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Information Power Grid: Distributed High-Performance Computing and Large-Scale Data Management for Science and Engineering

We use the term "Grid" to refer to distributed, high performance computing and data handling infrastructure that incorporates geographically and organizationally dispersed, heterogeneous resources that are persistent and supported. This infrastructure includes: (1) Tools for constructing collaborative, application oriented Problem Solving Environments / Frameworks (the primary user interfaces for Grids); (2) Programming environments, tools, and services providing various approaches for building applications that use aggregated computing and storage resources, and federated data sources; (3) Comprehensive and consistent set of location independent tools and services for accessing and managing dynamic collections of widely distributed resources: heterogeneous computing systems, storage systems, real-time data sources and instruments, human collaborators, and communications systems; (4) Operational infrastructure including management tools for distributed systems and distributed resources, user services, accounting and auditing, strong and location independent user authentication and authorization, and overall system security services The vision for NASA's Information Power Grid - a computing and data Grid - is that it will provide significant new capabilities to scientists and engineers by facilitating routine construction of information based problem solving environments / frameworks. Such Grids will knit together widely distributed computing, data, instrument, and human resources into just-in-time systems that can address complex and large-scale computing and data analysis problems. Examples of these problems include: (1) Coupled, multidisciplinary simulations too large for single systems (e.g., multi-component NPSS turbomachine simulation); (2) Use of widely distributed, federated data archives (e.g., simultaneous access to metrological, topological, aircraft performance, and flight path scheduling databases supporting a National Air Space Simulation systems}; (3) Coupling large-scale computing and data systems to scientific and engineering instruments (e.g., realtime interaction with experiments through real-time data analysis and interpretation presented to the experimentalist in ways that allow direct interaction with the experiment (instead of just with instrument control); (5) Highly interactive, augmented reality and virtual reality remote collaborations (e.g., Ames / Boeing Remote Help Desk providing field maintenance use of coupled video and NDI to a remote, on-line airframe structures expert who uses this data to index into detailed design databases, and returns 3D internal aircraft geometry to the field); (5) Single computational problems too large for any single system (e.g. the rotocraft reference calculation). Grids also have the potential to provide pools of resources that could be called on in extraordinary / rapid response situations (such as disaster response) because they can provide common interfaces and access mechanisms, standardized management, and uniform user authentication and authorization, for large collections of distributed resources (whether or not they normally function in concert). IPG development and deployment is addressing requirements obtained by analyzing a number of different application areas, in particular from the NASA Aero-Space Technology Enterprise. This analysis has focussed primarily on two types of users: the scientist / design engineer whose primary interest is problem solving (e.g. determining wing aerodynamic characteristics in many different operating environments), and whose primary interface to IPG will be through various sorts of problem solving frameworks. The second type of user is the tool designer: the computational scientists who convert physics and mathematics into code that can simulate the physical world. These are the two primary users of IPG, and they have rather different requirements. The results of the analysis of the needs of these two types of users provides a broad set of requirements that gives rise to a general set of required capabilities. The IPG project is intended to address all of these requirements. In some cases the required computing technology exists, and in some cases it must be researched and developed. The project is using available technology to provide a prototype set of capabilities in a persistent distributed computing testbed. Beyond this, there are required capabilities that are not immediately available, and whose development spans the range from near-term engineering development (one to two years) to much longer term R&D (three to six years). Additional information is contained in the original.

Johnston, William E.

Lessons Learned in the Implementation of a Training Knowledge Management System for the SERVIR Network

The SERVIR program is a unique partnership between NASA, the U.S. Agency for International Development (USAID), focusing on building capacity to use Earth observations for addressing development challenges. In that context, between 2004 and 2020, the program delivered approximately 365 trainings to almost 10,000 professionals. More recently, between November 2020 and August 2021, the SERVIR network executed some 55 training events addressing SERVIR’s 4 priority thematic areas, and roughly a quarter of SERVIR trainings overall have focused on themes related to Ecological Forecasting. Due to the ongoing COVID-19 pandemic, almost four-fifths of recent training events have been virtual, with the remainder being in-person under limited circumstances. The large number of training events delivered represents both an opportunity and a challenge in terms of knowledge management. While the training materials developed can later be reused in other parts of the SERVIR network, prior to recently, the lack of a central repository for those materials has prevented wider dissemination and use. The recently developed Training Knowledge Management System (TKMS) is now becoming an integral part of the SERVIR Capacity Building Framework, supporting the exchange of resources and methods for conducting training activities across the network. This presentation focuses on the structure of this system, as well as on the anticipated benefits for the User Communities for Earth Observations of Terrestrial Systems.

training

A Virtual Mission Operations Center: Collaborative Environment

The Virtual Mission Operations Center - Collaborative Environment (VMOC-CE) intent is to have a central access point for all the resources used in a collaborative mission operations environment to assist mission operators in communicating on-site and off-site in the investigation and resolution of anomalies. It is a framework that as a minimum incorporates online chat, realtime file sharing and remote application sharing components in one central location. The use of a collaborative environment in mission operations opens up the possibilities for a central framework for other project members to access and interact with mission operations staff remotely. The goal of the Virtual Mission Operations Center (VMOC) Project is to identify, develop, and infuse technology to enable mission control by on-call personnel in geographically dispersed locations. In order to achieve this goal, the following capabilities are needed: Autonomous mission control systems Automated systems to contact on-call personnel Synthesis and presentation of mission control status and history information Desktop tools for data and situation analysis Secure mechanism for remote collaboration commanding Collaborative environment for remote cooperative work The VMOC-CE is a collaborative environment that facilitates remote cooperative work. It is an application instance of the Virtual System Design Environment (VSDE), developed by NASA Goddard Space Flight Center's (GSFC) Systems Engineering Services & Advanced Concepts (SESAC) Branch. The VSDE is a web-based portal that includes a knowledge repository and collaborative environment to serve science and engineering teams in product development. It is a "one stop shop" for product design, providing users real-time access to product development data, engineering and management tools, and relevant design specifications and resources through the Internet. The initial focus of the VSDE has been to serve teams working in the early portion of the system/product lifecycle - concept development, proposal preparation, and formulation. The VMOC-CE expands the application of the VSDE into the operations portion of the system lifecycle. It will enable meaningful and real-time collaboration regardless of the geographical distribution of project team members. Team members will be able to interact in satellite operations, specifically for resolving anomalies, through access to a desktop computer and the Internet. Mission Operations Management will be able to participate and monitor up to the minute status of anomalies or other mission operations issues. In this paper we present the VMOC-CE project, system capabilities, and technologies.

Medina, Barbara

Bundle Data Approach at GES DISC Targeting Natural Hazards

Severe natural phenomena such as hurricane, volcano, blizzard, flood and drought have the potential to cause immeasurable property damages, great socioeconomic impact, and tragic loss of human life. From searching to assessing the Big, i.e., massive and heterogeneous scientific data (particularly, satellite and model products) in order to investigate those natural hazards, it has, however, become a daunting task for Earth scientists and applications researchers, especially during recent decades. The NASA Goddard Earth Sciences Data and Information Service Center (GES DISC) has served Big Earth science data, and the pertinent valuable information and services to the aforementioned users of diverse communities for years. In order to help and guide our users to online readily (i.e., with a minimum effort) acquire their requested data from our enormous resource at GES DISC for studying their targeted hazard event, we have thus initiated a Bundle Data approach in 2014, first targeting the hurricane event topic. We have recently worked on new topics such as volcano and blizzard. The bundle data of a specific hazard event is basically a sophisticated integrated data package consisting of a series of proper datasets containing a group of relevant (knowledge--based) data variables readily accessible to users via a system-prearranged table linking those data variables to the proper datasets (URLs). This online approach has been developed by utilizing a few existing data services such as Mirador as search engine; Giovanni for visualization; and OPeNDAP for data access, etc. The online Data Cookbook site at GES DISC is the current host for the bundle data. We are now also planning on developing an Automated Virtual Collection Framework that shall eventually accommodate the bundle data, as well as further improve our management in Big Data.

GES DISC

Virtualizing Resources for the Application Services and Framework Team

Virtualization is an emerging technology that will undoubtedly have a major impact on the future of Information Technology. It allows for the centralization of resources in an enterprise system without the need to make any changes to the host operating system, file system, or registry. In turn, this significantly reduces cost and administration, and provides a much greater level of security, compatibility, and efficiency. This experiment examined the practicality, methodology, challenges, and benefits of implementing the technology for the Launch Control System (LCS), and more specifically the Application Services (AS) group of the National Aeronautics and Space Administration (NASA) at the Kennedy Space Center (KSC). In order to carry out this experiment, I used several tools from the virtualization company known as VMWare; these programs included VMWare ThinApp, VMWare Workstation, and VMWare ACE. Used in conjunction, these utilities provided the engine necessary to virtualize and deploy applications in a desktop environment on any Windows platform available. The results clearly show that virtualization is a viable technology that can, when implemented properly, dramatically cut costs, enhance stability and security, and provide easier management for administrators.

Varner, Justin T.

Rapid Spacecraft Payload Development: In-Orbit Demonstration of Flight Software Reuse, Scalability, and Dependability

As space mission design trends towards shared, multi-mission platforms and high-performance onboard computing architectures, the number of spacecraft launched into operation is also steadily rising. Through ridesharing, spacecraft miniaturization, and other cost-reduction measures, the barriers to space are lowering, resulting in compounded growth in the amount of flight software being deployed. To meet the needs of both the growing quantity and evolving nature of spacecraft, flight software design must accordingly adapt to support more efficient development, solutions to computational resource-sharing, and software reusability. This paper focuses on a software payload demonstrating several core technologies that improve the state-of-the-art in these identified areas. Launched into low-earth orbit in January 2022, our software payload was conceived, designed, and delivered in a span of merely two months. It was developed on top of the NASA core Flight System (cFS) framework and the Distributed Spacecraft Autonomy (DSA) Comm cFS application, which translates cFS software bus messages across a Data Distribution Service (DDS) network. The flight software, packaged in Linux container images, was deployed as one of 18 flight applications managed through the Unibap SpaceCloud Framework. The applications were run on a Unibap iX5-102 radiation-tolerant payload computer, hosted on the D-Orbit SCV-004 spacecraft as part of an ESA-sponsored in-orbit technology test. Our payload, referred to as the DSA D-Orbit software, demonstrates the reusability of the DSA Comm app in a substantially different context and purpose as its original mission. Comm’s original design goal was to reliably distribute messages between spacecraft swarms of arbitrary size and dynamic network topology. However, we leverage this same functionality to introduce redundancy and opportunistic parallel data processing in the context of a representative onboard image processing workload. This adaptive mission architecture was enabled in part by the SpaceCloud Framework’s use of container virtualization as the payload integration interface. By using a base container image with common high-level language runtimes and libraries, we were able to rapidly design, develop, and validate our image processing application without many of the technological barriers common to flight software development. We present details the goals, approach, results, and lessons learned through this technology demonstration experiment and contextualize those observations against present and future challenges in spacecraft software development.

computer programming

MERRA Analytic Services: Meeting the Big Data Challenges of Climate Science Through Cloud-enabled Climate Analytics-as-a-service

Climate science is a Big Data domain that is experiencing unprecedented growth. In our efforts to address the Big Data challenges of climate science, we are moving toward a notion of Climate Analytics-as-a-Service (CAaaS). We focus on analytics, because it is the knowledge gained from our interactions with Big Data that ultimately produce societal benefits. We focus on CAaaS because we believe it provides a useful way of thinking about the problem: a specialization of the concept of business process-as-a-service, which is an evolving extension of IaaS, PaaS, and SaaS enabled by Cloud Computing. Within this framework, Cloud Computing plays an important role; however, we it see it as only one element in a constellation of capabilities that are essential to delivering climate analytics as a service. These elements are essential because in the aggregate they lead to generativity, a capacity for self-assembly that we feel is the key to solving many of the Big Data challenges in this domain. MERRA Analytic Services (MERRAAS) is an example of cloud-enabled CAaaS built on this principle. MERRAAS enables MapReduce analytics over NASAs Modern-Era Retrospective Analysis for Research and Applications (MERRA) data collection. The MERRA reanalysis integrates observational data with numerical models to produce a global temporally and spatially consistent synthesis of 26 key climate variables. It represents a type of data product that is of growing importance to scientists doing climate change research and a wide range of decision support applications. MERRAAS brings together the following generative elements in a full, end-to-end demonstration of CAaaS capabilities: (1) high-performance, data proximal analytics, (2) scalable data management, (3) software appliance virtualization, (4) adaptive analytics, and (5) a domain-harmonized API. The effectiveness of MERRAAS has been demonstrated in several applications. In our experience, Cloud Computing lowers the barriers and risk to organizational change, fosters innovation and experimentation, facilitates technology transfer, and provides the agility required to meet our customers' increasing and changing needs. Cloud Computing is providing a new tier in the data services stack that helps connect earthbound, enterprise-level data and computational resources to new customers and new mobility-driven applications and modes of work. For climate science, Cloud Computing's capacity to engage communities in the construction of new capabilies is perhaps the most important link between Cloud Computing and Big Data.

Data Analytics