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At least 991 records · Page 55

All sources NASA NTRS DOE OSTI

DOE OSTI2022

Multinode Multi-GPU Two-Electron Integrals: Code Generation Using the Regent Language

The computation of two-electron repulsion integrals (ERIs) is often the most expensive step of integral-direct self-consistent field methods. Formally it scales as O(N 4 ), where N is the number of Gaussian basis functions used to represent the molecular wave function. In practice, this scaling can be reduced to O(N 2 ) or less by neglecting small integrals with screening methods. The contributions of the ERIs to the Fock matrix are of Coulomb (J) and exchange (K) type and require separate algorithms to compute matrix elements efficiently. We previously implemented highly efficient GPU-accelerated J-matrix and K-matrix algorithms in the electronic structure code TeraChem. Although these implementations supported the use of multiple GPUs on a node, they did not support the use of multiple nodes. This presents a key bottleneck to cutting-edge ab initio simulations of large systems, e.g., excited state dynamics of photoactive proteins. We present our implementation of multinode multi-GPU J- and K-matrix algorithms in TeraChem using the Regent programming language. Regent directly supports distributed computation in a task-based model and can generate code for a variety of architectures, including NVIDIA GPUs. We demonstrate multinode scaling up to 45 GPUs (3 nodes) and benchmark against hand-coded TeraChem integral code. Finally, we also outline our metaprogrammed Regent implementation, which enables flexible code generation for integrals of different angular momenta.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS1990

Aerothermal environment induced by mismatch at the SSME main combustion chamber-nozzle joint

The computational study reported here is motivated by a Space Shuttle main engine hardware problem detected in post-flight and post-test inspections. Of interest are the potential for hot gas ingestion into the joint (G15) at the main combustion chamber-to-nozzle interface and the effect of particular goemetric nonuniformities on that gas ingestion. The flowfield in the G15 region involves supersonic flow past a rounded forward facing step preceded by a deep narrow cavity. This paper describes the physical problem associated with joint G15 and computational investigations of the G15 aerothermal environment. The associated flowfield was simulated in two and three space dimensions using the United Solutions Algorithm (USA) computational fluid dynamics code series. A benchmark calculation of experimentally measured supersonic flow over of a square cavity was performed to demonstrate the accuracy of the USA code in analyzing flows similar to the G15 computational flowfield. The G15 results demonstrate the mechanism for hot gas ingestion into the joint and reveal the sensitivity to salient geometric nonuniformities.

Mcconnaughey, H. V.↗

NASA NTRS1991

Numerical Simulation Of Flow Through An Artificial Heart

Research in both artificial hearts and fluid dynamics benefits from computational studies. Algorithm that implements Navier-Stokes equations of flow extended to simulate flow of viscous, incompressible blood through articifial heart. Ability to compute details of such flow important for two reasons: internal flows with moving boundaries of academic interest in their own right, and many of deficiencies of artificial hearts attributable to dynamics of flow.

Rogers, Stuart↗

NASA NTRS1992

Recursive formulation of operational space control

A recently developed spatial operator algebra approach to modeling and analysis of multibody robotic systems is used to develop O(n) recursive algorithms that compute the operational space mass matrix and the operational space coriolis/centrifugal and gravity terms of an n-link serial manipulator. These algorithms enable an O(n) recursive implementation of operational space control.

Kreutz-Delgado, K.↗

NASA NTRS1999

Tail Biting Trellis Representation of Codes: Decoding and Construction

This paper presents two new iterative algorithms for decoding linear codes based on their tail biting trellises, one is unidirectional and the other is bidirectional. Both algorithms are computationally efficient and achieves virtually optimum error performance with a small number of decoding iterations. They outperform all the previous suboptimal decoding algorithms. The bidirectional algorithm also reduces decoding delay. Also presented in the paper is a method for constructing tail biting trellises for linear block codes.

Shao. Rose Y.↗

NASA NTRS1971

A study of the Nordsieck-type predictor-corrector methods

Predictor-corrector schemes are discussed for the numerical integration of initial value problems by computer. Descloux formulas, which are considered modified Nordsieck formulas are studied because of their desirable stability and truncation properties along with the standard Nordsieck formulas. The stability of Nordsieck and modified Nordsieck algorithms are computed, and the results are graphed. Test problems are included as examples for comparing the efficiency of the algorithms.

Eiserike, H. M.↗

NASA NTRS2003

An Agent Inspired Reconfigurable Computing Implementation of a Genetic Algorithm

Many software systems have been successfully implemented using an agent paradigm which employs a number of independent entities that communicate with one another to achieve a common goal. The distributed nature of such a paradigm makes it an excellent candidate for use in high speed reconfigurable computing hardware environments such as those present in modem FPGA's. In this paper, a distributed genetic algorithm that can be applied to the agent based reconfigurable hardware model is introduced. The effectiveness of this new algorithm is evaluated by comparing the quality of the solutions found by the new algorithm with those found by traditional genetic algorithms. The performance of a reconfigurable hardware implementation of the new algorithm on an FPGA is compared to traditional single processor implementations.

Weir, John M.↗

DOE OSTI2021

Explaining Missing Data in Graphs: A Constraint-based Approach

Abstract: This paper introduces a constraint-based approach to clarify missing values in graphs. Our method capitalizes on a set S of graph data constraints. An explanation is a sequence of operational enforcement of S towards the recovery of interested yet missing data (e.g., attribute values, edges). We show that constraint-based approach helps us to understand not only why a value is missing, but also how to recover the missing value. We study S-explanation problem, which is to compute the optimal explanations with guarantees on the informativeness and conciseness. We show the problem is in ?P^2 for established graph data constraints such as graph keys and graph association rules. We develop an efficient bidirectional algorithm to compute optimal explanations, without enforcing S on the entire graph. We also show our algorithm can be easily extended to support graph refinement within limited time, and to explain missing answers. Using real-world graphs, we experimentally verify the effectiveness and efficiency of our algorithms.

Data Analytics↗

NASA NTRS1985

Study of one- and two-dimensional filtering and deconvolution algorithms for a streaming array computer

The development of vector processing computers of the streaming array architectures has made possible a dramatic decrease in the time required for the solution of problems, i.e., for those algorithms which readily lend themselves to sequential operations on long vectors. There has concurrently been rapid growth in the applications of the techniques generally known as mathematical digital filtering, also called signal analysis, digital signal processing, time series analysis, and digital image processing. The best known applications of these techniques is to seismic data and two-dimensional images, data types consisting of very large collections of numbers. A major limitation for these cases is the size and speed of the computer available. Therefore, a move to the streaming array architecture can result in marked improvement in the data analysis techniques which may be employed.

Ioup, G. E.↗

DOE OSTI2023

A greedy Galerkin method to efficiently select sensors for linear dynamical systems

A key challenge in inverse problems is the selection of sensors to gather the most effective data. In this paper, we consider the problem of inferring the initial condition to a linear dynamical system and develop an efficient control-theoretical approach for greedily selecting sensors. Our method employs a Galerkin projection to reduce the size of the inverse problem, resulting in a computationally efficient algorithm for sensor selection. As a byproduct of our algorithm, we obtain a preconditioner for the inverse problem that enables the rapid recovery of the initial condition. Here, we analyze the theoretical performance of our greedy sensor selection algorithm as well as the performance of the associated preconditioner. Finally, we verify our theoretical results on various inverse problems involving partial differential equations.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Scaling Out a Combinatorial Algorithm for Discovering Carcinogenic Gene Combinations to Thousands of GPUs

Cancer is a leading cause of death in the US, second only to heart disease. It is primarily a result of a combination of an estimated two-nine genetic mutations (multi-hit combinations). Although a body of research has identified hundreds of cancer-causing genetic mutations, we don’t know the specific combination of mutations responsible for specific instances of cancer for most cancer types. An approximate algorithm for solving the weighted set cover problem was previously adapted to identify combinations of genes with mutations that may be responsible for individual instances of cancer. However, the algorithm’s computational requirement scales exponentially with the number of genes, making it impractical for identifying more than three-hit combinations, even after the algorithm was parallelized and scaled up to a V100 GPU. Since most cancers have been estimated to require more than three hits, we scaled out the algorithm to identify combinations of four or more hits using 1000 nodes (6000 V100 GPUs with ≈48×106 processing cores) on the Summit supercomputer at Oak Ridge National Laboratory. Efficiently scaling out the algorithm required a series of algorithmic innovations and optimizations for balancing an exponentially divergent workload across processors and for minimizing memory latency and inter-node communication. We achieved an average strong scaling efficiency of 90.14% (80.96%–97.96% for 200 to 1000 nodes), compared to a 100 node run, with 84.18% scaling efficiency for 1000 nodes. With experimental validation, the multi-hit combinations identified here could provide further insight into the etiology of different cancer subtypes and provide a rational basis for targeted combination therapy.

Dash, Sajal↗

DOE OSTI2021

Online Voltage Event Detection Using Synchrophasor Data with Structured Sparsity-Inducing Norms

This paper develops an accurate and computationally efficient data-driven framework to detect voltage events from PMU data streams. It develops an innovative Proximal Bilateral Random Projection (PBRP) algorithm to quickly decompose the PMU data matrix into a low-rank matrix, a row-sparse event-pattern matrix and a noise matrix. Here, the row-sparse pattern matrix significantly distinguishes events from normal behavior. These matrices are then fed into a clustering algorithm to separate voltage events from normal operating conditions. Large-scale numerical study results on real-world PMU data show that the proposed algorithm is computationally more efficient and achieves higher F scores than state-of-the-art benchmarks.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2021

BASIC HARTREE-FOCK PROXY APPLICTION

This proxy application simulates the compute load and data-movement of the kernel of the Hartree-Fock method in quantum chemistry. The proxy features a simplified algorithm for computing electron repulsion integrals that is easily offloaded to GPUs.

FLETCHER, GRAHAMD↗

NASA NTRS1989

Computation of canonical correlation and best predictable aspect of future for time series

The canonical correlation between the (infinite) past and future of a stationary time series is shown to be the limit of the canonical correlation between the (infinite) past and (finite) future, and computation of the latter is reduced to a (generalized) eigenvalue problem involving (finite) matrices. This provides a convenient and essentially, finite-dimensional algorithm for computing canonical correlations and components of a time series. An upper bound is conjectured for the largest canonical correlation.

Pourahmadi, Mohsen↗

NASA NTRS2020

Formal Verification of a Solution to the n-Queens Problem

This report describes a formal verification of a concise algorithm that computes a solution to the n-Queens problem for all natural numbers n, such that n > 3. The formal proof of the algorithm is completed in the Prototype Verification System (PVS) theorem prover. This verification effort serves two purposes. First, it is presented as a pedagogical example for learning a theorem prover, such as PVS, and second, as a candidate benchmark for comparing other formal methods tools to PVS.

Mahyar R Malekpour↗

NASA NTRSDate not supplied

Error Localization Examples: Looking for a Needle in a Haystack

Finite element models (FEM) are routinely developed and used during fabrication of high dollar-value hardware. NASA, as part of the pre-flight certification of launch vehicles, routinely conducts vibration and static tests to calibrate models used for flight-risk assessments. During model calibration, certain areas of the model are modified, using engineering judgment and sensitivity analysis, to match the test results. Unfortunately, tools to identify problem areas in the FEM using test data directly are scarce and infrequently applied. Over the years, error localization algorithms have been proposed with very limited success. Recently, the Analytical Dynamics Model Improvement (ADMI) algorithm, which computes closed-form mass and stiffness corrections to match the test data exactly, have been shown to be an effective Error Localization Algorithm (ELA). The paper discusses three examples where ELA is used with simulated test data to locate problem areas. To gain confidence in the approach, the exact answer is shown along with ELA results. Results show that ELA is able to identify general problem areas consistent with known problem areas. In all examples, the ELA identified area is larger than the exact problem area. Nonetheless, with proper optimization tools, calibration results using the ELA identified areas provide excellent results.

model calibration↗

DOE OSTI2022

Scalable Energy System Expansion Under Uncertainty Using Multi-Stage Stochastic Optimization

The intermittent nature of renewable energy sources poses challenges for electrical grids. This is due to the variable and uncertain nature of the power output from these resources. These features of renewable generation are more relevant to energy system planning as grids reach higher penetration levels of renewable energy. We present approaches for energy system planning based on scalable computational approaches which enable explicit consideration of operational uncertainties in the planning process. Using multi-stage stochastic programming and the progressive hedging algorithm, we compute energy system expansion decisions on modified versions of the RTS-GMLC test system.

electrical↗

NASA NTRS2014

Vision Based Autonomous Robotic Control for Advanced Inspection and Repair

The advanced inspection system is an autonomous control and analysis system that improves the inspection and remediation operations for ground and surface systems. It uses optical imaging technology with intelligent computer vision algorithms to analyze physical features of the real-world environment to make decisions and learn from experience. The advanced inspection system plans to control a robotic manipulator arm, an unmanned ground vehicle and cameras remotely, automatically and autonomously. There are many computer vision, image processing and machine learning techniques available as open source for using vision as a sensory feedback in decision-making and autonomous robotic movement. My responsibilities for the advanced inspection system are to create a software architecture that integrates and provides a framework for all the different subsystem components; identify open-source algorithms and techniques; and integrate robot hardware.

sensory feedback↗