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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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DOE OSTI2018

Multi-Level Load Balancing with an Integrated Runtime Approach

The recent trend of increasing numbers of cores per chip has resulted in vast amounts of on-node parallelism. These high core counts result in hardware variability that introduces imbalance. Applications are also becoming more complex, re-sulting in dynamic load imbalance. Load imbalance of any kind can result in loss of performance and system utilization. We address the challenge of handling both transient and persistent load imbalances while maintaining locality with low overhead. In this paper, we propose an integrated runtime system that combines the Charm++ distributed programming model with concurrent tasks to mitigate load imbalances within and across shared memory address spaces. It utilizes a periodic assignment of work to cores based on load measurement, in combination with user created tasks to handle load imbalance. We integrate OpenMP with Charm++ to enable creation of potential tasks via OpenMP's parallel loop construct. This is also available to MPI applications through the Adaptive MPI implementation. We demonstrate the benefits of our work on three applications. We show improvements of Lassen by 29.6% on Cori and 46.5% on Theta. We also demonstrate the benefits on a Charm++ application, ChaNGa by 25.7% on Theta, as well as an MPI proxy application, Kripke, using Adaptive MPI.

Bak, Seonmyeong↗

DOE OSTI2025

Electrical Load Forecasting Over Multihop Smart Metering Networks With Federated Learning

Electric load forecasting is essential for power management and stability in smart grids. This is mainly achieved via advanced metering infrastructure, where smart meters (SMs) record household energy data. Traditional machine learning (ML) methods are often employed for load forecasting, but require data sharing, which raises data privacy concerns. Federated learning (FL) can address this issue by running distributed ML models at local SMs without data exchange. However, current FL-based approaches struggle to achieve efficient load forecasting due to imbalanced data distribution across heterogeneous SMs. Here, this article presents a novel personalized FL (PFL) method for high-quality load forecasting in metering networks. A meta-learning-based strategy is developed to address data heterogeneity at local SMs in the collaborative training of local load forecasting models. Moreover, to minimize the load forecasting delays in our PFL model, we study a new latency optimization problem based on optimal resource allocation at SMs. A theoretical convergence analysis is also conducted to provide insights into FL design for federated load forecasting. Extensive simulations from real-world datasets show that our method outperforms existing approaches regarding better load forecasting and reduced operational latency costs.

Rahman, Ratun [Univ. of Alabama, Huntsville, AL (U↗

NASA NTRS1989

Data traffic reduction schemes for Cholesky factorization on asynchronous multiprocessor systems

Communication requirements of Cholesky factorization of dense and sparse symmetric, positive definite matrices are analyzed. The communication requirement is characterized by the data traffic generated on multiprocessor systems with local and shared memory. Lower bound proofs are given to show that when the load is uniformly distributed the data traffic associated with factoring an n x n dense matrix using n to the alpha power (alpha less than or equal 2) processors is omega(n to the 2 + alpha/2 power). For n x n sparse matrices representing a square root of n x square root of n regular grid graph the data traffic is shown to be omega(n to the 1 + alpha/2 power), alpha less than or equal 1. Partitioning schemes that are variations of block assignment scheme are described and it is shown that the data traffic generated by these schemes are asymptotically optimal. The schemes allow efficient use of up to O(n to the 2nd power) processors in the dense case and up to O(n) processors in the sparse case before the total data traffic reaches the maximum value of O(n to the 3rd power) and O(n to the 3/2 power), respectively. It is shown that the block based partitioning schemes allow a better utilization of the data accessed from shared memory and thus reduce the data traffic than those based on column-wise wrap around assignment schemes.

Naik, Vijay K.↗

NASA NTRS1999

3D Multistage Simulation of Each Component of the GE90 Turbofan Engine

A 3D multistage simulation of each component of the GE90 Turbofan engine has been made. This includes 49 blade rows. A coupled simulation of all blade rows will be made very soon. The simulation is running using two levels of parallelism. The first level is on a blade row basis with information shared using files. The second level is using a grid domain decomposition with information shared using MPI. Timings will be shown for running on the SP2, an SGI Origin and a distributed system of HP workstations. On the HP workstations, the CHIMP version of MPI is used, with queuing supplied by LSF (Load Sharing Facility). A script-based control system is used to ensure reliability. An MPEG movie illustrating the flow simulation of the engine has been created using PV3, a parallel visualization library created by Bob Haimes of MIT. PVM is used to create a virtual machine from 10 HP workstations and display on an SGI workstation. A representative component simulation will be compared to rig data to demonstrate its usefulness in turbomachinery design and analysis.

Turner, Mark↗

DOE OSTI2020

Methods and apparatus to modify a binary file for scalable dependency loading on distributed computing systems

Methods and apparatus to modify a binary file for scalable loading on distributed computing systems are disclosed. An example method to modify a binary file for scalable loading on a distributed computing system includes identifying, by executing an instruction with a processor, in the binary file a file name for a shared file, determining, by executing an instruction with the processor, whether the shared file can be loaded based on a path name specified in the binary file, and, responsive to a determination that the shared file can be loaded, generating, by executing an instruction with the processor, an identifier that can be used to access a local file scalably copied from a global file system, and modifying, by executing an instruction with the processor, the binary file by replacing, in the binary file, the file name with the generated identifier.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1993

Prediction-based dynamic load-sharing heuristics

The authors present dynamic load-sharing heuristics that use predicted resource requirements of processes to manage workloads in a distributed system. A previously developed statistical pattern-recognition method is employed for resource prediction. While nonprediction-based heuristics depend on a rapidly changing system status, the new heuristics depend on slowly changing program resource usage patterns. Furthermore, prediction-based heuristics can be more effective since they use future requirements rather than just the current system state. Four prediction-based heuristics, two centralized and two distributed, are presented. Using trace driven simulations, they are compared against random scheduling and two effective nonprediction based heuristics. Results show that the prediction-based centralized heuristics achieve up to 30 percent better response times than the nonprediction centralized heuristic, and that the prediction-based distributed heuristics achieve up to 50 percent improvements relative to their nonprediction counterpart.

Goswami, Kumar K.↗

NASA NTRS1994

Instrumented Bolts Would Measure Shear Forces In Joints

Bolts instrumented with strain gauges used to measure shear forces. Bolts installed in multiple-bolt lap joints to obtain data on distribution of stresses and deformations in and around joints. Strain gauges indicate share of applied load borne by each individual bolt. In original application, bolted panels made of advanced refractory composite materials designed to withstand use at temperatures up to 4,000 degrees F. Also applicable to other joint materials and measurement of shear loads in other connections such as, shear loads on shafts in pulleys or gears.

Sawyer, James Wayne↗

NASA NTRS2000

Parallel and Distributed Computational Fluid Dynamics: Experimental Results and Challenges

This paper describes several results of parallel and distributed computing using a large scale production flow solver program. A coarse grained parallelization based on clustering of discretization grids combined with partitioning of large grids for load balancing is presented. An assessment is given of its performance on distributed and distributed-shared memory platforms using large scale scientific problems. An experiment with this solver, adapted to a Wide Area Network execution environment is presented. We also give a comparative performance assessment of computation and communication times on both the tightly and loosely-coupled machines.

Djomehri, Mohammad Jahed↗

NASA NTRS1990

Control of multiple resonant power processors in a multi-source system

Analysis and test results show that phasor-regulated, Mapham-derived resonant inverters can be paralleled to provide standardizing interfaces for multiple sources on a utility-type, aerospace power distribution bus. The basic sources do not require matching in any way, and may have grossly different characteristics. Fully stable system architectures with multiple sources, parallel/redundant distribution buses, and a wide variety of loads can be easily constructed and controlled. The commands and parameters available for system control allow for tight tolerance bus voltage control, and absolute power-sharing control from the various sources over the full range of possible source and load variations. That level of control enables simplified load power processing hardware and the distribution of losses to optimally load the source thermal control system. Positive control of all system performance and allocation of losses are not required by all missions or vehicles, and overall vehicle considerations do not always require the loads on vehicle energy sources and thermal control systems to be balanced. In those cases, power system control can be simplified, and a hierarchical set of defaults can be substituted for computer-generated or supervisory input commands to allow for stable, fully autonomous system operation.

Mildice, James↗

DOE OSTI2024

Security Constrained Distributed Transaction Model for Multiple Prosumers

Massive access of renewable energy has prompted demand-side distributed resources to participate in regulation and improve flexibility of power systems. With large-scale access of massive, decentralized, and diverse distributed resources, demand-side market members have transformed from traditional “consumers” to “prosumers”. To explore the distributed transaction model of prosumers, in this paper, a multi-prosumer distributed transaction model is proposed, and the Conditional Value-at-Risk (CVaR) theory is applied to quantify potential risks caused by the stochastic characteristics inherited from renewable energy. First, a prosumer model under constraints of the distribution network including photovoltaic units, fuel cells, energy storage system, central air conditioning and flexible loads is established, and a multi-prosumer distributed transaction strategy is proposed to achieve power sharing among multiple prosumers. Second, a prosumer transaction model based on CVaR is constructed to measure risks inherited from the uncertainty of PV output within the prosumer and ensure safety of system operation in extreme PV output scenarios. Then, the alternating direction multiplier method (ADMM) is utilized to solve the constructed model efficiently. Finally, distributed transaction costs of prosumers are distributed fairly based on the generalized Nash equilibrium to maximize social benefits. Simulation results show the multi-prosumer distributed transaction mechanism established under the proposed generalized Nash equilibrium method can encourage power sharing among prosumers, increasing their own income and social benefits. Also, the CVaR can assist decision making of prosumers in weighting the risks and benefits, improving system resilience through energy management of prosumers.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS1988

Data traffic reduction schemes for sparse Cholesky factorizations

Load distribution schemes are presented which minimize the total data traffic in the Cholesky factorization of dense and sparse, symmetric, positive definite matrices on multiprocessor systems with local and shared memory. The total data traffic in factoring an n x n sparse, symmetric, positive definite matrix representing an n-vertex regular 2-D grid graph using n (sup alpha), alpha is equal to or less than 1, processors are shown to be O(n(sup 1 + alpha/2)). It is O(n(sup 3/2)), when n (sup alpha), alpha is equal to or greater than 1, processors are used. Under the conditions of uniform load distribution, these results are shown to be asymptotically optimal. The schemes allow efficient use of up to O(n) processors before the total data traffic reaches the maximum value of O(n(sup 3/2)). The partitioning employed within the scheme, allows a better utilization of the data accessed from shared memory than those of previously published methods.

Naik, Vijay K.↗

DOE OSTI2021

Priority-enabled Load Balancing for Dispersed Computing

Opportunistic managed access to local in-network compute resources can improve the performance of distributed applications and reduce the dependence on shared network resources. Instead of backhauling application data to a centralized cloud data center for processing, networked services may be adaptively and continuously dispersed into shared compute resources that are closer to the source of need. While this approach has several benefits, support for mission-aware access to computation is often an afterthought, and is implemented as a brittle extension over traditional load-balancer solutions.In this work, we investigate the design of two priority-aware resource allocation strategies and two load-balancing dispatching strategies as first class citizens in an open-source dispersed computing middleware. We present a control theoretic analysis of these load-balancing primitives to identify weaknesses and strengths in our design, and recommend future directions. In parallel, we prototype two priority-aware allocation algorithms to validate our priority predictions. In initial experiments our prototype shows substantial gains in processing prioritized load. Finally, we make our source-code and experimental configurations open source.

Paulos, Aaron↗

DOE OSTI2023

On Site Wind for Rural Load Centers: RADWIND community presentation

These slides will be presented to the RADWIND workshop attendees at the pre-conference workshop of the NRECA TechAdvantage Experience. This presentation gives an overview of the On Site Wind for Rural Load Centers project in order to inform participants of ongoing work in the distributed wind space and share opportunities to get involved.

17 WIND ENERGY↗

DOE OSTI2023

On Site Wind for Rural Load Centers

This slide deck shares an overview of the On Site Wind for Rural Load Centers project, its relevance to the distributed wind community, and stakeholder engagement efforts.

17 WIND ENERGY↗

DOE OSTI2020

Characterizing Output Bottlenecks of a Production Supercomputer: Analysis and Implications

This article studies the I/O write behaviors of the Titan supercomputer and its Lustre parallel file stores under production load. The results can inform the design, deployment, and configuration of file systems along with the design of I/O software in the application, operating system, and adaptive I/O libraries.We propose a statistical benchmarking methodology to measure write performance across I/O configurations, hardware settings, and system conditions. Moreover, we introduce two relative measures to quantify the write-performance behaviors of hardware components under production load. In addition to designing experiments and benchmarking on Titan, we verify the experimental results on one real application and one real application I/O kernel, XGC and HACC IO, respectively. These two are representative and widely used to address the typical I/O behaviors of applications.In summary, we find that Titan’s I/O system is variable across the machine at fine time scales. This variability has two major implications. First, stragglers lessen the benefit of coupled I/O parallelism (striping). Peak median output bandwidths are obtained with parallel writes to many independent files, with no striping or write sharing of files across clients (compute nodes). I/O parallelism is most effective when the application—or its I/O libraries—distributes the I/O load so that each target stores files for multiple clients and each client writes files on multiple targets in a balanced way with minimal contention. Second, our results suggest that the potential benefit of dynamic adaptation is limited. In particular, it is not fruitful to attempt to identify “good locations” in the machine or in the file system: component performance is driven by transient load conditions and past performance is not a useful predictor of future performance. For example, we do not observe diurnal load patterns that are predictable.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Distribution Grid Model Publication Investigation

Interest in the external exchange of distribution grid model data is growing around the world, driven largely by the challenges and opportunities presented by the increasing amount of generation, storage, and flexible load being embedded within the distribution grid. This report provides an overview of the current state of distribution grid model data sharing, with a focus on the industry-leading activities currently underway in Great Britain (GB). A second report will explore opportunities for external distribution grid model sharing in the United States.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS1987

Lithospheric loading and tectonics of the lunar irregular maria

Many of the tectonic features associated with the circular maria are the result of stresses generated by loading of the lunar lithosphere by mare basalt units. The hypothesis is tested that the irregular lunar maria share with the circular maria the processes leading to the formation of associated graben and mare ridge systems. A formulation of the lithospheric flexure problem that accounts for the variable distribution of basalt loads for the irregular maria is applied. On the basis of the tectonic structures and geologic history of each of the major irregular maria, as well as models for the distribution of mare basalt for each region, the predicted stress fields are compared with the distribution of tectonic features for a range of assumed values of the thickness of the elastic lithosphere. The best fitting values for lithospheric thickness beneath the regular maria are then compared with those previously inferred for the circular maria.

Hall, J. Lynn↗

DOE OSTI2018

COOLR: A New System for Dynamic Thermal-Aware Computing

Extreme-scale systems need to walk a fine line between the amount of cooling they receive and the thermal-induced performance and reliability degradation they can sustain. System managers are extremely motivated to battle cooling-energy cost: the largest line item in their total operating cost. On the other hand, pushing the nodes to peak performance in tightened cooling regimes places the burden on the dynamic thermal management (DTM) to protect the hardware. DTM schemes throttle performance to relieve heat accumulation within nodes when cooling cannot mitigate the problem. These interventions prevent fatal failures but introduce inevitable performance degradations and variations. Such variations can have drastic consequences on the performance of extreme-scale systems. Furthermore, distribution of heat across different system nodes depends not only on the amount of workload. Even if a strictly equal share of computational load is assigned to all nodes, there are physical attributes and topological features of each system that inherently cause uneven accumulation of heat. These can cause one subcomponent to trigger DTM prematurely and penalize the overall system. Our goal in this project is to create a holistic thermal-aware view of the system, capturing both inherent physical attributes and dynamic system state. We developed COOLR, a dynamic system with the ability to evaluate the interplay between management of computation, data, power dissipation, and thermal state. Thereby, COOLR will achieve higher overall performance at the same energy and cooling cost. First, we performed a systematic power and thermal modeling and of high performance computing architectures. Analytical and empirical techniques were blended to generate a light-weight thermal model of target systems. Second, we developed a thermal-aware OS and runtime system. Policies for managing resources and schedules for processes has been designed to co-optimize the thermal state and performance of the system. The main outcome of our proposed thermal-aware dynamic computing system are scheduling and allocation of processes and memory accesses leading to an appropriately “skewed” distribution of activity across the system. The ultimate result of this new arrangement resulted in reduced occurrences of hotspots and reduced episodes of DTM intervention, leading to improvements in performance. The overall thermal characterization and modeling methodology (thermal instrumentation techniques, model building, and systematic model reduction) resulting from this project can be applied to systems beyond our immediate scope and will be applicable to future scaling. The thermal-aware dynamic computing paradigm will impact the efficiency of extreme-scale systems. The gained “thermal slack” can be given back to further tighten the cooling budget, benefiting the management cost of next generation extreme-scale systems.

97 MATHEMATICS AND COMPUTING↗