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DOE OSTI2018

SLoG: Large-Scale Logging Middleware for HPC and Big Data Convergence

Cloud developers traditionally rely on purpose-specific services to provide the storage model they need for an application. In contrast, HPC developers have a much more limited choice, typically restricted to a centralized parallel file system for persistent storage. Unfortunately, these systems often offer low performance when subject to highly concurrent, conflicting I/O patterns. This makes difficult the implementation of inherently concurrent data structures such as distributed shared logs. Yet, this data structure is key to applications such as computational steering, data collection from physical sensor grids, or discrete event generators. In this paper we tackle this issue. We present SLoG, shared log middleware providing a shared log abstraction over a parallel file system, designed to circumvent the aforementioned limitations. We evaluate SLoG’s design on up to 100,000 cores of the Theta supercomputer: the results show high append velocity at scale while also providing substantial benefits for other persistent backend storage systems.

big data↗

DOE OSTI2020

Optimizing High Performance Markov Clustering for Pre-Exascale Architectures

HipMCL is a high-performance distributed memory implementation of the popular Markov Cluster Algorithm (MCL) and can cluster large-scale networks within hours using a few thousand CPU-equipped nodes. It relies on sparse matrix computations and heavily makes use of the sparse matrix-sparse matrix multiplication kernel (SpGEMM). The existing parallel algorithms in HipMCL are not scalable to Exascale architectures, both due to their communication costs dominating the runtime at large concurrencies and also due to their inability to take advantage of accelerators that are increasingly popular. In this work, we systematically remove scalability and performance bottlenecks of HipMCL. We enable GPUs by performing the expensive expansion phase of the MCL algorithm on GPU. Additionally, we propose a CPU-GPU joint distributed SpGEMM algorithm called pipelined Sparse SUMMA and integrate a probabilistic memory requirement estimator that is fast and accurate. Furthermore, we develop a new merging algorithm for the incremental processing of partial results produced by the GPUs, which improves the overlap efficiency and the peak memory usage. We also integrate a recent and faster algorithm for performing SpGEMM on CPUs. We validate our new algorithms and optimizations with extensive evaluations. With the enabling of the GPUs and integration of new algorithms, HipMCL is up to 12.4x faster, being able to cluster a network with 70 million proteins and 68 billion connections just under 15 minutes using 1024 nodes of ORNL's Summit supercomputer.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Can the United States Maintain Its Leadership in High-Performance Computing? - A report from the ASCAC Subcommittee on American Competitiveness and Innovation to the ASCR Office

The United States (U.S.) is no longer the unambiguous leader in the vitally important field of high performance computing (HPC). Japan, the European Union (EU), and China have fielded systems that are on par with our fastest supercomputers. The supply chain for everything from semiconductors to scientific software is globally distributed. Yet our economic future and security depend critically on our ability to innovate faster than our competitors, and the speed of innovation depends increasingly on large-scale computational science and engineering and thus HPC. How should the United States respond to this challenge? This report seeks to initiate a new and potentially transformative national discussion on this vital question. The Department of Energy’s (DOE) Advanced Scientific Computing Research (ASCR) program is well-positioned to make informed, targeted decisions about where the United States should cooperate and where it should compete in the global market for scientific exploration and discovery. By setting its sights on problems critical to our nation and the world, by establishing productive new collaborations, and by making strategic investments, ASCR can restore and maintain U.S. scientific leadership in the critical areas described in this report while strengthening our research infrastructure and training a large, diverse cohort of scientists. In doing so, ASCR and its scientists will pave the way for a secure and prosperous future for America. For more than 30 years, the ASCR program has provided the HPC and networking capabilities and expertise needed to support DOE’s mission to advance the national, economic, and energy security of the United States. The program now faces the challenge of developing and deploying the next generation of HPC systems and technologies, as well as supporting the application of HPC and artificial intelligence (AI) technologies to a wide range of scientific and engineering research problems. Through its research and development efforts, the ASCR program must also advance the state of the art in HPC and accelerate the pace of scientific discovery and technological innovation. Fulfilling this promise will require significantly increased investments, as well as innovative policies and programs. This subcommittee is aware that we are making recommendations and calls for action at a time when federal resources are limited. We understand that a wide range of competing priorities must be balanced by the nation’s leaders and that there is a need to leverage resources in new ways and seek efficiencies in facilities and operations. However, we must not let these realities limit our imagination or silence our advocacy. The ASCR program is a key part of the U.S. research infrastructure and an important component of economic growth and U.S. competitiveness. ASCR has a responsibility to pursue its mission, including advanced scientific computing, applications of AI technologies, and the required advanced research facilities, with determination and enthusiasm. To fulfill the scientific enterprise’s responsibility to the nation, the ASCR program must not only develop and publish a clear vision with an associated list of goals, priorities, and recommendations but also demonstrate scientific leadership by consistently securing long-term funding. This will allow the program to build on its achievements to date, to realize its ambitious vision, and to make lasting contributions to the field.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2013

DOE Hanford Network Upgrades and Disaster Recovery Exercise Support the Cleanup Mission Now and into the Future

In 2013, the U.S. Department of Energy's (DOE) Hanford Site, located in Washington State, funded an update to the critical network infrastructure supporting the Hanford Federal Cloud (HFC). The project, called ET-50, was the final step in a plan that was initiated five years ago called "Hanford's IT Vision, 2015 and Beyond." The ET-50 project upgraded Hanford's core data center switches and routers along with a majority of the distribution layer switches. The upgrades allowed HFC the network intelligence to provide Hanford with a more reliable and resilient network architecture. The culmination of the five year plan improved network intelligence and high performance computing as well as helped to provide 10 Gbps capable links between core backbone devices (10 times the previous bandwidth). These improvements allow Hanford the ability to further support bandwidth intense applications, such as video teleconferencing. The ET-50 switch upgrade, along with other upgrades implemented from the five year plan, have prepared Hanford's network for the next evolution of technology in voice, video, and data. Hand-in-hand with ET-50's major data center outage, Mission Support Alliance's (MSA) Information Management (IM) organization executed a disaster recovery (DR) exercise to perform a true integration test and capability study. The DR scope was planned within the constraints of ET-50's 14 hour datacenter outage window. This DR exercise tested Hanford's Continuity of Operations (COOP) capability and failover plans for safety and business critical Hanford Federal Cloud applications. The planned suite of services to be tested was identified prior to the outage and plans were prepared to test the services ability to failover from the primary Hanford data center to the backup data center. The services tested were: Core Network (backbone, firewall, load balancers); Voicemail; Voice over IP (VoIP); Emergency Notification; Virtual desktops; and, Select set of production applications and data. The primary objective of the exercise was to test COOP around the emergency operations at Hanford to provide information on capabilities and dependencies of the current system to insure improved focus of emergency, safety and security capacity in a disaster situation. The integration of the DR test into the ET-50 project allowed the testing of COOP at Hanford and allowed the lessons learned to be defined. These lessons learned have helped improve the understanding of Hanford's COOP capabilities and will be critical for future planning. With the completion of the Hanford Federal Cloud network upgrades and the disaster recovery exercise, the MSA has a clearer path forward for future technology implementations as well as network improvements to help shape the usability and reliability of the Hanford network in support of the cleanup mission.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2014

Graphics processing unit accelerated three-dimensional model for the simulation of pulsed low-temperature plasmas

A 3-dimensional particle-in-cell/Monte Carlo collision simulation that is fully implemented on a graphics processing unit (GPU) is described and used to determine low-temperature plasma characteristics at high reduced electric field, E/n, in nitrogen gas. Details of implementation on the GPU using the NVIDIA Compute Unified Device Architecture framework are discussed with respect to efficient code execution. The software is capable of tracking around 10 × 10{sup 6} particles with dynamic weighting and a total mesh size larger than 10{sup 8} cells. Verification of the simulation is performed by comparing the electron energy distribution function and plasma transport parameters to known Boltzmann Equation (BE) solvers. Under the assumption of a uniform electric field and neglecting the build-up of positive ion space charge, the simulation agrees well with the BE solvers. The model is utilized to calculate plasma characteristics of a pulsed, parallel plate discharge. A photoionization model provides the simulation with additional electrons after the initial seeded electron density has drifted towards the anode. Comparison of the performance benefits between the GPU-implementation versus a CPU-implementation is considered, and a speed-up factor of 13 for a 3D relaxation Poisson solver is obtained. Furthermore, a factor 60 speed-up is realized for parallelization of the electron processes.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2021

Electromagnetic Transient Simulation Algorithms for Evaluation of Large-Scale Extreme Fast Charging Systems (Distribution Grid Models)

The distribution and transmission grids are observing an increased penetration of power electronics in loads and generations. For example, there is increasing interest in integrating in extreme fast charging (XFC) systems for fast charging of electrical vehicles. As these systems are integrated, developing high-fidelity electromagnetic transient model of XFC systems in distribution grids and evaluating their interactions with the power grid would be of significant interest. This model will be utilized for design of XFC systems, to identify upgrades in distribution and/or transmission grids, for planning purposes by transmission planners or operators or owners, among others. It can also be utilized in operations for improved reliable performance of the grid and/or XFC station. The challenge with simulating these models is the high computational complexity introduced by the large number of states present in the system and the time-step needed to simulate the system. In this paper, advanced simulations algorithms are applied to reduce the computational complexity of simulating large-scale XFC systems. The algorithms include numerical stiffness-based segregation, time constant-based segregation, clustering and aggregation on differential algebraic equations (DAEs), and multi-order integration approaches. While the first three algorithms split the matrix that needs to be inverted from a large matrix to much smaller matrices, the final algorithm reduces the computational burden of applying higher-order integration approaches in the complete system. The comparison made in the previous sentence is with respect to use of homogeneous integration approaches used in conventional electromagnetic transient simulators like power systems computer aided design (PSCAD). The approaches mentioned here have resulted in speed-up of 36x in the simulation of a single distribution system with 15 XFCs.

Debnath, Suman↗

DOE OSTI2018

Effect of flow field geometry on operating current density, capacity and performance of vanadium redox flow battery

We report that addition of flow fields to carbon paper electrodes in a vanadium redox flow battery (VRFB) can improve the peak power density through uniform distribution of electrolyte in the electrodes. However, it is unclear whether flow fields have a similar effect with graphite felt electrodes, as VRFBs with felt electrodes reported in literature show a large anomaly in obtained power density. In this work, we evaluate three flow fields; viz. serpentine, interdigitated and conventional (without flow pattern) type with felt electrodes and compare their performance with a serpentine flow field using carbon paper electrodes under identical experimental conditions. The conventional flow field provides highest energy efficiency (75%) followed by serpentine (64%) and interdigitated (55%) at 0.2 A cm -2 attributable to the deteriorating electrolyte distribution in the electrodes. Computation fluid dynamic simulations confirm the experimental finding of worsening electrolyte distribution (conventional < serpentine < interdigitated). A power density of 0.51 W cm -2 at 60 mL min -1 flow rate is obtained for serpentine and conventional flow fields with felt electrodes; comparable to the highest power density reported in literature for high performing zero-gap flow field architecture. Finally, this paper gives comprehensive insights on flow fields for VRFBs that can be extended to other flow batteries.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Asynchronous Iterative Solvers for Extreme-Scale Computing

The Asynchronous Iterative Solvers for Extreme-Scale Computing (AsyncIS) project aims to explore more efficient numerical algorithms by decreasing their overhead. AsyncIS does this by replacing the outer Krylov subspace solver with an asynchronous optimized Schwarz method, thereby removing the global synchronization and bulk synchronous operations typically used in numerical codes. AsyncIS—a U.S. Department of Energy (DOE)-funded collaboration between Georgia Tech, the University of Tennessee, Knoxville, Temple University, and Sandia National Laboratories—also focuses on the development and optimization of asynchronous preconditioners (i.e., preconditioners that are generated and/or applied in an asynchronous fashion). The novel preconditioning algorithms that provide fine-grained parallelism enable preconditioned Krylov solvers to run efficiently on large-scale distributed systems and manycore accelerators like GPUs.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

A Scalable Multi-Modal Framework for High-Fidelity Distributed Human Mobility Simulations

The development of data-driven models for human mobility in urban settings requires access to substantial and diverse real-world data. However, existing historical data often presents challenges such as limited volume, variety, and veracity, as well as missing data and privacy preservation concerns. Also, urban mobility modeling is inherently time-variant, complex, and multi-modal, encompassing everything from individual walking and running to private road travel and large-scale public transportation. These challenges call for innovative solutions to overcome data limitations and compute needs to model mobility behaviors accurately. To address these challenges, we propose a distributed, co-simulation-based architecture DURMOSim that integrates real-world data with scalable, high-fidelity simulations, demonstrating distributed co-simulation feasibility with existing mobility models. DURMOSim underpins a modular integration that would enable using any available mobility simulators for greater extensibility and scalability in performing various urban scenarios. In this paper, we present the design, implementation, and performance evaluation of DURMOSim, highlighting its capability to model population-scale mobility patterns. Our initial results show its ability to dynamically synchronize multiple simulation models at runtime with negligible computational overhead. We believe DURMOSim could be a robust tool for advancing urban mobility research and intelligent transportation systems.

Yoginath, Srikanth [ORNL] (ORCID:0000000184236050)↗

DOE OSTI2021

On-Sun Testing of a High-Temperature Solar Receiver's Flux Distribution

Concentrated solar power (CSP) is a promising technology in transitioning to renewable energy because of its abundance in nature and thermal energy storage (TES) capability. Among the four types of available CSP technology, including parabolic trough, linear Fresnel, power tower, and parabolic dishes, a power tower using a central receiver has more potential to generate high-temperature heat in a scale supporting power cycles efficiency and achieve low levelized cost of energy (LCOE). Other than the conventional type of receiver design, the high-absorptive receiver concept developed and presented in this paper is novel in its design approach. The novel receiver design originated from National Renewable Energy Laboratory (NREL) consists of an array of solar flux absorb tubes. The solar absorb tubes require uniform flux distribution and in-depth flux penetration through the three different reflective sections of tubes in a hexagonal shape. To evaluate this unique receiver design and thermal performance, the flux distribution, flux uniformity, and intensity were numerically simulated using ansys fluent and SolTrace modeling program. On-sun testing has been done at NREL high flux solar testing facility, based on the computational analysis.

clean energy↗

DOE OSTI2016

Modeling primary atomization of liquid fuels using a multiphase DNS/LES Approach

We report on the development of a model framework to simulate spray flames from direct injection of liquid fuel into an automotive cylinder engine. The approach to this challenging problem was twofold. On one hand, the interface-capturing multiphase computer code CLSVOF was used to resolve the rapidly evolving, topologically convoluted interfaces that separate the liquid fuel from the gas at injection: the main challenges to address were the treatment of the high-pressure flow inside the injector, which required the inclusion of compressibility effects; and the computational framework necessary to achieve a Direct Numerical Simulation (DNS) level of accuracy. On the other hand, the scales of turbulent fuel mixing and combustion in the cylinder engine were ad- dressed by the high-performance computer code RAPTOR within the Large Eddy Simulation (LES) framework. To couple the two computational methods, a novel methodology was developed to describe the dense spray dynamics in Raptor from the assigned spray size distribution and dispersion angle derived from CLSVOF. This new, independent Eulerian Multi-Fluid (EMF) spray module was developed based on the kinetic description of a system of droplets as a pressure-less gas; as we will show, it was demonstrated to efficiently render the near-nozzle coupling in mass, momentum, and energy with the carrier gas phase.

02 PETROLEUM↗

DOE OSTI2023

UPC++ v1.0 Programmer’s Guide (Rev. 2023.9.0)

UPC++ is a C++ library that supports Partitioned Global Address Space (PGAS) programming. It is designed for writing efficient, scalable parallel programs on distributed-memory parallel computers. The key communication facilities in UPC++ are one-sided Remote Memory Access (RMA) and Remote Procedure Call (RPC). The UPC++ control model is single program, multiple-data (SPMD), with each separate constituent process having access to local memory as it would in C++. The PGAS memory model additionally provides one-sided RMA communication to a global address space, which is allocated in shared segments that are distributed over the processes. UPC++ also features Remote Procedure Call (RPC) communication, making it easy to move computation to operate on data that resides on remote processes. UPC++ was designed to support exascale high-performance computing, and the library interfaces and implementation are focused on maximizing scalability. In UPC++, all communication operations are syntactically explicit, which encourages programmers to consider the costs associated with communication and data movement. Moreover, all communication operations are asynchronous by default, encouraging programmers to seek opportunities for overlapping communication latencies with other useful work. UPC++ provides expressive and composable abstractions designed for efficiently managing aggressive use of asynchrony in programs. Together, these design principles are intended to enable programmers to write applications using UPC++ that perform well even on hundreds of thousands of cores.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

PETSc/TAO Users Manual V.3.21

This manual describes the use of the Portable, Extensible Toolkit for Scientific Computation (PETSc) and the Toolkit for Advanced Optimization (TAO) for the numerical solution of partial differential equations (PDEs) and related problems on high-performance computers. PETSc/TAO is a suite of data structures and routines that provide the building blocks for implementing large-scale application codes on parallel (and serial) computers. PETSc uses the MPI standard for all distributed memory communication. PETSc/TAO includes a large suite of parallel linear solvers, nonlinear solvers, time integrators, and optimizers that may be used in application codes written in Fortran, C, C++, and Python (via petsc4py; see Getting Started ). The library is organized hierarchically, enabling users to employ the abstraction level most appropriate for a particular problem. By using techniques of object-oriented programming, PETSc provides enormous flexibility for users.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

PETSc/TAO Users Manual Revision 3.22

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

PETSc/TAO Users Manual Revision 3.23

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

PETSc/TAO Users Manual Revision 3.24

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Additive Manufactured Composite Phase-Change Material for Thermal Energy Storage Applications

Phase-change materials play a critical role in industrial energy storage applications to drive efficiency improvements, thermal energy management, and carbon emissions reductions. Recently, it has been shown that rapid solidification of alloys with metastable immiscibility in the liquid phase has the potential to form unique microstructures in which a low-melting phase is uniformly distributed in a high-melting matrix. This feature can be exploited using additive manufacturing to produce components with complex geometries containing such unique phase-change microstructures. Phase-field simulations utilizing high-performance computing were used to provide a detailed description of the evolution of the active phase during service in terms of their morphology and composition in different polycrystalline matrix grain morphologies that are typically produced during additive manufacturing. Phase field simulations were performed using, MEUMAPPS-SL (Microstructure Evolution Using Massively Parallel Phase-field Simulations – Solid Liquid) code that was developed in-house by the Oak Ridge National Laboratory. The simulations utilized the capabilities of the Kestrel supercomputer at the National Renewable Energy Laboratory. The simulation results were compared with experimental results generated at Siemens Energy, Inc. The results indicate that the kinetics of liquid spreading along grain boundaries is largely determined by the mobility of the triple line along the intersection of the grain boundary liquid and the grain boundary plane.

25 ENERGY STORAGE↗

DOE OSTI2026

PETSc/TAO Users Manual Revision 3.25

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗