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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Performance tuning of CEED software and first wave apps

The goal of this milestone was the performance tuning of the CEED software and first wave apps. In this milestone, the CEED team developed optimization techniques and tuned for performance the CEED software. Specifically, the focus was on the following: (1) Fast finite element operator storage and evaluation using partial assembly/matrix-free algorithms that take advantage of tensor-product element structure; (2) Architecture optimizations, including the development of performant discretization libraries targeting heterogeneous systems with multi-core CPUs, GPUs, and/or many-core CPUs in single node, cluster, or large-scale ECP supercomputer configurations; and (3) Global kernels for finite element operators, including the development of algorithms and libraries for fast gather-scatter exchanges for action assembly on unstructured graphs and for components needed for global linear solvers. A main part of this milestone was the performance tuning of the CEED first-wave ECP applications. This included the ExaSMR application – Coupled Monte Carlo Neutronics and Fluid Flow Simulation of Small Modular Reactors (ORNL), and the MARBL application – Next-Gen Multi-physics Simulation Code (LLNL). The artifacts delivered include performance improvements in CEED’s 1st wave of applications, and tuned CEED software for various architectures through a number of backends, freely available in the CEED’s repository on GitHub. See the CEED website, http://ceed.exascaleproject.org and the CEED GitHub organization, http://github.com/ceed for more details. In addition to details and results from the above R&D efforts, in this document we are also reporting on other project-wide activities performed in Q4 of FY18 including: CEED’s second annual meeting, a successful minisymposium at the premier international conference on high-order methods (ICOSAHOM), making the CEED milestone reports publicly available, new Laghos release, and other outreach efforts.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Performance tuning of CEED software and 1st and 2nd wave apps

The goal of this milestone was the performance tuning of the CEED software, as well as the use and tuning of CEED to accelerate the first and second wave of targeted ECP applications. In this milestone, the CEED team developed optimization techniques and tuned for performance the CEED software to accelerate the first and second wave target ECP applications. Specifically, the focus was on the following: (1) Efficient use of the memory sub-system for managing data motion and interactions among different physics packages and libraries; this included integration of the new developments in a libCEED 0.5 software release; (2) Enhancing the CEED libraries with GPU and AMD GPU support in close interaction with vendors; (3) Optimal data locality and motion, and enhanced scalability and parallelism; this included vendors interactions for improvements in data motion and making strong scaling easier and more efficient; and (4) Continue boosting performance for the first-wave and second-wave of ECP target applications, including ExaSMR, ExaWind, Urban, MARBL, E3SM, and ExaAM. A main part of this milestone was the performance tuning of the CEED first-wave and second-wave ECP applications. This included the ExaSMR application – Coupled Monte Carlo Neutronics and Fluid Flow Simulation of Small Modular Reactors (ORNL), the MARBL application – Next-Gen Multi-physics Simulation Code (LLNL), and the ExaAM ExaConstit – a miniapp for the Transforming Additive Manufacturing through Exascale Simulation applications project (ExaAM), as well as ExaWind, Urban, and E3SM. The artifacts delivered include performance improvements in CEED’s 1st and 2nd wave of applications, and tuned CEED software for various architectures through a number of backends, freely available in the CEED’s repository on GitHub. See the CEED website, http://ceed.exascaleproject.org and the CEED GitHub organization, http://github.com/ceed for more details. In addition to details and results from the above R&D efforts, in this document we are also reporting on other project-wide activities performed in Q4 of FY19 including: CEED’s third annual meeting, MFEM GPU kernels scaling improvements, libCEED 0.5 and NekRS releases, an overview paper covering latest results on a set of bake-off high-order finite element problems (BPs), and other outreach efforts.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Accelerator Performance Tuning for E3SM: 2022 Annual Report [Abstract]

Over the past few years, we have been porting the Energy Exascale Earth System Model (E3SM) to GPU-accelerated architectures with a focus on the Leadership Computing Facilities at Oak Ridge and Argonne National Laboratories. This brief report describes work under a small allocation on the LANL Institutional Computing Chicoma machine to perform initial porting and performance tuning of the GPU-accelerated portions of E3SM for later production use on Chicoma, Perlmutter (a similar machine at NERSC) and eventually Venado.

58 GEOSCIENCES↗
DOE OSTI2019

ZIF‐8 Membrane Separation Performance Tuning by Vapor Phase Ligand Treatment

Abstract Vapor phase ligand treatment (VPLT) of 2‐aminobenzimidazole (2abIm) for 2‐methylimidazole (2mIm) in ZIF‐8 membranes prepared by two different methods (LIPS: ligand induced permselectivation and RTD: rapid thermal deposition) results in a notable shift of the molecular level cut‐off to smaller molecules establishing selectivity improvements from ca. 1.8 to 5 for O 2 /N 2 ; 2.2 to 32 for CO 2 /CH 4 ; 2.4 to 24 for CO 2 /N 2 ; 4.8 to 140 for H 2 /CH 4 and 5.2 to 126 for H 2 /N 2 . Stable (based on a one‐week test) oxygen‐selective air separation performance at ambient temperature, 7 bar(a) feed, and 1 bar(a) sweep‐free permeate with a mixture separation factor of 4.5 and oxygen flux of 2.6×10 −3 mol m −2 s −1 is established. LIPS and RTD membranes exhibit fast and gradual evolution upon a 2abIm‐VPLT, respectively, reflecting differences in their thickness and microstructure. Functional reversibility is demonstrated by showing that the original permeation properties of the VPLT‐LIPS membranes can be recovered upon 2mIm‐VPLT.

Eum, Kiwon↗
DOE OSTI2019

ZIF-8 Membrane Separation Performance Tuning by Vapor Phase Ligand Treatment

Vapor phase ligand treatment (VPLT) of 2-aminobenzimidazole (2abIm) for 2-methylimidazole (2mIm) in ZIF-8 membranes prepared by two different methods (LIPS: ligand induced permselectivation and RTD: rapid thermal deposition) results in a notable shift of the molecular level cut-off to smaller molecules establishing selectivity improvements from ca. 1.8 to 5 for O 2 /N 2 ; 2.2 to 32 for CO 2 /CH 4 ; 2.4 to 24 for CO 2 /N 2 ; 4.8 to 140 for H 2 /CH 4 and 5.2 to 126 for H 2 /N 2 . Furthermore, stable (based on a one-week test) oxygen-selective air separation performance at ambient temperature, 7 bar(a) feed, and 1 bar(a) sweep-free permeate with a mixture separation factor of 4.5 and oxygen flux of 2.6×10 -3 mol m -2 s -1 is established. LIPS and RTD membranes exhibit fast and gradual evolution upon a 2abIm-VPLT, respectively, reflecting differences in their thickness and microstructure. Functional reversibility is demonstrated by showing that the original permeation properties of the VPLT-LIPS membranes can be recovered upon 2mIm-VPLT.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

A Flexible-blocking Based Approach for Performance Tuning of Matrix Multiplication Routines for Large Matrices with Edge Cases

Efficient and scalable matrix operations are being highly demanding in the recent era of Machine Learning, Deep Learning, and Big Data Analytics. The two commonly used matrix-matrix operations in the Basic Linear Algebra Subprograms (BLAS) specification are General Matrix-Matrix multiplication (GEMM) and Symmetric Rank-k update (SYRK). The SYRK routine is a specialization of the GEMM routine, where half of the multiplications are skipped as the resultant matrix is known to be symmetric. Fortunately, several linear algebra libraries implement these BLAS routines quite efficiently. The libraries usually partition the input matrices into blocks and place them in processor caches, thus improving performance by leveraging the caches. However, the contemporary libraries are highly optimized for squarish matrices, but the performance degrades significantly for the matrices with edge case (strictly thin or strictly fat shapes) in the multicore machine. The primary reason is that the current state-of-the-art libraries make fixed block shapes based on a processor architecture, and do not consider the shape of the input matrices. In this paper, we propose a new blocking approach, we name it Flexible-blocking, to mitigate the scalability issues. In contrast to the contemporary libraries, our approach formulates the blocks of the input matrices based on the shapes of the matrices as well as the number of threads used in the implementation. Our proposed technique shows noticeable performance improvement on multicore shared-memory machines for the edge case matrices.

Hossain, Md Mosharaf↗
DOE OSTI2025

Parallelizing autotuning for HPC applications: Unveiling the potential of the speculation strategy in Bayesian optimization

In the exascale computing era, tuning High-Performance Computing (HPC) applications has become a significant computational challenge. Although Bayesian optimization (BO) has emerged as a promising tool for HPC performance tuning, the BO workflow is inherently sequential (i.e., one function evaluation at a time) and cannot leverage the huge amount of parallel resources present in modern supercomputers, resulting in a considerable underutilization of their computational capabilities. This paper explores the trade-off between search quality and parallelism in BO, investigating a diverse set of methods. Building upon both previous approaches from the literature and novel methodologies introduced in this work, our study provides a deep analysis to accelerate BO performance tuning. By examining a set of synthetic functions and practical HPC applications, our exploration analyzes the interaction among various BO methods for parallelization, the quantity of parallel resources, the runtime distribution of target HPC applications, and the costs associated with different search orchestration mechanisms that have been overlooked in previous studies. Compared to sequential BO, our novel methodology achieves comparable quality while demonstrating robust scalability in search time as the amount of parallel resources increases; it also outperforms a state-of-the-art tuner, which supports parallelization, achieving up to 3.67x faster search time. We provide high-value insights for practitioners seeking to leverage the power of parallel computing for efficient HPC application tuning. Additionally, to further assist researchers in accelerating the performance tuning of their HPC applications, we provide an extension of an existing open-source tuning framework that incorporates our methods.

Bayesian optimization↗
DOE OSTI2019

Tuning Photovoltaic Performance of Perovskite Nickelates Heterostructures by Changing the A-Site Rare-Earth Element

Perovskite rare-earth nickelates (RNiO3) have attracted much attention because of their exotic physical properties and rich potential applications. Here, we report systematic tuning of the electronic structures of RNiO3 (R=Nd, Sm, Gd, and Lu) by isovalent A-site substitution. By integrating RNiO3 thin films with Nb-doped SrTiO3 (NSTO), p-n heterojunction photovoltaic cells have been prepared and their performance has been investigated. The open-circuit voltage increases monotonically with decreasing A-site cation radius of RNiO3. This change results in a downward shift of the Fermi level and induces the increase in the built-in potential at the RNiO3/NSTO heterojunction, with LuNiO3/NSTO showing the largest open-circuit voltage. At the same time, the short-circuit current initially increases upon changing the A-site element from Nd to Sm. However, the larger bandgaps of GdNiO3 and LuNiO3 reduces light absorption which in turn induces a decrease in the short-circuit current. A power conversion efficiency of 1.13% has been achieved by inserting an ultrathin insulating SrTiO3 layer at the SmNiO3/NSTO interface. Our study illustrates how changing the A-site cation is an effective strategy for tuning photovoltaic performance and increasing the applicability of nickelates in optoelectric devices.

Nickelates, Oxygen vacancy, photovoltaics, p-n het↗
DOE OSTI2018

Tuning the Performance of Single-Atom Electrocatalysts: Support-Induced Structural Reconstruction

We present that creating active and stable electrocatalysts remains a highly desirable and critical goal in the fields of catalysis and clean energy conversion. Single-atom catalyst (SAC), as a new research frontier in heterogeneous catalysis, has demonstrated emerging prospects for many electrocatalytic reactions. Support assisted pyrolysis approaches are widely used in the synthesis of single-atom electrocatalysts. While extensive efforts have been devoted to increase the loading of the atomically dispersed metal sites, the role of the support in creating these active metal sites remains largely unexplored. Herein, we compare catalysts created by support-free and support-assisted pyrolysis of vitamin B12 and cobalt tetramethoxyphenylporphyrin, respectively, and demonstrate an important effect of support-induced structural reconstruction that directly controls the activation of SAC. Electrochemical studies show support-free catalysts are inactive for oxygen reduction reaction whereas the support-assisted pyrolysis yields highly active catalysts using the same molecular precursors. X-ray absorption spectroscopy experiments reveal that both the metal-nitrogen coordination and the type of nitrogen species are different in these two types of samples, which leads to a difference in the d-band of the cobalt metal center and ultimately controls the catalytic activity and stability. In conclusion, this new insight provides a unique perspective on how to tune the electrocatalytic performances of SAC at the molecular level.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2025

CMS HGCAL ECON-D ASIC : Impact of CMOS fabrication process tuning on performance and radiation tolerance

The CMS experiment’s High Granularity Calorimeter (HGCAL) upgrade will replace CMS’s existing endcap calorimeters in preparation for the High Luminosity LHC. To effectively use over 6 million channels of this “imaging”calorimeter, CMS has developed two novel Endcap Concentrator (ECON) ASICs to perform data compression/selection on detector. The ECON-D ASIC operates on the 750kHz data path, and the ECON-T ASIC on the 40MHz trigger path. These 65 nm CMOS ASICs are radiation tolerant to 200 Mrad and low power, operating at less than 2.5 mW/channel. The first full-functionality prototype ECONs were produced and characterized in 2021-23, and an initial engineering run was performed in 2024. ECON-D radiation testing for the engineering run revealed that the chip’s internal SRAMs produce intermittent read errors for a non-negligible fraction of chips. Further investigation indicated that the SRAM performance is highly sensitive to the exact parameters of the CMOS fabrication process. To both study this process sensitivity and mitigate SRAM performance issues, twenty ECON wafers were produced in 2025 with a range of doping concentrations designed to tune the underlying transistor threshold voltage by 0%, 5%, 10%, and 15% from nominal. This talk will present first measurements of ECON-D performance, power consumption, and radiation tolerance for these four variations of CMOS process.

Syal, Chinar [Fermilab]↗
DOE OSTI2020

Boosting the Oxygen Reduction Performance via Tuning the Synergy between Metal Core and Oxide Shell of Metal−Organic Frameworks‐Derived Co@CoO x

Abstract Co core@Co oxide shell (Co@CoO x ) catalysts represent a large family with promising oxygen reduction reaction (ORR) catalytic activity. However, inadequate understanding of Co@CoO x synergy prohibits further pursuit of catalytic performance enhancement. Herein, a Co zeolitic−imidazolate framework was converted into metallic Co, followed by controlled air treatment to form Co@CoO x . The composition and structure evolution as a function of air treatment temperature were studied thoroughly through conventional and synchrotron (both ex‐situ and in‐situ) characterizations, confirming the coexistence of CoO and Co 3 O 4 in the shell. The optimal catalyst showed an ORR half‐wave potential of 0.87 V (vs. RHE) in an alkaline half‐cell and delivered high discharge capacity in an aprotic Li−O 2 battery (7,124 mAh g Cat+C −1 ) and an aqueous Zn−air battery (694 mAh g Zn −1 ) with good performance retention after durability test. Modeling simulation and density functional theory calculation confirmed the charge donation from metal core to oxide shell and shed light on new insights of how metal@metal oxide synergy impacted the ORR via tuning the charge conductivity, oxygen affinity and intermediate transfer pathway. This work opens up a venue to boost ORR catalytic activity from an interfacial synergy perspective.

Wang, Hao↗
DOE OSTI2019

Proactive Data Containers for Scientific Storage (Final Report)

Emerging HPC systems are expected to be deployed with an unprecedented level of complexity, due to a deep system memory/storage hierarchy and heterogeneity of the storage hardware. This hierarchy is expected to range from CPU cache through several levels of volatile memory to nonvolatile memory, traditional hard disks, and tape. Simple and efficient methods of data management and movement through this hierarchy is critical for scientific applications using exascale systems. Existing storage system and I/O (SSIO) technologies face severe challenges in dealing with these requirements. POSIX and MPI I/O standards that are the basis for existing I/O libraries and parallel file systems present fundamental challenges in the areas of scalable metadata operations, semantics-based data movement performance tuning, asynchronous operation, and support for scalable consistency of distributed operations. Moving toward new paradigms for SSIO in the extreme-scale era, we have proposed to investigate novel object-based data abstractions and storage mechanisms that take advantage of the deep storage hierarchy and enable proactive automated performance tuning. In order to achieve these overarching goals, we initiated an effort to develop a fundamental new data abstraction, called Proactive Data Containers (PDC). A PDC is a container within a locus of storage (memory, NVRAM, disk, etc.) that stores science data in an object-centric manner. Managing data as objects enables powerful optimization opportunities for data movement and transformations. The R&D focus of this project are: 1) formulation of object-oriented PDCs and their mapping in different levels of the exascale storage hierarchy; 2) efficient strategies for moving data in deep storage hierarchies using PDCs; 3) techniques for transforming and reorganizing data based on application requirements; and 4) novel analysis paradigms for enabling data transformations and user-defined analysis on data in PDCs. Toward achieving these overarching goals, we designed an object-centric application programing interface (API) for HPC, scalable metadata management for object-centric storage systems, and data movement optimizations such as Data Elevator for moving data between two levels of storage devices and TAPIOCA for efficient aggregation of data on compute nodes. We then implemented several components of the PDC system. They include metadata management, data placement services, remote procedure calls, data aggregation, etc. We have put them together into the overall PDC framework.

97 MATHEMATICS AND COMPUTING↗