Results for “HPC” — Page 19

NASA NTRS2019

Scaling Evaluation of Ice-Crystal Icing on a Modern Turbofan Engine in PSL Using the COMDES-MELT Code

This paper presents preliminary ice-crystal icing (ICI) altitude scaling evaluation results of a Honeywell Uncertified Research Engine (HURE) that was tested in the NASA Glenn Research Center Propulsion Systems Laboratory (PSL) during January of 2018. This engine geometry features a hidden core design to keep the core less exposed. The engine was fitted with internal video cameras to observe various ice buildup processes at multiple selected locations within the engine core flow path covering the fan stator, the splitter-lip/shroud/strut, and the high pressure compressor (HPC) variable inlet guide vane (IGV) regions. The potential ice accretion risk was pre-determined to occur by using NASA’s in-house 1D Engine Icing Risk assessment code, COMDES-MELT. The code was successful in predicting the risk of ice accretion in adiabatic regions like the fan-stator of the HURE at specific engine operating points. However at several operating points during the test, liquid water was observed running along the shroud toward the variable IGV of the HPC regions with an air temperature well below freezing, thus no particle melting could have occurred due to heating from the air alone. It was reasoned that other sources of heat were present in that region. To account for these heat sources the inlet total temperature was adjusted to give a wet bulb temperature of 24 F below the standard minimum wet bulb temperature of 492 R to allow ice to accrete in the splitter-lip/shroud/strut region, which was determined from a reference case where hard ice was observed in that region. With that adjustment the COMDES-MELT code was successful in providing operating points where there was a risk of ice accretion during the test campaign. In addition to calculating possible conditions at different selected lower altitudes, simulations were run to determine potential inlet conditions that could lead to ice-crystal accretion along the prescribed stations where the cameras were available. From there, scaled test conditions were determined by best matching the following three icing related parameters of the reference condition: (1) the local air total wet bulb temperature, (2) the local ice crystal cloud melt ratio and (3) the engine fan face ice/water to air mass flux ratio of the ice crystal cloud. Instantaneous images taken from the time-lapsed movies of ice buildup were used along with the relevant thermodynamic data of air, water vapor and local icing condition to help evaluate how closely the proposed altitude scaling method could be used in ground based test facility to duplicate selected reference ICI features observed at specific location inside this engine at different scale altitudes. Discussions on observed limitation for engine icing scaling application from this test campaign and needed improvement are provided. A scaling test procedure to help identify potential ICI risk conditions and possible ice accretion locations of a new turbofan engine is evaluated in PSL.

Engine Testing in PSL↗

NASA NTRS2019

Cloud Computing Methods for Near Rectilinear Halo Orbit Trajectory Design

Complicated mission design problems require innovative computational solutions. As spacecraft depart from a proposed Gateway in a Near Rectilinear Halo Orbit (NRHO), recontact analysis is required to avoid risk of collision and ensure safe operations. Escape dynamics from NRHOs are governed by multiple gravitational bodies, yielding a trajectory design space that is exhaustively large. This paper summarizes the recontact analysis for departure from the NRHO and describes how the Deep Space Trajectory Explorer (DSTE) trajectory design software incorporates high performance cloud computing to compute and visualize the orbit design space. Recent focus on exploration missions to cislunar space has kindled accelerated interest in multibody orbit solutions. Trajectory analysis in the presence of multiple gravity fields is complex, and innovative computational tools are needed to simplify complicated design spaces, to generate large quantities of data quickly, and to visualize the output for user accessibility. The Gateway mission is a prime example. The Gateway1 is proposed as a human outpost in deep space. The current baseline orbit for the Gateway is a Near Rectilinear Halo Orbit (NRHO) near the Moon.2 The NRHO exists in a regime that experiences the gravitational effects of the Earth and the Moon simultaneously, complicating orbit analysis. The mission design process benefits greatly from updated computational tools for multibody missions like the Gateway. As an example, consider the problem of assessing the risk of collision in an NRHO. As a staging location to missions to the lunar surface and beyond the Earth-Moon system, the Gateway will experience spacecraft and other objects regularly arriving and departing. Departing objects potentially include spent logistics modules, visiting crew vehicles, debris objects, wastewater particles, and cubesats. Each departure is governed by the dynamics of the Gateway orbit and the surrounding dynamical environment. Over time, any unmaintained object in such an orbit eventually departs due to the small instabilities associated with the NRHOs. A separation maneuver speeds the departure from the NRHO, but the effects of the maneuver on the spacecraft behavior depend on the location, magnitude, and direction of the burn. Escape dynamics from the NRHO with regard to these maneuver options open up an enormous potential trajectory design space where subtle changes in input can produce dramatically large changes in the results. Any departing object must avoid recontacting the Gateway as it leaves the lunar vicinity, and a recontact analysis thus involves a significant number of computations and extensive output data. To explore the dynamics of this extensive design space, the Deep Space Trajectory Explorer3 (DSTE) trajectory design software incorporates new High Performance Computing (HPC) services and novel interactive visualizations. This paper details the HPC and cloud infrastructure techniques that are implemented in the DSTE, applying the new capabilities to analysis of recontact risk with the Gateway in NRHO. NEAR RECTILINEAR HALO ORBITS The Gateway is planned to fly in a lunar NRHO as its baseline orbit. The NRHO families of orbits are subsets of the larger halo families, which originate from planar orbits near the L1 and L2 libration points; the Earth-Moon L2 halo family appears in Figure 1. Each halo orbit is perfectly periodic in the Circular Restricted 3-Body Problem (CR3BP) and becomes a quasi-periodic orbit in a higher fidelity ephemeris force model. The NRHOs are defined as those members of the halo family with bounded stability properties;2 they pass near the Moon at perilune and are nearly polar. Families exist with apolunes located both above the lunar north pole and above the lunar south pole; the Gateway is planned to reside in a southern L2 NRHO in a 9:2 resonance with the lunar synodic period. The 9:2 NRHO is characterized by a period of about 6.5 days, a perilune radius of about 3,500 km, and an apolune radius of about 71,000 km; it is strongly affected by the gravity of both the Earth and the Moon simultaneously. This NRHO offers extended communications with assets on the south pole of the Moon,4 as well as low-cost orbit maintenance and attitude control,5 favorable eclipse avoidance properties,6 and inexpensive transfers from Earth and to other destinations.5,7 The NRHO portion of the southern L2 halo family is highlighted in black in Figure 1, and the 9:2 NRHO appears in blue.

Phillips, Sean M.↗

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 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 NTRS2024

A High-Performance Computing Predictive GNSS Performance Monitor for Autonomous Air Vehicles in Urban Environments

This report offers analysis and design insights for leveraging High-Performance Computing (HPC) to predict line-of-sight (LOS) Global Navigation Satellite System (GNSS) availability in a city. This work is motivated by the emerging fields of Advanced and Urban Air Mobility (AAM/UAM), where regulatory authorities are seeking city-scale, meter-resolution risk forecasting in order to safely integrate new flight missions with existing urban life and infrastructure. This work addresses the technical challenge of efficiently computing urban GNSS satellite visibility to predict GNSS performance metrics under these requirements. We present a new HPC-optimized shadow casting algorithm variant as a ray-based approach to forecasting satellite visibility. We apply this algorithm variant in a software-defined prognostic service which generates a GNSS navigation risk-correlated map as a path planning-style potential field. We detail dominant computational burdens, viable simplifying assumptions, and different algorithmic implementations, intending to demonstrate a baseline of computation time needed by each stage in such a service. We conclude by analyzing the prototype service’s prediction accuracy compared to receiver data from Corpus Christi, Texas. This informs design trade-offs along the dimensions of hardware, computation time, and tolerable forecasting error (including proportions of false positives and false negatives).

GNSS↗

DOE OSTI2024

EVs@Scale Lab Consortium High-Power Charging Pillar Deep-Dive Technical Meeting

Managed under the the U.S. Department of Energy (DOE)-funded EVs@Scale Consortium, the High-Power Electric Vehicle Charging Hub Integration Platform (eCHIP) project aims to create an experimental platform for integration and control approaches in a direct current (DC), distribution-based high-power charging (HPC) system. The eCHIP project addresses the crucial need to design and validate efficient, low-cost, reliable, and interoperable solutions for a DC-coupled charging hub ("DC hub" for short). This report explains the design, development, and implementation process of an experimental platform for the DC hub. DC distribution holds significant potential for enhancing the operation of an HPC station architecture. However, there are challenges in establishing a DC hub, including interoperability, commoditization, distributed energy resource integration, stability, DC protection, and a lack of common system-level controllers. To address these challenges, a testing setup is required that accommodates commercial off-the-shelf (COTS) products, as well as novel, in-house designed solutions, to evaluate different use cases at rated power and voltage levels. The developed proof-of-concept charging platform and open-source SEMS allow the development and testing of various controllers and chargers from different vendors. The DC hub platform integrated EVs, an ESS, a PV system, and building load to demonstrate the flexibility of the platform. The open-source SEMS controlled the devices within the hub using a rule-based implementation, realizing available standards.

ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2024

Nov. 2024 EVs@Scale High-Power Charging Deep Dive Technical Meeting

EVs@Scale Lab Consortium is addressing challenges, developing solutions, and enabling technologies for transportation electrification ecosystem. The consortium has five research pillars one of which focuses on high power charging (HPC). HPC pillar brings together hardware and software expertise, capabilities, and facilities related to high power EV charging, charge management, and grid integration. Deep-dive technical meetings are organized twice a year and provides an opportunity for more industry engagement and technical feedback for the national labs throughout the project lifecycle. High-Power Charging pillar has two active projects: (i) Next-Gen Profiles (NGP) and (ii) High-Power Electric Vehicle Charging Hub Integration Platform (eCHIP). This presentation summarizes the progress made in both projects during the past six months focusing on specific topics. There will be two deep-dive technical meetings twice a year. Every deep-dive meeting will focus on different aspects of the project progress.

ADVANCED PROPULSION SYSTEMS,DIRECT ENERGY CONVERSI↗

DOE OSTI2024

Dynamic Modeling of Power Conversion Stages for an Exascale Supercomputer

In this paper a power conversion and energy consumption model for an exascale supercomputer is investigated. Power consumption, energy loss and efficiency are derived for the 27.2 MW liquid-cooled, centralized, High Performance Computing (HPC) power system, which is supplied directly from the 480 V three-phase mains. Two energy conversion stages are analyzed, measured and modeled. The model is developed in order to be adapted and implemented in a digital twin platform utilizing a Resource Allocator and Power Simulator (RAPS) module. RAPS enables estimation of potential energy savings in the direct AC power supply architecture via both conventional rectifier load sharing (commonly used in HPC systems), as well as smart rectifier load sharing. Moreover, besides the direct AC supply architecture analysis, the full direct DC supply architecture with with 1 kV DC bus were also studied. Comparison of 10 hour time frame operation of the system, with direct 480 V AC voltage supply with conventional and smart load sharing and medium dc voltage supply were done. For the direct AC supply architecture, with conventional and smart load sharing the predicted power loss was approximately 840 kW and 820 kW, respectively and the predicted total system efficiency was 92.87% and 93.05%, respectively. For the direct DC supply architecture with the 1000 V DC supply bus power loss was approximately 340 kW and the predicted total system efficiency was 97.02%.

Wojda, Rafal↗

DOE OSTI2024

VerifyIO: Ensuring Correctness of Consistency Semantics in Parallel I/O

Abstract—High-performance computing (HPC) applications generate and consume substantial amounts of data, typically managed by parallel file systems. These applications access file systems either through the POSIX interface or by using highlevel I/O libraries. While the POSIX consistency model remains dominant in HPC, emerging file systems and popular I/O libraries increasingly adopt alternative consistency models that relax semantics in various ways, creating significant challenges for correctness and portability. This paper addresses these challenges by proposing a trace-driven I/O consistency verification workflow, implemented in our open-source tool, VerifyIO, which collects execution traces, detects data conflicts, and verifies proper synchronization against specified consistency models. Our extensive evaluation of 91 test case executions across three widely used I/O libraries with four I/O consistency models reveals critical consistency issues at both application and implementation levels.

Consistency Semantics↗

DOE OSTI2025

Quantifying Message Aggregation Optimisations for Energy Savings in PGAS Models

Upon breaking past the exascale barrier, HPC systems are facing their greatest challenge yet - a power wall that must be addressed through new methods in both hardware and software. While energy costs are becoming a major issue at all levels, of particular concern is that of the network, as the relative cost of moving data is increasing faster than ever. The partitioned global address space (PGAS) model is critical within certain HPC domains, but is known to suffer from the small message problem, where irregular many-to-many access patterns result in congesting the network with excessive numbers of small messages. To address this, the conveyor aggregation library was developed to defer individual messages and group them for subsequent bulk processing. In this paper, we investigate its impact on energy use related to the network, with a focus on the Slingshot 11 interconnect. We will demonstrate that this strategy is not only highly performant, but also crucial to reducing energy footprints to remain within target power envelopes.

Welch, Aaron [ORNL]↗

DOE OSTI2024

Lamellar: A Rust-based Asynchronous Tasking and PGAS Runtime for High Performance Computing

Cybersecurity is one of the largest concerns in modern computing, impacting and dictating how governments, private corporations, and individuals interact with and live in an increasingly digital world. The NSA has recently released a memo [ 1] on “Software Memory Safety” where they highlight that both Microsoft and Google have stated around 70% of software vulnerabilities were due to memory safety issues. Although languages such as C and C++ provide freedom and flexibility with memory management, guaran- teeing safety falls mostly on the developer. The NSA recommends using “memory safe” languages whenever possible. In this paper we introduce Lamellar, an asynchronous tasking and PGAS HPC runtime written in Rust, one such "memory safe" language. We describe the entire Lamellar stack, from network interfaces to high- level abstractions such as distributed LamellarArrays and Active Messages. We conclude by showing comparable performance to legacy PGAS runtimes (e.g. OpenSHMEM) on a subset of the BALE kernel suite while maintaining strong memory safety principles.

HPC Software Systems, Rust Programming Language, P↗

DOE OSTI2024

Performance Study of CXL Memory Topology

This paper presents a comprehensive evaluation of the performance impact of various Compute Express Link (CXL) memory topologies, with a particular emphasis on CXL switches, in the context of High- Performance Computing (HPC) and Large Language Model (LLM) inference workloads. Our study unveils significant performance variations across different topologies, demonstrating that certain configurations yield superior performance for specific workloads. These findings underscore the critical importance of tailored topol- ogy selection in optimizing system performance. Additionally, we address the inherent challenges associated with integrating CXL switches, including overhead considerations and routing complex- ities. Our research highlights the necessity for thorough evalua- tion methodologies to fully leverage CXL technology’s potential in contemporary computing environments. These insights provide valuable guidance for system architects and data center operators in designing and optimizing CXL-based infrastructures for diverse workload requirements.

CXL, memory, Artificial Intelligence (AI), HPC↗

DOE OSTI2025

Accelerating discoveries at DIII-D with the Integrated Research Infrastructure

DIII-D research is being accelerated by leveraging high performance computing (HPC) and data resources available through the National Energy Research Scientific Computing Center (NERSC) Superfacility initiative. As part of this initiative, a high-resolution, fully automated, whole discharge kinetic equilibrium reconstruction workflow was developed that runs at the NERSC for most DIII-D shots in under 20 min. This has eliminated a long-standing research barrier and opened the door to more sophisticated analyses, including plasma transport and stability. These capabilities would benefit from being automated and executed within the larger Department of Energy Advanced Scientific Computing Research program’s Integrated Research Infrastructure (IRI) framework. The goal of IRI is to empower researchers to meld DOE’s world-class research tools, infrastructure, and user facilities seamlessly and securely in novel ways to radically accelerate discovery and innovation. For transport, we are looking at producing flux matched profiles and also using particle tracing to predict fast ion heat deposition from neutral beam injection before a shot takes place. Our starting point for evaluating plasma stability focuses on the pedestal limits that must be navigated to achieve better confinement. This information is meant to help operators run more effective experiments, so it needs to be available rapidly inside the DIII-D control room. So far this has been achieved by ensuring the data is available with existing tools, but as more novel results are produced new visualization tools must be developed. In addition, all of the high-quality data we have generated has been collected into databases that can unlock even deeper insights. This has already been leveraged for model and code validation studies as well as for developing AI/ML surrogates. The workflows developed for this project are intended to serve as prototypes that can be replicated on other experiments and can be run to provide timely and essential information for ITER, as well as next stage fusion power plants.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

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 NTRSDate not supplied

GPU Implementation of the OVERFLOW CFD Code

The high-performance computing (HPC) landscape is quickly changing to systems where most of the performance comes from specialized chips, specifically graphics processing units (GPUs). Such GPU systems are throughput machines, where efficient use of the GPU often requires code refactoring to expose a few orders of magnitude more fine grain parallelism than was previously used on the CPU. Recent modifications to OVERFLOW, an overset, structured grid, computational fluid dynamics flow solver, written in Fortran will be presented. These modifications include both code modernization efforts and algorithmic changes to enable OVERFLOW to efficiently utilize GPUs. Many of these algorithmic changes would likely also be applicable for other structured grid, stencil-based codes wanting to utilize GPUs. The capabilities that have been ported to run on the GPUs are presented, along with the performance gains of the GPU version relative the CPU version of OVERFLOW.

GPU Programming↗

NASA NTRSDate not supplied

GPU Implementation of the OVERFLOW CFD Code

The high-performance computing (HPC) landscape is quickly changing to systems where most of the performance comes from specialized chips, specifically graphics processing units (GPUs). Such GPU systems are throughput machines, where efficient use of the GPU often requires code refactoring to expose a few orders of magnitude more fine grain parallelism than was previously used on the CPU. Recent modifications to OVERFLOW, an overset, structured grid, computational fluid dynamics flow solver, written in Fortran will be presented. These modifications include both code modernization efforts and algorithmic changes to enable OVERFLOW to efficiently utilize GPUs. Many of these algorithmic changes would likely also be applicable for other structured grid, stencil-based codes wanting to utilize GPUs. The capabilities that have been ported to run on the GPUs are presented, along with the performance gains of the GPU version relative the CPU version of OVERFLOW.

GPU Programming↗