Results for “HPC storage” | Engineering Papers

NASA NTRS2018

Evolving Storage and Cyber Infrastructure at the NASA Center for Climate Simulation

This talk will describe recent developments at the NASA Center for Climate Simulation, which is funded by NASAs Science Mission Directorate, and supports the specialized data storage and computational needs of weather, ocean, and climate researchers, as well as astrophysicists, heliophysicists, and planetary scientists. To meet requirements for higher-resolution, higher-fidelity simulations, the NCCS augments its High Performance Computing (HPC) and storage retrieval environment. As the petabytes of model and observational data grow, the NCCS is broadening data services offerings and deploying and expanding virtualization resources for high performance analytics.

Cyberinfrastructure↗

NASA NTRS1993

Improvement in HPC performance through HIPPI RAID storage

In 1986, RAID (redundant array of inexpensive (or independent) disks) technology was introduced as a viable solution to the I/O bottleneck. A number of different RAID levels were defined in 1987 by the Computer Science Division (EECS) University of California, Berkeley, each with specific advantages and disadvantages. With multiple RAID options available, taking advantage of RAID technology required matching particular RAID levels with specific applications. It was not possible to use one RAID device to address all applications. Maximum Strategy's Gen 4 Storage Server addresses this issue with a new capability called programmable RAID level partitioning. This capability enables users to have multiple RAID levels coexist on the same disks, thereby providing the versatility necessary for multiple concurrent applications.

Homan, Blake↗

NASA NTRS2019

Dynamic Analysis of the STARC-ABL Propulsion System

In the pursuit of Electrified Aircraft Propulsion (EAP), much of the attention is on the development of hybrid electric concept vehicles and their propulsion systems from a steady state performance perspective. While it is steady-state performance that largely determines the efficiency of civil air transports, engine operability and transient performance define constraints for the steady state design that impact efficiency and system viability. Neglecting dynamics and control technologies can result in an over-designed, sub optimal propulsion system or a concept that is not feasible. Thus, dynamic system studies were conducted on the propulsion system of the conceptual aircraft design known as the Single-aisle Turboelectric AiRCraft with Aft Boundary Layer propulsor (STARC-ABL). This paper describes the development of a controller to verify the baseline concept's feasibility from an operability perspective. Further, studies were conducted to identify excessive stability margin in the baseline design that could be traded for potential benefits in efficiency through an engine re design. This study revealed the potential to reduce the high pressure compressor (HPC) stall margin by 3%. Finally, a study was conducted to investigate the potential benefit of adding energy storage to the STARC-ABL concept that further improves operability and enables more gains in engine efficiency and performance. The energy storage provided an additional 0.5% stall margin can be removed from the HPC.

STARC-ABL↗

NASA NTRS2019

Dynamic Analysis of the STARC-ABL Propulsion System

In the pursuit of Electrified Aircraft Propulsion (EAP), much of the attention is on the development of hybrid electric concept vehicles and their propulsion systems from a steady state performance perspective. While it is steady-state performance that largely determines the efficiency of civil air transports, engine operability and transient performance define constraints for the steady state design that impact efficiency and system viability. Neglecting dynamics and control technologies can result in an over-designed, sub optimal propulsion system or a concept that is not feasible. Thus, dynamic system studies were conducted on the propulsion system of the conceptual aircraft design known as the Single-aisle Turboelectric AiRCraft with Aft Boundary Layer propulsor (STARC-ABL). This paper describes the development of a controller to verify the baseline concept's feasibility from an operability perspective. Further, studies were conducted to identify excessive stability margin in the baseline design that could be traded for potential benefits in efficiency through an engine re design. This study revealed the potential to reduce the high pressure compressor (HPC) stall margin by 3%. Finally, a study was conducted to investigate the potential benefit of adding energy storage to the STARC-ABL concept that further improves operability and enables more gains in engine efficiency and performance. The energy storage provided an additional 0.5% stall margin can be removed from the HPC.

STARC-ABL↗

NASA NTRS2019

Dynamic Analysis of the STARC-ABL Propulsion System

In the pursuit of Electrified Aircraft Propulsion (EAP), much of the attention is on the development of hybrid electric concept vehicles and their propulsion systems from a steady state performance perspective. While it is steady-state performance that largely determines the efficiency of civil air transports, engine operability and transient performance define constraints for the steady state design that impact efficiency and system viability. Neglecting dynamics and control technologies can result in an over-designed, sub optimal propulsion system or a concept that is not feasible. Thus, dynamic system studies were conducted on the propulsion system of the conceptual aircraft design known as the Single-aisle Turboelectric AiRCraft with Aft Boundary Layer propulsor (STARC-ABL). This paper describes the development of a controller to verify the baseline concept's feasibility from an operability perspective. Further, studies were conducted to identify excessive stability margin in the baseline design that could be traded for potential benefits in efficiency through an engine re design. This study revealed the potential to reduce the high pressure compressor (HPC) stall margin by 3%. Finally, a study was conducted to investigate the potential benefit of adding energy storage to the STARC-ABL concept that further improves operability and enables more gains in engine efficiency and performance. The energy storage provided an additional 0.5% stall margin can be removed from the HPC.

dynamic systems analysis↗

NASA NTRS2013

NASA Center for Climate Simulation (NCCS) Advanced Technology AT5 Virtualized Infiniband Report

The NCCS is part of the Computational and Information Sciences and Technology Office (CISTO) of Goddard Space Flight Center's (GSFC) Sciences and Exploration Directorate. The NCCS's mission is to enable scientists to increase their understanding of the Earth, the solar system, and the universe by supplying state-of-the-art high performance computing (HPC) solutions. To accomplish this mission, the NCCS (https://www.nccs.nasa.gov) provides high performance compute engines, mass storage, and network solutions to meet the specialized needs of the Earth and space science user communities

cloud↗

NASA NTRS2001

Distributed Accounting on the Grid

By the late 1990s, the Internet was adequately equipped to move vast amounts of data between HPC (High Performance Computing) systems, and efforts were initiated to link together the national infrastructure of high performance computational and data storage resources together into a general computational utility 'grid', analogous to the national electrical power grid infrastructure. The purpose of the Computational grid is to provide dependable, consistent, pervasive, and inexpensive access to computational resources for the computing community in the form of a computing utility. This paper presents a fully distributed view of Grid usage accounting and a methodology for allocating Grid computational resources for use on a Grid computing system.

Thigpen, William↗

NASA NTRS2019

Electra: A Modular-Based Expansion of NASA's Supercomputing Capability

NASA has increasingly relied on high-performance computing (HPC) re- sources for computational modeling, simulation, and data analysis to meet the science and engineering goals of its missions in space exploration, aeronautics, and Earth and space science. The NASA Advanced Supercomputing (NAS) Division at Ames Research Center in Silicon Valley, Calif., hosts NASA’s premier supercomputing resources, integral to achieving and enhancing the success of the agency’s missions. NAS provides a balanced environment, funded under the High-End Computing Capability (HECC) project, comprised of world-class supercomputers, including its flagship distributed-memory cluster, Pleiades; high-speed networking; and massive data storage facilities, along with multi-disciplinary support teams for user support, code porting and optimization, and large-scale data analysis and scientific visualization. However, as scientists have increased the fidelity of their simulations and engineers are conducting larger parameter-space studies, the requirements for supercomputing resources have been growing by leaps and bounds. With the facility housing the HECC systems reaching its power and cooling capacity, NAS undertook a prototype project to investigate an alternative approach for housing supercomputers. Modular supercomputing, or container-based computing, is an innovative concept for expanding NASA’s HPC capabilities. With modular supercomputing, additional containers—similar to portable storage pods—can be connected together as needed to accommodate the agency’s ever-increasing demand for computing resources. In addition, taking advantage of the local weather permits the use of cooling technologies that would additionally save energy and reduce annual water usage. The first stage of NASA’s Modular Supercomputing Facility (MSF) prototype, which resulted in a 1,000 square-foot module on a concrete pad with room for 16 compute racks, was completed in Fall 2016 and an SGI (now HPE) computer system, named Electra, was deployed there in early 2017. Cooling is performed via an evaporative system built into the module, and preliminary experience shows a Power Usage Effectiveness (PUE) measurement of 1.03. Electra achieved over a petaflop on the LINPACK benchmark, sufficient to rank number 96 on the November 2016 TOP500 list [14]. The system consists of 1,152 InfiniBand-connected Intel Xeon Broadwell-based nodes. Its users access their files on a facility-wide file system shared by all HECC compute assets via Mellanox MetroX InfiniBand extenders, which connect the Electra fabric to Lustre routers in the primary facility over fiber-optic links about 900 feet long. The MSF prototype has exceeded expectations and is serving as a blueprint for future expansions. In the remainder of this chapter, we detail how modular data center technology can be used to expand an existing compute resource. We begin by describing NASA’s requirements for supercomputing and how resources were provided prior to the integration of the Electra module-based system.

Biswas, Rupak↗

NASA NTRS2019

Using Big Data Technologies with Earth Science Data in HDF5: HDF5 Scalable Solutions

HDF5 (Hierarchical Data Format 5) is open-source, high-performance software that consists of an abstract data model, library, and fileformat used for storing and managing extremely large and/or complex data collections. NASA Earth Observing System (EOS) Data and Information Systems use HDF5 as an archival format to store remote sensing data from EOS satellites. HDF5 is also used to store other types of Geoscience and Strophysical data, e.g., seismic data and data from Low-Frequency Array (LOFAR) radio telescopes. Data stored in HDF5 has reached tens of petabytes and is growing at an accelerated rate.With the growing amout of HDF5 Earth Science data to analyze and process, scientists need to adopt big data technologies including new storage paradigms such as cloud and object storage. To run models and perform data analysis they also need to utilizied efficient and diverse ways to access data, from high-performance computing's (HPC) Message Passing Interface (MPI) I/O and deep memory hierarchies (DMH) to non-HPC frameworks such as Apache Hadoop, Spark, and Drill. The HDF Group continually works to enable usage of big data technologies in HDF software.

Knox, Larry↗

NASA NTRS2012

Social Networking Adapted for Distributed Scientific Collaboration

Share is a social networking site with novel, specially designed feature sets to enable simultaneous remote collaboration and sharing of large data sets among scientists. The site will include not only the standard features found on popular consumer-oriented social networking sites such as Facebook and Myspace, but also a number of powerful tools to extend its functionality to a science collaboration site. A Virtual Observatory is a promising technology for making data accessible from various missions and instruments through a Web browser. Sci-Share augments services provided by Virtual Observatories by enabling distributed collaboration and sharing of downloaded and/or processed data among scientists. This will, in turn, increase science returns from NASA missions. Sci-Share also enables better utilization of NASA s high-performance computing resources by providing an easy and central mechanism to access and share large files on users space or those saved on mass storage. The most common means of remote scientific collaboration today remains the trio of e-mail for electronic communication, FTP for file sharing, and personalized Web sites for dissemination of papers and research results. Each of these tools has well-known limitations. Sci-Share transforms the social networking paradigm into a scientific collaboration environment by offering powerful tools for cooperative discourse and digital content sharing. Sci-Share differentiates itself by serving as an online repository for users digital content with the following unique features: a) Sharing of any file type, any size, from anywhere; b) Creation of projects and groups for controlled sharing; c) Module for sharing files on HPC (High Performance Computing) sites; d) Universal accessibility of staged files as embedded links on other sites (e.g. Facebook) and tools (e.g. e-mail); e) Drag-and-drop transfer of large files, replacing awkward e-mail attachments (and file size limitations); f) Enterprise-level data and messaging encryption; and g) Easy-to-use intuitive workflow.

Karimabadi, Homa↗

NASA NTRS2019

Evolving HPC and Application Design Toward a Coupled Data Assimilation System at NASA Suitable for Emerging Exascale Platforms

The prediction capabilities of global models have continuously evolved from the traditional medium-range global weather prediction application to span scales in support of hourly prediction of convective scale storms to seasonal Earth system prediction. This evolution has increased the demands on the system infrastructure design and workflow to achieve the required performance on modern high-performance computing (HPC) platforms. The planned evolution of the Goddard Earth Observing System (GEOS) modeling and assimilation system will stress the capabilities of conventional HPC overwhelming the available compute cycles at the NASA Center for Climate Simulation (NCCS) at the NASA Goddard Space Flight Center in the coming 5-10 years. This has led to the re-design of key elements of the assimilation and modeling systems to achieve significant gains in performance on anticipated Exacale platforms. The transition of the assimilation system to the Joint Effort for Data assimilation Integration (JEDI) framework has positioned GEOS to exploit new efficient algorithms for data assimilation (DA) in a fully-coupled Earth system context. The suitability of the GEOS model to leverage a domain specific language (DSL) approach and artificial intelligence (AI) is being explored to accelerate computational performance and data exchange efficiency of the coupled Earth system model. The storage and processing of large data volumes produced by these advance systems is being redesigned with a data-centric cloud-based approach. We will highlight the recent efforts in these areas and emphasize the demand for further development and re-design to achieve the science objectives in support of NASA's Earth system modeling and assimilation missions.

Putman, Bill↗