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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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The Argonne Leadership Computing Facility (ALCF) I/O Data Repository is a collection of anonymized production I/O activity logs from the ALCF. This report provides an overview of the repository, including how to interpret the data and how to acknowledge its use.
Autoignition in turbulent flows is a challenging fundamental problem due to the intricate coupling of different physical and chemical processes extending over multiple flow and chemistry scales. At the same time, the improved understanding and ability to predict autoignition in flows characterized by considerable fluctuations of velocity, composition, and temperature is essential for the development of novel low-emission concepts for power generation. The aim of this project is to study the fundamental aspects of autoignition in a fuel-air mixing device directly applicable to mixing ducts in gas turbines. The NEK5000-based code for low Mach number reactive flows is used to perform very large scale direct numerical simulations of autoignition of a diluted hydrogen jet ejected in a cross-flowing stream of hot turbulent air in a laboratory-scale configuration. We report on our experience running NEK5000 on the new BGQ system at ALCF mira during the early science period (ESP). First of all, the most efficient problem size per MPI-rank is obtained through core-level efficiency metric measured from the target simulation. Furthermore, the most efficient number of ranks is found through strong scaling experiments. Finally, low-level insight into the observed parallel efficiency is enabled through IBM’s HPC Toolkit libraries.
This report gives an account of the 2017 achievements and findings of the ALCF as well as future directives.
This report gives an account of the 2018 achievements and findings of the ALCF as well as future directives.
The investigation and design of new classes of materials for energy and catalysis requires a multi-facetted approach to simulation. Multiple methods are needed to study materials on the length scale 0.1 nm - 10 nm. For simulations where the atomic (and electronic) degrees of freedom are relevant, the methods of choice in the surface science, condensed matter physics, and material science communities are classical molecular dynamics (CMD), Density Functional Theory (DFT), and quantum Monte Carlo (QMC). The original scope for this Early Science Program (ESP) project was to perform fast-accurate DFT calculations on materials for energy and catalysis using the GPAW code on Blue Gene/Q. The types of calculations included significantly reduced time-to-solution on systems sizes accessible on Blue Gene/P (~10, 0000 valence electrons), but also systems which were were at least a factor of two larger (~20, 000 valence electrons). GPAW is a real-space DFT code using the projector augmented wave (PAW) method. DFT calculations on Blue Gene/P were executed on over >100, 000 cores using GPAW; thus it was consider a success on Mira’s predecessor system, Intrepid. One of the co-PIs (NAR), determined that the work necessary to allow the GPAW code for these aforementioned types of calculations could not be accomplish within the time frame of the ESP. This was not simply due to human time required to implement OpenMP parallelism, but also from intrinsic algorithmic limitations in supporting libraries, most notably ScaLAPACK. Additionally, the return-on-investment on $\mathcal{O}(N^3)$ DFT code has become some what tenable at best. NAR argues that what is really needed in preparation for exascale computing and to enable high-fidelity materials research is robust reduced scaling, $\mathcal{O}$(N) or $\mathcal{O}$(N)log(N), DFT approaches. Thus, in agreement with the other co-PIs, the decision was made to purse QMC as a complimentary method on Mira since it would be valuable for the scientific community and could easily leverage the massive parallelism that would be provided by the Blue Gene/Q. We note that the two other atomic-scale methods mentioned here, CMD and DFT, are being pursued by other ESP projects on Mira. The remainder of this report will focus on our progress on QMC.
The HACC (Hybrid/Hardware Accelerated Cosmology Code) framework has achieved over 69% of the floating-point peak running on all of Mira, and is now uniquely positioned to make significant contributions to the science of large-scale structure formation. At the beginning of the Early Science Project (ESP), HACC was attaining under 1% of the peak FLOPS, and lacked the memory-management and file I/O capabilities necessary for running at scale. This report describes the improvements that transformed HACC from an average scientific code to one well-known for its unmatched performance.
The aerodynamic simulations of this project involve modeling of active flow control based on synthetic jet actuation that has been shown experimentally to produce large-scale flow changes (e.g., re-attachment of separated flow or virtual aerodynamic shaping of lifting surfaces) from micro-scale input. This micro-scale input consists for instance in 0.1 W piezoelectric disk which resonate in a cavity alternately and pushes/pulls out/in the fluid through a small slit to create small-scale vortical structures that interact with, and thereby dramatically alter, the cross flow. This process has yet to be understood fundamentally. Synthetic jet actuators offer the prospect of not only augmenting lift but also other forces and moments in a dynamic and controlled fashion for a range of operating conditions. They have been demonstrated to restore and maintain flow attachment and reduce vibrations in wind turbine blades during dynamic pitch, thereby reducing unsteady loads on gearboxes that are currently the prime failure point. In virtual-shape flight control surfaces for aerial vehicles (including commercial airplanes), conventional control surfaces (e.g., flaps, rudder, etc.) can be augmented or even replaced with active flow control, thus improving their lift-to-drag ratio and/or control power. The goal of the numerical simulations proposed in this project is to provide a complementary and detailed view of the flow interactions at a much higher Reynolds number, approaching engineering application scales for the first time.
Lattice QCD is a numerical method to simulate QCD (Quantum Chromodynamics) including non-perturbative effects. Among other methods, lattice QCD is the only successful non-perturbative method that can be systematically improved from first principles. Lattice QCD plays an important role in High Energy Particle Physics (flavor physics, spectroscopy, and beyond the Standard Model physics) and Nuclear Physics (nucleon/nuclear spectrum & structure, quark-gluon plasma, and the QCD equation of state). Moreover, recently there are active developments in applying lattice gauge theory to quantum field theory in general, for example the theoretical description of graphene or cold atom systems. We define the QCD action on a finite and discrete ‘lattice’ like grid, so that we can compute the path integral (partition function) on a computer. A current lattice size is 96 3 ×192, and the corresponding number of degrees of freedom for the path integral is about 6×10 8 . Thus, it requires enormous computing resources. In this report, we describe our overall efforts to improve lattice QCD software on Mira, which include a new communication library using the Message Unit (MU) SPI (System Programming Interface), better node mapping strategy, lattice site reordering, and using the quad floating point (QPX) intrinsics.
The electroweak response is a fundamental ingredient to describe the neutrino - 12 Carbon scattering, recently measured by the MiniBooNE collaboration to calibrate the detector aimed at studying neutrino oscillations. As a first step towards its calculation, we have computed the sum rules for the electromagnetic response of 12 C.
Large-scale Molecular dynamics (MD) simulation based on atomic models provide a powerful tool to understand the structure-dynamics-function relationships of important biological systems. Recent advances in computing power, especially in supercomputer, make MD simulation more and more popular in modern scientific community. However, the power of classical MD simulation has been limited mainly by the accuracy of the potential energy function and the efficiency of the dynamic algorithm enabling the adequate configurational sampling. This Early Science Project is aimed to make MD simulation method go beyond current limit using the leadership supercomputer Blue Gene/Q Mira. To address the issue of potential energy accuracy, classical Drude oscillator is developed to take into account the electronic polarizability in molecular systems. In order to develop and test the Drude polarizable force field for biomolecules, extensive MD simulations of typical polypeptides, lipids are needed. This requires efficient dynamic sampling algorithm that allows fast sampling. The sampling issue can be addressed by using advanced strategies based on multiple copies in order to enhance the sampling efficiency of brute-force MD. One such method is called replica-exchange MD (REMD).
Figure 1 shows, schematically, the tokamak device, whose intent is to magnetically confine a high-temperature plasma and produce energy through nuclear fusion. The confined plasma, shown in pink, is toroidal in shape. For several decades now, scientists have been studying and improving these devices, working toward a successful fusion ignition—creating a burning plasma—and sustaining it to generate more power than it took to create it. The next big experimental step will be the International Thermonuclear Experimental Reactor, a twenty billion dollar burning plasma device under construction in France, involving the partnership of seven governments. The human in Figure 2 illustrates the scale of ITER. The magnetic field in the tokamak confines the plasma—ions, electrons, and their heat and momentum. Various kinds of instabilities in the plasma work against that confinement. Turbulent fluctuations can cause transport of particles and energy across the magnetic field lines, toward the outside of the plasma, where it is lost. Loss of plasma and energy, of course, works against confinement and successful fusion. This microturbulence is something the fusion community needs to understand and control. In past and present tokamaks, measurements have shown that the transport of energy and particles caused by microturbulence depends on the size of the tokamak—larger means more transport. This is Bohm scaling. However, theoretical arguments predict that beyond a certain size, which ITER will be beyond, the size dependence goes away, leading to relatively smaller turbulent losses and thus better confinement. This is GyroBohm scaling. The key target of this ESP project is to simulate microturbulent transport for devices of different sizes up through ITER size, and validate and understand GyroBohm scaling.
Our efforts in developing a highly parallel implementation of the reactive force field model, the Multi-state Empirical Valence Bond (MS-EVB) method, are discussed. We have introduced multi-threading, a state decomposition parallelism, and replica exchange capabilities. Example calculations are presented to demonstrate the improved productivity and scalability of the new code on the Blue Gene/Q supercomputer, Mira. We show that we are now able to successfully scale to half of Mira and have the potential to scale even further.
This project uses dynamic rupture simulations to investigate high-frequency seismic energy generation. The relevant phenomena (frictional breakdown, shear heating, effective normal-stress fluctuations, material damage, etc.) controlling rupture are strongly interacting and span many orders of magnitude in spatial scale, requiring highresolution simulations that couple disparate physical processes (e.g., elastodynamics, thermal weakening, pore-fluid transport, and heat conduction). Compounding the computational challenge, we know that natural faults are not planar, but instead have roughness that can be approximated by power laws potentially leading to large, multiscale fluctuations in normal stress. The capacity to perform 3D rupture simulations that couple these processes will provide guidance for constructing appropriate source models for high-frequency ground motion simulations. The improved rupture models from our multi-scale dynamic rupture simulations will be used to conduct physicsbased (3D waveform modeling-based) probabilistic seismic hazard analysis (PSHA) for California. These calculation will provide numerous important seismic hazard results, including a state-wide extended earthquake rupture forecast with rupture variations for all significant events, a synthetic seismogram catalog for thousands of scenario events and more than 5000 physics-based seismic hazard curves for California.
Clouds remain the largest source of uncertainty in our understanding of global climate change. Different aspects of the planetary cloud field can provide positive and negative feedback to the Earth’s energy balance, and clouds of course are directly implicated in changes to the planetary distribution of precipitation. A fundamental problem in our current understanding of the role of clouds in the dynamics of climate are that current resolutions do not resolve the fundamental length scales associated with clouds. We expect our understanding of the role of clouds in climate to undergo a qualitative change as the resolutions of global models begin to encompass clouds. At these resolutions (which roughly scale with the tropopause height of 10km) non-hydrostatic dynamics become significant and deep convective processes are resolved. We are poised at the threshold of being able to run global scale simulations that include direct, nonparameterized, simulations of deep convective clouds. The goal of this research is to use the Argonne Leadership Computing Facility to explore the frontier of weather prediction and climate modeling with the newly developed Geophysical Fluid Dynamics (GFDL) global cloud-resolving model. A single unified atmospheric modeling system with a cubed-sphere dynamical core and bulk cloud micro-physics running at 3.5km resolutions was run with the goal of capturing the climatology of clouds and severe storms in a warming world. The ability to reproduce historical tropical storm statistics will be used as a test of this ground-breaking model.
In order to solve the electronic structure of large molecular systems on petascale computers using MADNESS, a numerical tool kit, are required fast and accurate implementations for linear algebra. MADNESS uses multiresolution analysis and low separation rank which translates high dimensional functions in tensor products using Legendre polynomial. The multiple tensor products make to the singular value decomposition and matrix multiplication the most intense operations in MADNESS. This work discusses the interfacing of Eigen3 as a C++ substitute of LAPACK and introduces Elemental for the diagonalization of large matrices. Furthermore, the present paper shows the performance these libraries on Blue Gene/ Q.
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The Argonne Leadership Computing Facility provides supercomputing capabilities to the scientific and engineering community to advance fundamental discovery and understanding in a broad range of disciplines.
This Operational Assessment Report describes how the Argonne Leadership Computing Facility (ALCF) met or exceeded every goal set by DOE for the calendar year (CY) 2024. In CY 2024, the ALCF operated Polaris, an AMD and NVIDIA-based Hewlett Packard Enterprise (HPE) Apollo 6500 Gen10+ system that provides a powerful platform for breakthrough science and prepares applications and workloads for Aurora, Argonne National Laboratory’s Intel-HPE exascale computer. Since going into production in August 2022, Polaris has supported research teams from the DOE Exascale Computing Project (ECP), which concluded in 2024, and from ALCF’s Aurora Early Science Program (ESP). Polaris delivered a total of 2555.7K node-hours to 17 Innovative and Novel Computational Impact on Theory and Experiment (INCITE) 2024 projects and 601.6K node-hours to ASCR Leadership Computing Challenge (ALCC) projects (12 of which were awarded during the 2023–2024 ALCC year and 11 of which were awarded during the 2024–2025 ALCC year), as well as providing substantial time for Director’s Discretionary (DD) projects (966.2K node-hours). As Table ES.1 shows, Polaris performed exceptionally well in terms of overall availability (97.7 percent), scheduled availability (99.6 percent), and utilization (94.7 percent; Table 2.1). In CY 2024, ALCF supported more than 2,000 users. As of March 18, 2025, ALCF’s users have published 254 papers in peer-reviewed journals and technical proceedings.