Human Research Program at NASA Glenn Research Center
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Systematic Evaluation of Backdoor Data Poisoning Attacks on Image Classifiers
Backdoor data poisoning attacks have recently been demonstrated in computer vision research as a potential safety risk for machine learning (ML) systems. Traditional data poisoning attacks manipulate training data to induce unreliability of an ML model, whereas backdoor data poisoning attacks maintain system performance unless the MLmodel is presented with an input containing an embedded“trigger” that provides a predetermined response advantageous to the adversary. Our work builds upon prior back-door data-poisoning research for ML image classifiers and systematically assesses different experimental conditions including types of trigger patterns, persistence of trigger patterns during retraining, poisoning strategies, architectures (ResNet-50, NasNet, NasNet-Mobile), datasets (Flowers, CIFAR-10), and potential defensive regularization techniques (Contrastive Loss, Logit Squeezing, Manifold Mixup,Soft-Nearest-Neighbors Loss). Experiments yield four key findings. First, the success rate of backdoor poisoning at-tacks varies widely, depending on several factors, including model architecture, trigger pattern and regularization technique. Second, we find that poisoned models are hard to detect through performance inspection alone. Third, regularization typically reduces backdoor success rate, although it can have no effect or even slightly increase it, depending on the form of regularization. Finally, backdoors inserted through data poisoning can be rendered ineffective after just a few epochs of additional training on a small set of clean data without affecting the model’s performance.
Truong, Loc T.↗
Bringing OpenCL to Commodity RISC-V CPUs
The importance of open-source hardware has been increasing in recent years with the introduction of the RISC-V Open ISA. This has also accelerated the push for support of the open-source software stack from compiler tools to full-blown operating systems. Parallel computing with today’s Application Programming Interfaces such as OpenCL has proven to be effective at leveraging the parallelism in commodity multi-core processors and programmable parallel accelerators. However, to the best of our knowledge, there is currently no publicly available implementation of OpenCL targeting commodity RISC-V processors that is accessible to the open-source community. Besides opening RISC-V to the existing rich variety of scientific parallel applications, OpenCL also provides access to a unique genre of benchmarks useful in computer architecture research. In this work, we extended an Open-source implementation of OpenCL to target RISC-V CPUs. Our work not only cover commodity multi-core RISC-V processors, but also plethora of low- profile embedded RISC-V CPUs that often do not support atomic instructions or multi-threading.
Tine, Blaise↗
Evaluating HPC Kernels for Processing in Memory
Memory subsystems contribute significantly to the performance and energy efficiency of high-performance computing (HPC) applications. Traditional memory technologies with conventional organization (e.g., DRAM) are struggling to keep up with the increasing memory requirements of modern applications. Techniques such as multilayer cache hierarchy and out-of-order execution are still falling short of mitigating the penalty incurred by memory accesses. Processing-in-memory (PIM), which involves moving memory-intensive kernels to memory for execution instead of bringing the data to the processing unit, is emerging as a promising technique. PIM has recently received traction among computer architecture researchers, and the increasing research activity surrounding this technique indicates its potential to alleviate main memory performance bottlenecks. In this paper, we characterize and identify memory-intensive HPC kernels, perform a first-order evaluation of the PIM technique for selected HPC kernels, quantify performance deviation, and analyze the key factors that affect PIM efficiency.
Asifuzzaman, Kazi↗
Emergent properties of magnons coupled to microwave photons (Final Technical Report)
Studying the emergent properties of hybrid quantum material platforms holds great promise for advancing quantum technologies and transforming our ability to control quantum mechanical interactions. A key development in recent years is the recognition that magnons – the elementary quanta of spin waves – can serve as fundamental building blocks in quantum systems. Understanding the mechanisms behind the generation and control of hybrid quasiparticles based on magnons could pave the way for engineering new materials for quantum coherent processing and quantum computing. This research project focused on the precise control of light-matter interactions in magnetic hybrid systems and nanostructures, where light is carried by microwave photons and matter by magnons in engineered magnetic metamaterials. Furthermore, we investigated hybridized magnon interactions in magnetic nanostructures and devices. To this end, the project has developed new measurement techniques and systematically studied novel material systems for efficient magnon-photon coupling. A key focus was uncovering the fundamental mechanisms governing magnon-photon and magnon-phonon interactions – critical for utilizing magnons as coherent information transducers between carriers. Specifically, this research addressed: 1. Investigate the dispersion and collective properties of magnon hybrid systems in new material systems. 2. Develop magnonic hybrids with non-zero wavevectors and achieve effective control of magnon-polariton properties through engineered magnonic behaviors. 3. Determine how spin-orbit torques interact with electromagnetic fields in the strong coupling regime. This work generated new insights into the physics of magnonic hybrid systems and their emergent properties by broadening the range of material platforms and measurement techniques used to study magnon-photon and magnon-magnon coupling. The findings deepen our understanding of magnon-polaritons and lay the groundwork for novel spintronic devices with potential applications in quantum information science.
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
Developing Capabilities in Physical and Computational Sciences
The Physical and Computational Sciences Directorate (PCSD) performs fundamental research in support of the science missions of Offices of Basic Energy Sciences (BES), Advanced Scientific Computing Research (ASCR), High Energy Physics (HEP), Nuclear Physics (NP), and Fusion Energy Sciences (FES), and others within the domains of the chemical, materials, computational sciences, mathematics, and physics. This LDRD project aims to provide funding to develop/demonstrate research capabilities for proposals and publications to support these science missions. Staff will propose small research tasks/projects to be performed under this overall project.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
The design of research and development policy
Computer simulation and dynamics of management planning in research and development projects
MANAGEMENT PLANNING↗
Fierro Version 2.x
FIERRO is a parallel C++ code designed to simulate fluid mechanics, heat transfer, and solid mechanics in two- and three-dimensional space. FIERRO is written to run on homogeneous (CPU) and heterogeneous (CPU+GPU) high performance computing machines. Fierro can aid a) modeling and design efforts that have historically relied on commercial implicit and explicit finite element codes, b) numerical methods research, c) manufacturing research, and d) computer science research. The code contains diverse numerical methods to solve the governing physics equations for both quasi-static and dynamic problems. Mathematical optimization solvers are coupled to the numerical methods to research topology and shape optimization that has application to additive manufacturing, and to create novel numerical approaches. Phase-field methods with micromechanical solvers are provided to simulate microstructure formation and evolution in manufacturing processes. The micromechanical solvers can also help research efforts create continuum-scale constitutive models for solids, as a function of the microstructure, in situ in a calculation or in a stand-alone manner. No physical data exists within the code.
Morgan, Nathaniel↗
Fierro
FIERRO is a parallel C++ code designed to simulate fluid mechanics, heat transfer, and solid mechanics in two- and three dimensional space. FIERRO is written to run on homogeneous (CPU) and heterogeneous (CPU+GPU) high performance computing machines. Fierro can aid a) modeling and design efforts that have historically relied on commercial implicit and explicit finite element codes, b) numerical methods research, c) manufacturing research, and d) computer science research. The code contains diverse numerical methods to solve the governing physics equations for both quasi-static and dynamic problems. Mathematical optimization solvers are coupled to the numerical methods to research topology and shape optimization that has application to additive manufacturing, and to create novel numerical approaches. Phase-field methods with micromechanical solvers are provided to simulate microstructure formation and evolution in manufacturing processes. The micromechanical solvers can also help research efforts create continuum-scale constitutive models for solids, as a function of the microstructure, in situ in a calculation or in a stand-alone manner. No physical data exists within the code.
Morgan, Nathaniel↗
RIACS FY2002 Annual Report
The Research Institute for Advanced Computer Science (RIACS) carries out basic research and technology development in computer science, in support of the National Aeronautics and Space Administration's missions. Operated by the Universities Space Research Association (a non-profit university consortium), RIACS is located at the NASA Ames Research Center, Moffett Field, California. It currently operates under a multiple year grant/cooperative agreement that began on October 1, 1997 and is up for renewal in September 2003. Ames has been designated NASA's Center of Excellence in Information Technology. In this capacity, Ames is charged with the responsibility to build an Information Technology (IT) Research Program that is preeminent within NASA. RIACS serves as a bridge between NASA Ames and the academic community, and RIACS scientists and visitors work in close collaboration with NASA scientists. RIACS has the additional goal of broadening the base of researchers in these areas of importance to the nation's space and aeronautics enterprises. RIACS research focuses on the three cornerstones of IT research necessary to meet the future challenges of NASA missions: 1) Automated Reasoning for Autonomous Systems; 2) Human-Centered Computing; and 3) High Performance Computing and Networking. In addition, RIACS collaborates with NASA scientists to apply IT research to a variety of NASA application domains including aerospace technology, earth science, life sciences, and astrobiology. RIACS also engages in other activities, such as workshops, seminars, visiting scientist programs and student summer programs, designed to encourage and facilitate collaboration between the university and NASA IT research communities.
Leiner, Barry M.↗
Hollow cathodes as electron emitting plasma contactors Theory and computer modeling
Several researchers have suggested using hollow cathodes as plasma contactors for electrodynamic tethers, particularly to prevent the Shuttle Orbiter from charging to large negative potentials. Previous studies have shown that fluid models with anomalous scattering can describe the electron transport in hollow cathode generated plasmas. An improved theory of the hollow cathode plasmas is developed and computational results using the theory are compared with laboratory experiments. Numerical predictions for a hollow cathode plasma source of the type considered for use on the Shuttle are presented, as are three-dimensional NASCAP/LEO calculations of the emitted ion trajectories and the resulting potentials in the vicinity of the Orbiter. The computer calculations show that the hollow cathode plasma source makes vastly superior contact with the ionospheric plasma compared with either an electron gun or passive ion collection by the Orbiter.
Davis, V. A.↗
Research Projects, Technical Reports and Publications
The Research Institute for Advanced Computer Science (RIACS) was established by the Universities Space Research Association (USRA) at the NASA Ames Research Center (ARC) on June 6, 1983. RIACS is privately operated by USRA, a consortium of universities with research programs in the aerospace sciences, under contract with NASA. The primary mission of RIACS is to provide research and expertise in computer science and scientific computing to support the scientific missions of NASA ARC. The research carried out at RIACS must change its emphasis from year to year in response to NASA ARC's changing needs and technological opportunities. A flexible scientific staff is provided through a university faculty visitor program, a post doctoral program, and a student visitor program. Not only does this provide appropriate expertise but it also introduces scientists outside of NASA to NASA problems. A small group of core RIACS staff provides continuity and interacts with an ARC technical monitor and scientific advisory group to determine the RIACS mission. RIACS activities are reviewed and monitored by a USRA advisory council and ARC technical monitor. Research at RIACS is currently being done in the following areas: Advanced Methods for Scientific Computing High Performance Networks During this report pefiod Professor Antony Jameson of Princeton University, Professor Wei-Pai Tang of the University of Waterloo, Professor Marsha Berger of New York University, Professor Tony Chan of UCLA, Associate Professor David Zingg of University of Toronto, Canada and Assistant Professor Andrew Sohn of New Jersey Institute of Technology have been visiting RIACS. January 1, 1996 through September 30, 1996 RIACS had three staff scientists, four visiting scientists, one post-doctoral scientist, three consultants, two research associates and one research assistant. RIACS held a joint workshop with Code 1 29-30 July 1996. The workshop was held to discuss needs and opportunities in basic research in computer science in and for NASA applications. There were 14 talks given by NASA, industry and university scientists and three open discussion sessions. There were approximately fifty participants. A proceedings is being prepared. It is planned to have similar workshops on an annual basis. RIACS technical reports are usually preprints of manuscripts that have been submitted to research 'ournals or conference proceedings. A list of these reports for the period January i 1, 1996 through September 30, 1996 is in the Reports and Abstracts section of this report.
Oliger, Joseph↗
FAIR Surrogate Benchmarks Supporting AI and Simulation Research (Final Report)
Computational Science is being revolutionized by integrating AI and simulation and, in particular, by deep learning surrogate models that can replace all or part of traditional large‐scale HPC computations. Such surrogates can achieve remarkable performance improvements, as much as several orders of magnitude, and save both compute time and energy. The Surrogate Benchmark Initiative (SBI) project creates a community repository and FAIR (Findable, Accessible, Interoperable, and Reusable) data ecosystem for HPC application surrogate benchmarks. The SBI team comes from Argonne National Laboratory (ANL), Indiana University (IU), Rutgers University, the University of Tennessee, Knoxville (UTK), and the University of Virginia (UVA). SBI repositories include data, code, and all relevant collateral artifacts that the science and engineering community need to use and reuse these data sets and surrogates. SBI repositories generate active research from both the participants in SBI and the broad community of AI and domain scientists. This project develops surrogates that use several different neural nets to learn and quickly infer the results of simulations and data systems and captures them as surrogate benchmarks with a rich set of metadata covering: Data; Model; Metrics specification; Machine specification; and Science, Speed, and Power Results. We research FAIR metadata for these benchmarks. We develop application surrogate examples as benchmarks across many fields (ANL, UTK, IU, UVA). We also study non-Surrogate benchmarks that have many common features and similar issues as regards FAIRness. We work with MLCommons (UVA, UTK), which is a major machine learning benchmarking activity where we get metadata ontologies, software, and benchmarks, Benchmarks have datasets, models, and metadata and they need a technical framework developed by UTK and Rutgers and deployed by UVA. We study features of Surrogates including performance, training set size, and uncertainty quantification (Rutgers, UVA and IU).
97 MATHEMATICS AND COMPUTING↗
Computational engine structural analysis
A significant research activity at the NASA Lewis Research Center is the computational simulation of complex multidisciplinary engine structural problems. This simulation is performed using computational engine structural analysis (CESA) which consists of integrated multidisciplinary computer codes in conjunction with computer post-processing for problem-specific application. A variety of the computational simulations of specific cases are described in some detail in this paper. These case studies include: (1) aeroelastic behavior of bladed rotors, (2) high velocity impact of fan blades, (3) blade-loss transient response, (4) rotor/stator/squeeze-film/bearing interaction, (5) blade-fragment/rotor-burst containment, and (6) structural behavior of advanced swept turboprops. These representative case studies are selected to demonstrate the breath of the problems analyzed and the role of the computer including post-processing and graphical display of voluminous output data.
Chamis, C. C.↗
Computational engine structural analysis
A significant research activity at the NASA Lewis Research Center is the computational simulation of complex multidisciplinary engine structural problems. This simulation is performed using computational engine structural analysis (CESA) which consists of integrated multidisciplinary computer codes in conjunction with computer post-processing for problem-specific application. A variety of the computational simulations of specific cases are described in some detail in this paper. These case studies include: (1) aeroelastic behavior of bladed rotors, (2) high velocity impact of fan blades, (3) blade-loss transient response, (4) rotor/stator/squeeze-film/bearing interaction, (5) blade-fragment/rotor-burst containment, and (6) structural behavior of advanced swept turboprops. These representative case studies are selected to demonstrate the breath of the problems analyzed and the role of the computer including post-processing and graphical display of voluminous output data.
Chamis, C. C.↗
Exploratory research for the development of a computer aided software design environment with the software technology program
Field studies were conducted by MCC to determine areas of research of mutual interest to MCC and JSC. NASA personnel from the Information Systems Directorate and research faculty from UHCL/RICIS visited MCC in Austin, Texas to examine tools and applications under development in the MCC Software Technology Program. MCC personnel presented workshops in hypermedia, design knowledge capture, and design recovery on site at JSC for ISD personnel. The following programs were installed on workstations in the Software Technology Lab, NASA/JSC: (1) GERM (Graphic Entity Relations Modeler); (2) gIBIS (Graphic Issues Based Information System); and (3) DESIRE (Design Recovery tool). These applications were made available to NASA for inspection and evaluation. Programs developed in the MCC Software Technology Program run on the SUN workstation. The programs do not require special configuration, but they will require larger than usual amounts of disk space and RAM to operate properly.
Hardwick, Charles↗
X-Ray Micro-Computed Tomography of Apollo Samples as a Curation Technique Enabling Better Research
X-ray micro-computed tomography (micro-CT) is a technique that has been used to research meteorites for some time and many others], and recently it is becoming a more common tool for the curation of meteorites and Apollo samples. Micro-CT is ideally suited to the characterization of astromaterials in the curation process as it can provide textural and compositional information at a small spatial resolution rapidly, nondestructively, and without compromising the cleanliness of the samples (e.g., samples can be scanned sealed in Teflon bags). This data can then inform scientists and curators when making and processing future sample requests for meteorites and Apollo samples. Here we present some preliminary results on micro-CT scans of four Apollo regolith breccias. Methods: Portions of four Apollo samples were used in this study: 14321, 15205, 15405, and 60639. All samples were 8-10 cm in their longest dimension and approximately equant. These samples were micro-CT scanned on the Nikon HMXST 225 System at the Natural History Museum in London. Scans were made at 205-220 kV, 135-160 microamps beam current, with an effective voxel size of 21-44 microns. Results: Initial examination of the data identify a variety of mineral clasts (including sub-voxel FeNi metal grains) and lithic clasts within the regolith breccias. Textural information within some of the lithic clasts was also discernable. Of particular interest was a large basalt clast (approx.1.3 cc) found within sample 60639, which appears to have a sub-ophitic texture. Additionally, internal void space, e.g., fractures and voids, is readily identifiable. Discussion: It is clear from the preliminary data that micro-CT analyses are able to identify important "new" clasts within the Apollo breccias, and better characterize previously described clasts or igneous samples. For example, the 60639 basalt clast was previously believed to be quite small based on its approx.0.5 sq cm exposure on the surface of the main mass. These scans show the clast to be approx.4.5 g, however (assuming a density of approx.3.5 g/cc). This is large enough for detailed studies including multiple geo-chronometers. This basalt clast is of particular interest as it is the largest Apollo 16 basalt, and it is the only mid-TiO2 basalt in the Apollo sample suite. By identifying the location of interesting clasts or grains within a sample, we will be able to make more informed decisions about where to cut a sample in order to best expose clasts of interest for future study. Moreover, knowing the location of internal defects (e.g., fractures) will allow more precise chipping and extraction of clasts or grains. By combining micro-CT scans with compositional techniques like micro x-ray fluorescence (particularly on sawn slabs), we will be able to provide even more comprehensive information to scientists trying to best select samples that fit their scientific needs.
Ziegler, R. A.↗
Input Waste Stream Modeling for Trash Management, Recycling, and Manufacturing Processes
Astronaut waste is an important aspect of the planning and execution of long-term crewed missions, especially to the Moon and Mars. However, as new technologies arise and mission planning evolves, the projected composition of the waste similarly evolves. This poses a problem for researchers who are investigating various approaches to mitigating crew waste, since the investigation of each new waste-mitigation technology typically uses a static waste composition that is based on a simulant developed at the time of the research; several such waste simulants have been developed over recent years. To mitigate the ‘moving target’ aspect of crew waste composition and use, researchers at NASA KSC have developed a computational tool wherein researchers can adjust the composition of the crew waste, as well as other important parameters such as crew size, mission duration, and waste mitigation method (e.g., incineration, compaction, jettison, etc.). The computational tool then returns important mission metrics such as waste-related mass reduction, power consumed, water produced or consumed, elemental mass balance, and available feedstock for in-space manufacturing (ISM) applications. This tool can then be used to adjust aspects of a waste model (e.g., removal of metal aluminum (Al) for ISM applications) and determine an associated set of metrics in order to inform mission planning.
Ray Pitts↗