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Liao, C.

Publications and source records attributed to Liao, C..

12 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Reductive Analysis with Compiler-Guided Large Language Models for Input-Centric Code Optimizations

Input-centric program optimization aims to optimize code by considering the relations between program inputs and program behaviors. Despite its promise, a long-standing barrier for its adoption is the difficulty of automatically identifying critical features of complex inputs. This paper introduces a novel technique, reductive analysis through compiler-guided Large Language Models (LLMs), to solve the problem through a synergy between compilers and LLMs. It uses a reductive approach to overcome the scalability and other limitations of LLMs in program code analysis. The solution, for the first time, automates the identification of critical input features without heavy instrumentation or profiling, cutting the time needed for input identification by 44× (or 450× for local LLMs), reduced from 9.6 hours to 13 minutes (with remote LLMs) or 77 seconds (with local LLMs) on average, making input characterization possible to be integrated into the workflow of program compilations. Optimizations on those identified input features show similar or even better results than those identified by previous profiling-based methods, leading to optimizations that yield 92.6% accuracy in selecting the appropriate adaptive OpenMP parallelization decisions, and 20-30% performance improvement of serverless computing while reducing resource usage by 50-60%.

Input-Centric Optimization↗
DOE OSTI2024

Developing an Interactive OpenMP Book with Large Language Models

Abstract. This paper presents an approach to authoring a textbook titled Interactive OpenMP Programming with the assistance of Large Language Models (LLMs). The writing process utilized state-of-the-art LLMs, including Gemini Pro 1.5, Claude 3, and ChatGPT-4, to generate the initial structure and outline of the book, as well as the initial content for specific chapters. This content included detailed descriptions of individual OpenMP constructs and practical programming examples. The outline and content have then undergone extensive manual revisions to meet our book goals. In this paper, we report our findings about the capabilities and limitations of these LLMs. We address critical questions concerning the necessity of textbook resources and the effectiveness of LLMs in creating fundamental and practical programming content. Our findings suggest that while LLMs offer significant advantages in generating textbook content, they require careful integration with traditional educational methodologies to ensure depth, accuracy, and pedagogical effectiveness. The Interactive OpenMP Programming book is developed with the framework of Jupyter Book, enabling the execution of code within the book from the web browser, providing instant feedback and a dynamic learning experience that stands in contrast to traditional educational resources. The book represents a significant step towards modernizing programming education, offering insights into practical strategies for generating the textbook through advanced AI tools.

Large Language Model · OpenMP · Interactive Book ·↗
DOE OSTI2022

Generating and Analyzing Program Call Graphs using Ontology

Call graph or caller-callee relationships have been used for various kinds of static program analysis, performance analysis and profiling, and for program safety or security analysis such as detecting anomalies of program execution or code injection attacks. However, different tools generate call graphs in different formats, which prevents efficient reuse of call graph results. In this paper, we present an approach of using ontology and resource description framework (RDF) to create knowledge graphs for specifying call graphs to facilitate the construction of full-fledged and complex call graphs of computer programs, realizing more interoperable and scalable program analyses than conventional approaches. We create a formal ontology-based specification of call graph information to capture concepts and properties of both static and dynamic call graphs so different tools can collaboratively contribute to more comprehensive analysis results. Our experiments show that ontology enables merging of call graphs generated from different tools and flexible queries using a standard query interface. Index Terms—Callgraph, ontology, knowl

Dorta, E.↗
DOE OSTI2018

Muon-Computed Tomography using POCA Trajectory for Imaging Spent Nuclear Fuel in Dry Storage Casks

Cosmic ray muon-computed tomography (μCT) is a new imaging modality with unique characteristics that can be particularly important for applications in nuclear proliferation detection and international treaty verification. Using cosmic ray muons for nuclear security presents several potential advantages. Among others, muons are generated naturally in the atmosphere, can penetrate high-density materials, and are freely available. No radiological sources are required and consequently there is no associated radiological dose. Recently, the feasibility of using muons for imaging spent nuclear fuel stored in shielded casks has been explored and has been proved beneficial. However, challenges in μCT imaging include low muon flux of ~10,000 muons/m2/min, the effects of multiple Coulomb scattering (MCS) blurring the image, and inefficiency in being able to use all recorded muons for imaging. In this paper, we argue that the use of muon tracing should produce tomographic muon images with improved quality – or more quickly for the same image quality – compared to the case where conventional methods are used. In our paper, we report on the development and assessment of a novel muon tracing method for μCT. The proposed method back projects the muon’s scattering angle into each pixel crossed by its PoCA trajectory then forward projects the variance of the scattering angle in each pixel to detector bins along the muon’s incident horizontal direction. Two scenarios were simulated to assess the expected detection capability of this proposed method. GEANT4 was used to model the main characteristics of 1-60 GeV muons through matter. The simulated images showed an expected improvement in resolution and a reduced the reliance on the muon momentum information compared to a more conventional muon tomography method.

Liu, Zhengzhi↗
DOE OSTI2018

Exploring Deep Learning and Sparse Matrix Format Selection

We proposed to explore the use of Deep Neural Networks (DNN) for addressing the longstanding barriers. The recent rapid progress of DNN technology has created a large impact in many fields, which has significantly improved the prediction accuracy over traditional machine learning techniques in image classifications, speech recognitions, machine translations, and so on. To some degree, these tasks resemble the decision makings in many HPC tasks, including the aforementioned format selection for SpMV and linear solver selection. For instance, sparse matrix format selection is akin to image classification—such as, to tell whether an image contains a dog or a cat; in both problems, the right decisions are primarily determined by the spatial patterns of the elements in an input. For image classification, the patterns are of pixels, and for sparse matrix format selection, they are of non-zero elements. DNN could be naturally applied if we regard a sparse matrix as an image and the format selection or solver selection as classification problems.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1997

Electron Excitation Cross Sections for the S II Transitions: 3s(exp 2)3p(exp 3) 4S(exp o) approaches 3s(exp 2)3p(exp 3) 2D(exp o), 2P(exp o), and 3s3p(exp 4) 4P

Experimental and theoretical collisional excitation cross sections are reported for the transitions 3s(exp 2)3p(exp 3)4S(exp o) approaches 3s(exp 2)3p(exp 3) 2D(exp o), 2P(exp o), and 3s3P(exp 4) 4P in S II. The transition wavelengths (energies) are 6716 A (1.85 eV), 4069 A (3.05 eV), and 1256 A (9.87 eV), respectively. In the experiments, use is made of the energy-loss merged-beams method. The metastable fraction of the S II beam was assessed and minimized. The contribution of elastically scattered electrons was reduced by the use of a lowered solenoidal magnetic field and a modulated radio-frequency voltage on the analyzing plates and by retarding grids to reject the elastically scattered electrons with larger Larmor radii. For each transition, comparisons are made among experiments, the new 19 state R-matrix calculation, and three other close-coupling calculations.

Liao, C.↗
NASA NTRS1996

Status of the Multiply-Charged Ion Research Facility at JPL

In order to provide a better understanding of the energy balance and ion composition in solar, stellar, and planetary atmospheres, and in the interstellar medium, a new research facility for the study of interactions of multiply-charged ions has been developed at the Jet Propulsion Laboratory (JPL).

charged↗
NASA NTRS1985

A 4-node Bilinear Isoparametric Element in Rockwell NASTRAN

The development and evaluation of the Rockwell NASTRAN four node quadrilateral (QUAD4) element is presented. The element derivation utilizes bilinear isoparametric techniques both for membrane and bending characteristics. The QUAD4 element coordinate system, membrane properties, lumped mass matrix, and treatment of warping are based upon the COSMIC/NASTRAN QDMEMI element while the bending characteristics are based on a paper by T. J. R. Hughes. The effects of warping on the bending stiffness, consistent mass, and geometric stiffness are based upon a paper by R. H. MacNeal. Numerical integration is accomplished by Gaussian quadrature on a 2 x 2 grid. Practical user support features include variable element thickness, thermal analysis and layered composite material definitions.

Liao, C.↗