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An Infrastructure for HPC Knowledge Sharing and Reuse
Abstract not provided
OpenK: An Open Infrastructure for the Accumulation, Sharing and Reuse of High Performance Computing Knowledge
In high performance computing (HPC), often a wide range of knowledge about the particular domains, software applications, and hardware architectures are necessary for applying the right optimizations in the appropriate contexts. In today’s practice, however, such knowledge has been expressed and managed in an ad-hoc manner by each individual. Systematic accumulation, sharing and reuse of the knowledge across a broad community has been difficult. This paper introduces OpenK, an ontology-based open infrastructure for solving the problem. By centering around ontology – a generic knowledge representation – and extensible designs, it offers a promising support for lowering the barriers.
A Stochastic Calculus Approach to Boltzmann Transport
Traditional Monte Carlo methods for particle transport utilize source iteration to express the solution, the flux density, of the transport equation as a Neumann series. Our contribution is to show that the particle paths simulated within source iteration are associated with the adjoint flux density and the adjoint particle paths are associated with the flux density. Here, we make our assertion rigorous through the use of stochastic calculus by representing the particle path used in source iteration as a solution to a stochastic differential equation (SDE). The solution to the adjoint Boltzmann equation is then expressed in terms of the same SDE, and the solution to the Boltzmann equation is expressed in terms of the SDE associated with the adjoint particle process. An important consequence is that the particle paths used within source iteration simultaneously provide Monte Carlo samples of the flux density and adjoint flux density in the detector and source regions, respectively. The significant practical implication is that particle trajectories can be reused to obtain both forward and adjoint quantities of interest. To the best our knowledge, the reuse of entire particles paths has not appeared in the literature. Monte Carlo simulations are presented to support the reuse of the particle paths.
Water reuse for sustainable microalgae cultivation: current knowledge and future directions
Microalgae hold great promise as environmentally sustainable sources of food, animal feed, and fuel. However, large amounts of water are used during microalgae cultivation and this negatively impacts economic viability and environmental sustainability. Reusing cultivation water can reduce the direct impacts of water usage and also reduce nutrient requirements and algal wastewater treatment. However, studies have shown that algae growth in reused water can be compromised, unaffected, or sometimes enhanced compared to controls. This review examines recent studies on water reuse to qualitatively understand these varied effects. Growth inhibitors and stimulators in reused water and their underlying mechanisms are discussed, as well as recent pre-treatment technologies and factors affecting the quality of reused water, such as microalgae taxa, culture conditions, and harvesting methods, are considered. A scheme is proposed for water reuse and harvesting methods based on the desired algal end products. Finally, taking these findings together, here we provide recommendations for further research directions as well as new insights into designing and integrating a cultivation strategy with a harvesting platform to reuse water for more efficient microalgae cultivation.
KM-IT Mobile Platform for D and D - 18300
Knowledge management (KM) is the practice or process responsible for gathering, analyzing, storing and sharing insights, experiences, knowledge, and information within an organization or community. The main focus of the Knowledge Management Information Tool (KM-IT) for the deactivation and decommissioning (D and D) community is to enhance safety through improved efficiencies (e.g., by reducing the need to rediscover the knowledge and experience gained over time and to promote the reuse of the existing knowledge). KM-IT serves as a centralized information repository and a common interface for D and D related activities. It facilitates the gathering, analysis, storage and sharing of knowledge and information within the D and D community. FIU has developed eight active modules as part of the web-based mobile application for the KM-IT, which can be accessed from m.dndkm.org: Vendor, Specialist Directory, Technology, Picture Library, Hotline, Lessons Learned, Best Practices and Fixatives. All of the mobile modules are scaled-down versions of the desktop module available at www.dndkm.org and publish data from the KM-IT database to the D and D community. FIU has recently developed a native mobile application for Android mobile devices for selecting D and D fixatives. This application runs natively on mobile devices and displays data through the fixative services which uses REST-based API for communication across mobile platforms. Xamarin Forms are used to develop the front-end application for the Android operating system (OS) and will be used for future platforms (iOS and Windows) as well. The native fixative application can be installed on mobile devices to search information related to fixatives, decontamination gels and strippable coatings applicable to D and D. The KM-IT platform includes a comprehensive database of commercially available fixatives and other contamination control products. Search functionality allows the user to filter and sort these products according to the search criteria or keyword. Three levels of refinement are available via a drill down menu for the criteria. (authors)
MARSAME Radiological Release Report for Metal Items from Technical Area 53, Set 28
Environmental Protection and Compliance, Environmental Stewardship Group (EPC-ES) has evaluated the survey results for metal items from the Los Alamos Neutron Science Center (LANSCE) at Technical Area 53 (TA-53) and found that the metal items described in Table 1 of this report (identified by Radiation Protection [RP] Tracking Numbers) meet the criteria for unrestricted release under Department of Energy (DOE) Order 458.1 Chg 4, Radiation Protection of the Public and the Environment (DOE 2020) and can be recycled. This conclusion is based on the known history of the metal items and radiation survey data (see the completed RP-Form-031 LANSCE Metals Clearance Log [LANL 2021a] for each item in Attachment 1). Process knowledge indicates that items were released from radiological areas, including radiation areas, prior to the implementation of the 2000 metals moratorium. Therefore, the items are considered unencumbered and are not subject to the moratorium suspension on metal recycling from DOE facilities. Additionally, Los Alamos National Laboratory (LANL) has determined that there is no practical opportunity for internal DOE reuse of this metal. Process knowledge indicates that these metal items were unlikely to ever be in direct contact with the beam and thus are unlikely to have become activated. Surface contamination measurements (both total and removable) showed either no detectable radioactivity or activity levels within the range of background. All measurements for volumetric contamination were indistinguishable from background based on calculated decision limits. Additionally, all gamma isotopic surveys conducted for defense-in depth showed no identifiable gamma radiation from beam activation.
Charting the unknown: A dive into the world of standards mapping
When you hear standards mapping what do you think about? For the Secure Software Central (SSC) project this means comparing our process to the National Institute of Standards and Technology’s (NIST) security control catalog. So how is it done? The project completed this summer can be broken down into three simple phases. Phase one consists of mapping the SSC process to the NIST’s security control catalog. While phase two entails mapping mitigations from a threat profile to NIST. Lastly phase three requires the creation of a knowledge base allowing for the reuse of controls across numerous projects This project presented a few different challenges: locating the correct control within the NIST catalog while correctly matching the proposed mitigations from the SSC team, accurately leveling the mitigation to the security level of the system, creating a toolbox to showcase a dataset of mitigations and standards to be used in current and future projects. each challenge allowed for opportunities in growth and understanding of how security controls can map to a governing set of standards. These standards maps are a crucial element to support the insights provided by the SSC team and allow the client to have confidence in the work being completed. My internship has allowed me to set and achieve many goals such as coming to understand that the field of cybersecurity truly is the right place for me. I have also learned that it’s ok to be wrong if you learn something from it. For significant accomplishments I have helped integrate standards mapping into the fabric of SSC. The field experience that I have gained such as interacting with the SSC team along with other senior staff and building a good rapport are crucial skills to. This time at PNNL has been an irreplaceable experience.
MARSAME Radiological Release Report for Metal Items from Technical Area 53, Set 26
Environmental Protection and Compliance, Environmental Stewardship Group (EPC-ES) has evaluated the survey results for metal items from the Los Alamos Neutron Science Center (LANSCE) at Technical Area 53 (TA-53) and found that the metal items described in Table 1 of this report (identified by Radiation Protection [RP] Tracking Numbers) meet the criteria for unrestricted release under Department of Energy (DOE) Order 458.1 Chg 4, Radiation Protection of the Public and the Environment (DOE 2020) and can be recycled. This conclusion is based on the known history of the metal items and radiation survey data. None of the items in this report are located within radiological areas. Therefore, the items are considered unencumbered and are not subject to the moratorium suspension on metal recycling from DOE facilities. Additionally, Los Alamos National Laboratory (LANL) has determined that there is no practical opportunity for internal DOE reuse of this metal. Process knowledge indicates that these metal items were unlikely to ever be in direct contact with the beam and thus are unlikely to have become activated. Surface contamination measurements (both total and removable) showed either no detectable radioactivity or activity levels within the range of background. All measurements for volumetric contamination were indistinguishable from background based on calculated decision limits. Additionally, all gamma isotopic surveys conducted for defense-in depth showed no identifiable gamma radiation from beam activation.
Centralized Interactive Phenomics Resource: an integrated online phenomics knowledgebase for health data users
Development of clinical phenotypes from electronic health records (EHRs) can be resource intensive. Several phenotype libraries have been created to facilitate reuse of definitions. However, these platforms vary in target audience and utility. Here, we describe the development of the Centralized Interactive Phenomics Resource (CIPHER) knowledgebase, a comprehensive public-facing phenotype library, which aims to facilitate clinical and health services research. The platform was designed to collect and catalog EHR-based computable phenotype algorithms from any healthcare system, scale metadata management, facilitate phenotype discovery, and allow for integration of tools and user workflows. Phenomics experts were engaged in the development and testing of the site. The knowledgebase stores phenotype metadata using the CIPHER standard, and definitions are accessible through complex searching. Phenotypes are contributed to the knowledgebase via webform, allowing metadata validation. Data visualization tools linking to the knowledgebase enhance user interaction with content and accelerate phenotype development. The CIPHER knowledgebase was developed in the largest healthcare system in the United States and piloted with external partners. The design of the CIPHER website supports a variety of front-end tools and features to facilitate phenotype development and reuse. Health data users are encouraged to contribute their algorithms to the knowledgebase for wider dissemination to the research community, and to use the platform as a springboard for phenotyping. CIPHER is a public resource for all health data users available at https://phenomics.va.ornl.gov/ which facilitates phenotype reuse, development, and dissemination of phenotyping knowledge.
MARSAME Radiological Release Report for Metal Items from TA 53- Set 16
EPC-ES has evaluated the survey results for metal items from the Los Alamos Neutron Science Center (LANSCE) and found that the metal items described in Table 1 of this report (identified by RP Tracking Numbers) meet the criteria for unrestricted release under DOE Order 458.1 Radiation Protection of the Public and the Environment and can be recycled. This conclusion is based on the known history of the metal items and on radiation survey data (see the completed RP-Form-036 LANSCE Metals Clearance Log for each item). None of the items in this report are located within radiological areas. Therefore, the items are considered unencumbered and are not subject to the moratorium suspension on metal recycling from Department of Energy facilities. Additionally, LANL has determined that there is no practical opportunity for internal DOE reuse or recycling of this metal. Process knowledge indicates that these metal items were unlikely to ever be in direct contact with the beam and thus are unlikely to have become activated. Surface contamination measurements (both total and removable) showed either no detectable radioactivity or activity levels within the range of background. All measurements for volumetric contamination were indistinguishable from background based on calculated decision limits. Additionally, all gamma isotopic surveys conducted for defense in depth showed no identifiable gamma radiation from beam activation.
MARSAME Radiological Release Report for Metal Items from TA 53, Set 20
EPC-ES has evaluated the survey results for metal items from the Los Alamos Neutron Science Center (LANSCE) and found that the metal items described in Table 1 of this report (identified by RP Tracking Numbers) meet the criteria for unrestricted release under DOE Order 458.1 Radiation Protection of the Public and the Environment (DOE 2020) and can be recycled. This conclusion is based on the known history of the metal items and on radiation survey data (see the completed RP-Form-031 LANSCE Metals Clearance Log for each item). None of the items in this report are located within radiological areas. Therefore, the items are considered unencumbered and are not subject to the moratorium suspension on metal recycling from Department of Energy facilities. Additionally, LANL has determined that there is no practical opportunity for internal DOE reuse or recycling of this metal. Process knowledge indicates that these metal items were unlikely to ever be in direct contact with the beam and thus are unlikely to have become activated. Surface contamination measurements (both total and removable) showed either no detectable radioactivity or activity levels within the range of background. All measurements for volumetric contamination were indistinguishable from background based on calculated decision limits. Additionally, all gamma isotopic surveys conducted for defense-in-depth showed no identifiable gamma radiation from beam activation.
MARSAME Radiological Release Report for Metal Items from TA 53, Set 22
EPC-ES has evaluated the survey results for metal items from the Los Alamos Neutron Science Center (LANSCE) and found that the metal items described in Table 1 of this report (identified by RP Tracking Numbers) meet the criteria for unrestricted release under DOE Order458.1 Radiation Protection of the Public and the Environment (DOE 2020) and can be recycled. This conclusion is based on the known history of the metal items and on radiation survey data (see the completed RP-Form-031 LANSCE Metals Clearance Log [LANL 2021a] for each item). None of the items in this report are located within radiological areas. Therefore, the items are considered unencumbered and are not subject to the moratorium suspension on metal recycling from Department of Energy facilities. Additionally, LANL has determined that there is no practical opportunity for internal DOE reuse or recycling of this metal. Process knowledge indicates that these metal items were unlikely to ever bein direct contact with the beam and thus are unlikely to have become activated. Surface contamination measurements (both total and removable) showed either no detectable radioactivity or activity levels within the range of background. All measurements for volumetric contamination were indistinguishable from background based on calculated decision limits. Additionally, all gamma isotopic surveys conducted for defense-in-depth showed no identifiable gamma radiation from beam activation.
Emerging Trends in Biological Treatment of Wastewater From Unconventional Oil and Gas Extraction
Unconventional oil and gas exploration generates an enormous quantity of wastewater, commonly referred to as flowback and produced water (FPW). Limited freshwater resources and stringent disposal regulations have provided impetus for FPW reuse. Organic and inorganic compounds released from the shale/brine formation, microbial activity, and residual chemicals added during hydraulic fracturing bestow a unique as well as temporally varying chemical composition to this wastewater. Studies indicate that many of the compounds found in FPW are amenable to biological degradation, indicating biological treatment may be a viable option for FPW processing and reuse. This review discusses commonly characterized contaminants and current knowledge on their biodegradability, including the enzymes and organisms involved. Further, a perspective on recent novel hybrid biological treatments and application of knowledge gained from omics studies in improving these treatments is explored.
AWB-GCN: A Graph Convolutional Network Accelerator with Runtime Workload Rebalancing
The recent development of deep learning has been mostly focusing on Euclidean data, such as images, videos, audios, etc. However, most real-world information and relation are often expressed as graphs. To efficiently learn from graph data, graph convolutional networks (GCNs) emerge as a promising approach, showing advantages in several practical applications such as social network analysis, knowledge discovery, 3D modeling, motion capturing, etc. Real-world graphs are usually extremely large and imbalanced, posting significant performance demand and design challenges on the hardware dedicated for GCN inference. In this paper, we propose an architecture design called UW-GCN to accelerate graph convolutional network inference. To tackle the major performance bottleneck from workload imbalance, we propose dynamic neighborhood stealing and remote chunk shuffling techniques, relying on hardware flexibility to achieve hardware auto-tuning under negligible area or delay overhead. Specifically, UW-GCN is able to smartly profile the sparse graph pattern while continuously adjusting the workload distribution via routing reconfiguration among parallel processing elements (PEs). The ideal configuration is then reused in the remaining iterations. To the best of our knowledge, this is the first accelerator design particularly for GCN and the first work relying on hardware auto-tuning, which is normally based on software, to achieve near-optimal workload balance in processing sparse structures.
Integrative Modeling and Analysis of Fungal Central Carbon Metabolism
Over a thousand fungal genomes have been sequenced, yet manually curated genome-scale metabolic models (GEMs) are available for only a limited number of species. Moreover, these models have often been developed independently, leading to inconsistencies in namespaces, compartment definitions, and pathway representations that hinder comparative analysis, the systematic reuse of prior curation efforts, and the integration of consolidated metabolic knowledge. Here, we present the Consolidated Fungal Core Metabolism Model (CFCMM), constructed by integrating thirteen published fungal models spanning Ascomycota, Mucoromycota, and both Crabtree-positive and Crabtree-negative yeasts. We harmonized metabolites and reactions into a non-redundant shared ModelSEED ontological space, standardized compartmentalization, and refined gene–protein–reaction (GPR) rules. Using pathway-level visualization and systematic gap detection, we further improved the integrated network through literature-guided curation to correct stoichiometry, stereospecificity, and pathway architecture. Orthologous protein family reconstruction and functional annotation workflows were used to validate and inform GPR associations, with particular emphasis on ambiguous enzyme superfamilies and membrane-associated components. Using the resulting CFCMM, we built high-quality central carbon core models for each fungus and performed flux balance analysis to quantify ATP-yield variation under aerobic and anaerobic conditions, explicitly evaluating scenarios driven by differences in electron transport chain (ETC) composition. Simulations reproduced the expected fermentative yield of approximately 2 mmol ATP per mmol glucose under anaerobic conditions and separated the thirteen fungi into two bioenergetic groups under aerobic respiration based on Complex I status, with predicted yields of approximately 30 versus 22 mmol ATP per mmol glucose. Forcing flux through the alternative oxidase bypass further reduced ATP yields to approximately 12 and 4 mmol ATP per mmol glucose in Complex I-containing and Complex I-lacking fungi, respectively. Collectively, this work provides a manually curated, ModelSEED-consistent, and extensible fungal core metabolic template, deployed in DOE KBase as a resource for automated reconstruction of central carbon core models from any sequenced fungal genome. In addition, the CFCMM provides modular components for developing GEMs with more accurate energy predictions and enables robust comparative analyses of fungal bioenergetics and core metabolic diversity
Why don't we share data and code? Perceived barriers and benefits to public archiving practices
The biological sciences community is increasingly recognizing the value of open, reproducible and transparent research practices for science and society at large. Despite this recognition, many researchers fail to share their data and code publicly. This pattern may arise from knowledge barriers about how to archive data and code, concerns about its reuse, and misaligned career incentives. Here, we define, categorize and discuss barriers to data and code sharing that are relevant to many research fields. We explore how real and perceived barriers might be overcome or reframed in the light of the benefits relative to costs. By elucidating these barriers and the contexts in which they arise, we can take steps to mitigate them and align our actions with the goals of open science, both as individual scientists and as a scientific community.
DaCe - Data Centric Parallel Programming
DaCe is a parallel programming framework that takes code in Python/NumPy and other programming languages, and maps it to high-performance CPU, GPU, and FPGA programs, which can be optimized to achieve state-of-the-art. Internally, DaCe uses the Stateful DataFlow multiGraph (SDFG) data-centric intermediate representation: A transformable, interactive representation of code based on data movement. Since the input code and the SDFG are separate, it is possible to optimize a program without changing its source, so that it stays readable. On the other hand, transformations are customizable and user-extensible, so they can be written once and reused in many applications. With data-centric parallel programming, we enable direct knowledge transfer of performance optimization, regardless of the application or the target processor.