help of mathematical models. Here we report the development of a kinetic metabolic model of lipid metabolism in Saccharomyces cerevisiae that integrates fatty acid biosynthesis, glycerophospholipid metabolism, sphingolipid metabolism, storage lipids, lumped sterol synthesis, and the synthesis and transport of relevant target-chemicals, such as fatty acids and fatty alcohols. The model was trained on lipidomic data of a reference S. cerevisiae strain, single knockout mutants, and lipid overproduction strains reported in literature. The model was used to design mutants for fatty alcohol overproduction and the lipidomic analysis of the resultant mutant strains coupled with model-guided hypothesis led to discovery of a futile cycle in the triacylglycerol biosynthesis pathway. In addition, the model was used to explain successful and unsuccessful mutant designs in metabolic engineering literature. Thus, this kinetic model of lipid metabolism can not only enable the discovery of new phenomenon in lipid metabolism but also the engineering of mutant strains for overproduction of lipids.
Concepts for integral glass sheet encapsulation of terrestrial solar cell modules using techniques based upon electrostatic bonding are being developed. It is possible for the glass to provide hermetic encapsulation, the structural support, and a vehicle for integral interconnection of the solar cells. Anticipated capabilities, present status, and cost projections for large scale terrestrial utilization are discussed.
Detecting and analyzing complex patterns in multivariate time-series data is crucial for decision-making in urban and environmental system operations. However, challenges arise from the high dimensionality, intricate complexity, and interconnected nature of complex patterns, which hinder the understanding of their underlying physical processes. Existing AI methods often face limitations in interpretability, computational efficiency, and scalability, reducing their applicability in real-world scenarios. This paper proposes a novel visual analytics framework that integrates two generative AI models, Temporal Fusion Transformer (TFT) and Variational Autoencoders (VAEs), to reduce complex patterns into lower-dimensional latent spaces and visualize them in 2D using dimensionality reduction techniques such as PCA, t-SNE, and UMAP with DBSCAN. These visualizations, presented through coordinated and interactive views and tailored glyphs, enable intuitive exploration of complex multivariate temporal patterns, identifying patterns’ similarities and uncover their potential correlations for a better interpretability of the AI outputs. The framework is demonstrated through a case study on power grid signal data, where it identifies multi-label grid event signatures, including faults and anomalies with diverse root causes. Additionally, novel metrics and visualizations are introduced to validate the models and assess the performance, efficiency, and consistency of latent maps generated by VAE, which have been utilized in prior studies for latent space cartography and used as a benchmark in this study, and the emerging TFT architecture under various configurations. These analyses provide actionable insights for model parameter tuning and reliability improvements. Comparative results highlight that TFT achieves shorter run times and superior scalability to diverse time-series data shapes compared to VAE. This work advances fault diagnosis in multivariate time series, fostering explainable AI to support critical system operations.
Additive manufacturing (AM) is revolutionizing the production of custom components with complex internal geometries, essential for high-performance applications in diverse fields such as medicine and defense. These AM parts optimize strength while minimizing weight by utilizing internal lattice structures consisting of large quantities of small interconnected struts. However, the complexity of these structures, combined with the challenges of using X-ray Computed Tomography (XCT) data, makes validation of part reliability difficult. This ultimately inhibits the development of novel parts for our collaborating material scientists. Here, we introduce LatticeAnalytics, a novel framework specifically designed for visual inspection of defects in these lattice structures. Our framework offers an end-to-end solution that includes the data management of XCT scans, enables remote access for geographically dispersed teams through a web-based dashboard, and incorporates novel visualizations. Our analysis is facilitated by a coarse alignment between the lattice’s nominal model, a spatial graph, and the XCT data. We employ a simple VR-based approach for fast and rough alignment, followed by an offline registration and identification of the struts. With the nodes and struts aligned and identified in the volume, our framework allows querying of subvolumes containing a single strut at multiple resolutions. This avoids computation over the entire lattice and also allow for easy parallelization of down-stream computations, such as strut-specific metrics. To depict a fast overview of the strut quality, we introduce two innovative visual encodings, crucial for our collaborators’ research in creating novel AM parts: the Contour View and the Roughness Map, which depict critical geometrical and surface features of individual struts in standardized two 2D views. We evaluated the integrated system through expert interviews. The feedback confirms the framework’s practicality and its effectiveness in enhancing current inspection workflows. It solves major bottlenecks for our collaborators, ultimately helping them create novel parts with advanced properties.
Visualization—the use of visual elements to explore data, form hypotheses, or convey conclusions—is an integral part of the scientific process. Starting from an initial exploration of new data to illustrating outcomes for the general public, visualization is one of the most intuitive and powerful modes of communication. With the explosion of new data sources and types, unprecedented volumes of data, and new technologies, such as virtual reality (VR) and artificial intelligence (AI), visualization has become increasingly essential but also ever more challenging. The Department of Energy’s (DOE) Office of Advanced Scientific Computing Research (ASCR) sponsored a Basic Research Needs workshop in January 2022 to understand the major opportunities and grand challenges in visualization tools and technologies for scientific computing as well as for DOE-relevant applications and goals in general. The workshop identified five priority research directions (PRDs) for visualization to support scientific discovery, decision making, and communication. The first three PRDs describe interconnected research themes addressing the need for new techniques to deal with complex data, uncertainty, and interpretability (PRD 1); the need for scalable and interoperable software stacks (PRD 2); and the challenges and opportunities inherent in new technologies, such as VR, cloud, or exascale computing (PRD 3). The remaining two PRDs describe foundational research themes that recognize the potential of visualizations to provide equitable access to information and to strengthen the scientific discourse (PRD 4); and the need to consider human factors when designing visualizations (PRD 5). Collectively, these PRDs form the pillars for a coherent, long-term research and development strategy in Visualization for Scientific Discovery, Decision-Making, and Communication in the context of the Office of Science’s mission scope.