Results for “optimization platform” — Page 92

DOE OSTI2023

Evaluating performance and portability of high-level programming models: Julia, Python/Numba, and Kokkos on exascale nodes

We explore the performance and portability of the high-level programming models: the LLVM-based Julia and Python/Numba, and Kokkos on high-performance computing (HPC) nodes: AMD Epyc CPUs and MI250X graphical processing units (GPUs) on Frontier’s test bed Crusher system and Ampere’s Arm-based CPUs and NVIDIA’s A100 GPUs on the Wombat system at the Oak Ridge Leadership Computing Facilities. We compare the default performance of a hand-rolled dense matrix multiplication algorithm on CPUs against vendor-compiled C/OpenMP implementations, and on each GPU against CUDA and HIP. Rather than focusing on the kernel optimization per-se, we select this naive approach to resemble exploratory work in science and as a lower-bound for performance to isolate the effect of each programming model. Julia and Kokkos perform comparably with C/OpenMP on CPUs, while Julia implementations are competitive with CUDA and HIP on GPUs. Performance gaps are identified on NVIDIA A100 GPUs for Julia’s single precision and Kokkos, and for Python/Numba in all scenarios. We also comment on half-precision support, productivity, performance portability metrics, and platform readiness. We expect to contribute to the understanding and direction for high-level, high-productivity languages in HPC as the first-generation exascale systems are deployed.

Godoy, William↗

DOE OSTI2016

Image Processing Occupancy Sensor

The Image Processing Occupancy Sensor, or IPOS, is a novel sensor technology developed at the National Renewable Energy Laboratory (NREL). The sensor is based on low-cost embedded microprocessors widely used by the smartphone industry and leverages mature open-source computer vision software libraries. Compared to traditional passive infrared and ultrasonic-based motion sensors currently used for occupancy detection, IPOS has shown the potential for improved accuracy and a richer set of feedback signals for occupant-optimized lighting, daylighting, temperature setback, ventilation control, and other occupancy and location-based uses. Unlike traditional passive infrared (PIR) or ultrasonic occupancy sensors, which infer occupancy based only on motion, IPOS uses digital image-based analysis to detect and classify various aspects of occupancy, including the presence of occupants regardless of motion, their number, location, and activity levels of occupants, as well as the illuminance properties of the monitored space. The IPOS software leverages the recent availability of low-cost embedded computing platforms, computer vision software libraries, and camera elements.

Source record↗

DOE OSTI2024

Discovery Science and Inertial Fusion Energy Research at the Jupiter Laser Facility (Research Performance Progress Report)

The goal of this project is to provide operational support to run the Jupiter Laser Facility within the LaserNetUS network to achieve the following four objectives: • Develop new science, techniques, and platforms for discovery science and IFE research, in partnership with academia, other LaserNetUS nodes, and the greater community. • Advance the development of secondary sources of photons and particles for applications relevant to discovery science and IFE; • Serve as a testbed for new laser, optical, target, and diagnostic capabilities that will advance IFE; • Attract, train, and retain talent in high-energy-density and laser science that will be essential in furthering development of IFE, and help build new collaborations between national laboratory and academic researchers. We have accomplished our four objectives by: • Providing access to the three JLF platforms (Titan, Janus, and COMET) to LaserNetUS users after their proposals have been independently reviewed and ranked by the LaserNetUS PRP; • Providing expertise and technical capabilities to support focused science research thrusts at the facility; • Promoting and maintaining technical relationships and collaborations with other members of the LaserNetUS community to nurture and grow the discovery science and IFE workforce— especially students and early career scientists—on LaserNetUS facilities. • Augmenting JLF with specific improvements while coordinating efforts with LLNL organizations and collaborators to provide users with optimal laser, target, and diagnostic resources to help them maximize technical impact.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2020

Potential for Applying Continuous Directed Evolution to Plant Enzymes: An Exploratory Study

Plant evolution has produced enzymes that may not be optimal for maximizing yield and quality in today’s agricultural environments and plant biotechnology applications. By improving enzyme performance, it should be possible to alleviate constraints on yield and quality currently imposed by kinetic properties or enzyme instability. Enzymes can be optimized more quickly than naturally possible by applying directed evolution, which entails mutating a target gene in vitro and screening or selecting the mutated gene products for the desired characteristics. Continuous directed evolution is a more efficient and scalable version that accomplishes the mutagenesis and selection steps simultaneously in vivo via error-prone replication of the target gene and coupling of the host cell’s growth rate to the target gene’s function. However, published continuous systems require custom plasmid assembly, and convenient multipurpose platforms are not available. We discuss two systems suitable for continuous directed evolution of enzymes, OrthoRep in Saccharomyces cerevisiae and EvolvR in Escherichia coli, and our pilot efforts to adapt each system for high-throughput plant enzyme engineering. To test our modified systems, we used the thiamin synthesis enzyme THI4, previously identified as a prime candidate for improvement. Our adapted OrthoRep system shows promise for efficient plant enzyme engineering.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

The Model System Saccharomyces cerevisiae Versus Emerging Non-Model Yeasts for the Production of Biofuels

Microorganisms are effective platforms for the production of a variety of chemicals including biofuels, commodity chemicals, polymers and other natural products. However, deep cellular understanding is required for improvement of current biofuel cell factories to truly transform the Bioeconomy. Modifications in microbial metabolic pathways and increased resistance to various types of stress caused by the production of these chemicals are crucial in the generation of robust and efficient production hosts. Recent advances in systems and synthetic biology provide new tools for metabolic engineering to design strategies and construct optimal biocatalysts for the sustainable production of desired chemicals, especially in the case of ethanol and fatty acid production. Yeast is an efficient producer of bioethanol and most of the available synthetic biology tools have been developed for the industrial yeast Saccharomyces cerevisiae. Non-conventional yeast systems have several advantageous characteristics that are not easily engineered such as ethanol tolerance, low pH tolerance, thermotolerance, inhibitor tolerance, genetic diversity and so forth. Currently, synthetic biology is still in its initial steps for studies in non-conventional yeasts such as Yarrowia lipolytica, Kluyveromyces marxianus, Issatchenkia orientalis and Pichia pastoris. Therefore, the development and application of advanced synthetic engineering tools must also focus on these underexploited, non-conventional yeast species. Herein, we review the basic synthetic biology tools that can be applied to the standard S. cerevisiae model strain, as well as those that have been developed for non-conventional yeasts. In addition, we will discuss the recent advances employed to develop non-conventional yeast strains that are efficient for the production of a variety of chemicals through the use of metabolic engineering and synthetic biology.

09 BIOMASS FUELS↗

NASA NTRS2011

Current-Sensitive Path Planning for an Underactuated Free-Floating Ocean Sensorweb

This work investigates multi-agent path planning in strong, dynamic currents using thousands of highly under-actuated vehicles. We address the specific task of path planning for a global network of ocean-observing floats. These submersibles are typified by the Argo global network consisting of over 3000 sensor platforms. They can control their buoyancy to float at depth for data collection or rise to the surface for satellite communications. Currently, floats drift at a constant depth regardless of the local currents. However, accurate current forecasts have become available which present the possibility of intentionally controlling floats' motion by dynamically commanding them to linger at different depths. This project explores the use of these current predictions to direct float networks to some desired final formation or position. It presents multiple algorithms for such path optimization and demonstrates their advantage over the standard approach of constant-depth drifting.

oceanography↗

DOE OSTI2026

Smart Energy Storage Integration and Management Platform for Buildings (SESIMP-B)

This project involved the design, development, and testing of a commercial smart service panel. It includes an innovative AI-driven control method to manage smart functions of the panel and a technical-economic feasibility assessment for enhancing building energy resilience and grid-edge technology integration.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2025

Ultra‐Flexible Pixelated Perovskite Photodetectors Enabled by Honeycomb Polymer Grids for High‐Resolution Imaging

Abstract A nature‐inspired fabrication method based on a photolithography‐free flexible polymer grid is reported for high‐resolution pixelation of perovskite photodiode arrays with exceptional mechanical ductility and a morphology resembling that of natural compound eyes. The resulting pixelated perovskite photosensitive layer has a ≈1 µm pixel size with 2000 Pixels per inch (PPI) resolution when fully assembled as a photodetector array, delivering a detectivity of >10 13 Jones while providing cross‐talk free imaging. Using a polymer grid effectively releases stress on the perovskite platform, greatly increasing the mechanical agility of the otherwise brittle perovskite film. This novel fabrication methodology and device design offer new possibilities for applications in robotics, biomedical imaging, and virtual and augmented reality.

Zheng, Ding [Department of Chemistry and the Mater↗

DOE OSTI2018

Analytical Cost Metrics : Days of Future Past

As we move towards the exascale era, the new architectures must be capable of running the massive computational problems efficiently. Scientists and researchers are continuously investing in tuning the performance of extreme-scale computational problems. These problems arise in almost all areas of computing, ranging from big data analytics, artificial intelligence, search, machine learning, virtual/augmented reality, computer vision, image/signal processing to computational science and bioinformatics. With Moore’s law driving the evolution of hardware platforms towards exascale, the dominant performance metric (time efficiency) has now expanded to also incorporate power/energy efficiency. Therefore the major challenge that we face in computing systems research is: “how to solve massive-scale computational problems in the most time/power/energy efficient manner?”

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Discovery of a weak topological insulating state and van Hove singularity in triclinic RhBi2

Abstract Time reversal symmetric (TRS) invariant topological insulators (TIs) fullfil a paradigmatic role in the field of topological materials, standing at the origin of its development. Apart from TRS protected strong TIs, it was realized early on that more confounding weak topological insulators (WTI) exist. WTIs depend on translational symmetry and exhibit topological surface states only in certain directions making it significantly more difficult to match the experimental success of strong TIs. We here report on the discovery of a WTI state in RhBi 2 that belongs to the optimal space group P $$\bar{1}$$ 1 ¯ , which is the only space group where symmetry indicated eigenvalues enumerate all possible invariants due to absence of additional constraining crystalline symmetries. Our ARPES, DFT calculations, and effective model reveal topological surface states with saddle points that are located in the vicinity of a Dirac point resulting in a van Hove singularity (VHS) along the (100) direction close to the Fermi energy ( E F ). Due to the combination of exotic features, this material offers great potential as a material platform for novel quantum effects.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Solving the Bernstein-Vazirani problem using Majorana-based topological quantum algorithms

Executing quantum algorithms using Majorana zero modes—a major milestone for the field of topological quantum computing—requires a platform that can be scaled to large quantum registers, can be controlled in real time and space, and a braiding protocol that uses the unique properties of these exotic particles. Here, we demonstrate the first successful simulation of a Majorana-based, fault-tolerant quantum algorithm to solve the Bernstein-Vazirani problem in two-dimensional magnet-superconductor hybrid structures from initialization to read-out of the final many-body state. Utilizing the Majorana zero modes’ topological properties, we introduce an optimized braiding protocol for the algorithm and a scalable architecture for its implementation with an arbitrary number of qubits. We visualize the algorithm protocol in real time and space by computing the non-equilibrium density of states, which is proportional to the time-dependent differential conductance, and the non-equilibrium charge density, which assigns a unique signature to each final state of the algorithm.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2019

Engineered Pseudomonas putida KT2440 co-utilizes galactose and glucose

Abstract Background Efficient conversion of plant biomass to commodity chemicals is an important challenge that needs to be solved to enable a sustainable bioeconomy. Deconstruction of biomass to sugars and lignin yields a wide variety of low molecular weight carbon substrates that need to be funneled to product. Pseudomonas putida KT2440 has emerged as a potential platform for bioconversion of lignin and the other components of plant biomass. However, P. putida is unable to natively utilize several of the common sugars in hydrolysate streams, including galactose. Results In this work, we integrated a De Ley–Doudoroff catabolic pathway for galactose catabolism into the chromosome of P. putida KT2440, using genes from several different organisms. We found that the galactonate catabolic pathway alone (DgoKAD) supported slow growth of P. putida on galactose. Further integration of genes to convert galactose to galactonate and to optimize the transporter expression level resulted in a growth rate of 0.371 h −1 . Additionally, the best-performing strain was demonstrated to co-utilize galactose with glucose. Conclusions We have engineered P. putida to catabolize galactose, which will allow future engineered strains to convert more plant biomass carbon to products of interest. Further, by demonstrating co-utilization of glucose and galactose, continuous bioconversion processes for mixed sugar streams are now possible.

09 BIOMASS FUELS↗

DOE OSTI2026

Scalable foundation models for numerical simulations on HPC platforms

In recent years, foundation models (FMs) have begun to reshape numerical simulations on high-performance computing (HPC) platforms. These large, pre-trained AI models enable rapid predictions across a broad range of physical domains, including Earth system modeling, fluid dynamics, materials science, as well as complex multi-modal simulations in aerospace engineering and fusion research. By training on diverse datasets, FMs learn intricate relationships and underlying physical behavior while also enabling the quantification of uncertainty in their predictions. This capability allows simulations that once required days of numerical calculation to be completed in minutes (FM inference), supporting real-time design optimization, uncertainty-aware decision making, and more comprehensive exploration of complex scenarios.

AI↗

NASA NTRSDate not supplied

Radiation-Hard Parallel Readout Circuit for Low-Frequency Voltage Signal Measurements

NASA Goddard Space Flight Center (GSFC) has successfully developed and tested a custom-designed low-noise multi-channel digitizer (MCD) application specific integrated circuit (ASIC) for operation in harsh radiation environments. The MCD-ASIC is optimized for low-frequency and low-voltage signal measurements from sensors and transducers. It has 20 input channels where each channel is comprised of auto-zeroed chopper variable-gain amplifier, post amplifier, and a second order ∑∆ modulator. ∑∆ analog-to-digital converter (ADC) relies on oversampling and noise shaping to achieve high-resolution conversion. However, the MCD-ASIC requires digital filtering and decimation to convert the output single bit streams from the ADC to useful data words. A parallel digital platform such as a field-programmable-gate-array (FPGA) is highly suitable to fully leverage the capabilities of the MCD-ASIC. The FPGA controls the MCD-ASIC via serial peripheral interface (SPI) protocol and acquires data from it. A Python-script communicates with the FPGA board through a USB interface on a cross operating platform. Using this architecture, the system is capable of monitoring up to 20 voltage readout channels simultaneously in a real-time manner. Each channel’s parameters can be programmed independently allowing maximum user versatility. In this paper, we present analysis of the analog front-end, the implementation of the digital processing unit on the FPGA, and provide noise performance results from the MCD-ASIC readout.

ASIC↗

NASA NTRSDate not supplied

Innovative Features of NASA's Celestial Mapping System to Support Exploration in the Lunar South Pole

Introduction: NASA's Celestial Mapping System (CMS) is developed to address the need for 3D tools for planetary science investigations, mission planning, in-situ operations, in a 3D-first design constructed around a unified view of a planetary globe. At present CMS provides many critical functionalities that include 1) Equipment planning and optimized placement on Lunar surface 2) Line of sight (visibility ) analysis 3) Powerful measurement tools based on 3D terrain with realistic 3D models to represent rovers, astronauts and equipment 4) Visualization of de-rived mapping products (e.g. resource maps), and 5) Data engine for hosting new observations that are not available in other contemporary lunar data tools. CMS is built on the foundation of powerful NASA WorldWind globe engines. In near future, users will be able to simultaneously deploy CMS onto multiple hardware configurations and platforms such as Windows, Linux, iOS and Android. The users will also have the flexibility to update to the latest imagery and terrain datasets as they are being acquired (in real time) before and/or during the exploration mission. CMS is also capable of consumption and analysis of data from locally hosted and external sources. It supports Open Geospatial Consorti-um (OGC) data and file standards, with current integrations of datasets from the Astrogeology Science Center of USGS which include global and local data acquired from NASA (LRO, Clementine, Lunar Orbiter) and JAXA (SELENE/Kaguya) with the capability of integrating more datasets. With development experience in both the end-user application and planetary engine side, CMS is also able to adapt to newer Lunar cartography standards as they develop and become recognized by international geospatial panels. Overcoming Polar Distortions: 3D geospatial applications traditionally suffer from significant distortion of imagery at the poles due to following reasons – 1) distortions in the source imagery 2) Incompatible tessellation algorithm on the poles 3) map projections. In the lunar context, with the focus on the South pole, this is not acceptable. The CMS team is researching ways to address polar distortion of imagery with new tessellation algorithms and by reprojecting the data using projections that are more accurate in polar scenarios. Figure1 shows the potential error introduced by different tessellation methods, represented by the red and green circles for Shoemaker crater. There is ~2 Km difference in the placement of the crater. Line of Sight Analysis and Traverse Planning: We have developed a built-in line of sight analysis (LOS) tool in CMS that analyzes the terrain profile and obstructions and provides the visibility of a given terrain for a remote observer. Figure 2 shows the viewshed analysis on the PSR in Nobile region. The PSR was created with help of HORUS generated images. The yellow pin shows the observer location outside the PSR. The yellow area shows the visible part of PSR. The obstructed area with no visibility for the observer is shown in red. This analysis was ex-tended further to set different heights for various observers and then perform the viewshed analysis. Combining the different visibility profiles can help designing improved traverses within the crater.

Geospatial Mapping↗

NASA NTRSDate not supplied

Innovative Features of NASA's Celestial Mapping System to Support Exploration in the Lunar South Pole

Introduction: NASA's Celestial Mapping System (CMS) is developed to address the need for 3D tools for planetary science investigations, mission planning, in-situ operations, in a 3D-first design constructed around a unified view of a planetary globe. At present CMS provides many critical functionalities that include 1) Equipment planning and optimized placement on Lunar surface 2) Line of sight (visibility ) analysis 3) Powerful measurement tools based on 3D terrain with realistic 3D models to represent rovers, astronauts and equipment 4) Visualization of de-rived mapping products (e.g. resource maps), and 5) Data engine for hosting new observations that are not available in other contemporary lunar data tools. CMS is built on the foundation of powerful NASA WorldWind globe engines. In near future, users will be able to simultaneously deploy CMS onto multiple hardware configurations and platforms such as Windows, Linux, iOS and Android. The users will also have the flexibility to update to the latest imagery and terrain datasets as they are being acquired (in real time) before and/or during the exploration mission. CMS is also capable of consumption and analysis of data from locally hosted and external sources. It supports Open Geospatial Consorti-um (OGC) data and file standards, with current integrations of datasets from the Astrogeology Science Center of USGS which include global and local data acquired from NASA (LRO, Clementine, Lunar Orbiter) and JAXA (SELENE/Kaguya) with the capability of integrating more datasets. With development experience in both the end-user application and planetary engine side, CMS is also able to adapt to newer Lunar cartography standards as they develop and become recognized by international geospatial panels. Overcoming Polar Distortions: 3D geospatial applications traditionally suffer from significant distortion of imagery at the poles due to following reasons – 1) distortions in the source imagery 2) Incompatible tessellation algorithm on the poles 3) map projections. In the lunar context, with the focus on the South pole, this is not acceptable. The CMS team is researching ways to address polar distortion of imagery with new tessellation algorithms and by reprojecting the data using projections that are more accurate in polar scenarios. Figure1 shows the potential error introduced by different tessellation methods, represented by the red and green circles for Shoemaker crater. There is ~2 Km difference in the placement of the crater. Line of Sight Analysis and Traverse Planning: We have developed a built-in line of sight analysis (LOS) tool in CMS that analyzes the terrain profile and obstructions and provides the visibility of a given terrain for a remote observer. Figure 2 shows the viewshed analysis on the PSR in Nobile region. The PSR was created with help of HORUS generated images. The yellow pin shows the observer location outside the PSR. The yellow area shows the visible part of PSR. The obstructed area with no visibility for the observer is shown in red. This analysis was ex-tended further to set different heights for various observers and then perform the viewshed analysis. Combining the different visibility profiles can help designing improved traverses within the crater.

Geospatial Mapping↗

DOE OSTI2018

Target tracking via recursive Bayesian state estimation in cognitive radar networks

To cope with complicated environments and stealthier targets, incorporating intelligence and cognition cycles into target tracking is of great importance in modern sensor network management. With remarkable advances in sensor techniques and deployable platforms, a sensing system has freedom to select a subset of available radars, plan their trajectories, and transmit designed waveforms. In this paper, we propose a general framework for single target tracking in cognitive networks of radars, including consideration of waveform design, path planning, and radar selection, which are separately but not jointly taken into account in existing work. The tracking procedure, built on the theories of dynamic graphical models (DGM) and recursive Bayesian state estimation (RBSE), is formulated as two iterative steps: (i) solving a combinatorial optimization problem to select the optimal subset of radars, waveforms, and locations for the next tracking instant, and (ii) acquiring the recursive Bayesian state estimation to accurately track the target. Further, an illustrative example introduces a specific scenario in 2-D space. Simulation results based on the scenario demonstrate that the proposed framework can accurately track the target under the management of the network of radars.

47 OTHER INSTRUMENTATION↗

DOE OSTI2017

Active Site and Electronic Structure Elucidation of Pt Nanoparticles Supported on Phase-Pure Molybdenum Carbide Nanotubes

Here, we recently showed that phase-pure molybdenum carbide nanotubes can be durable supports for platinum (Pt) nanoparticles in hydrogen evolution reaction (HER). In this paper we further characterize surface properties of the same Pt/β-Mo 2 C catalyst platform using carbon monoxide (CO)-Pt and CO-Mo 2 C bond strength of different Pt particle sizes in the <3 nm range. Results from diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) and temporal analysis of products (TAP) revealed the existence of different active sites as Pt particle size increases. Correlation between the resultant catalyst activity and deposited Pt particle size was further investigated using water–gas-shift (WGS) as a probe reaction, suggesting that precise control of particle diameter and thickness is needed for optimized catalytic activity.

36 MATERIALS SCIENCE↗