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DOE OSTI2022

Electron Cooling Experiment for Proton Beams with Intense Space-Charge in IOTA

Electron cooling as a method of creating intense ion beams has a practical upper limit when it comes to the peak phase space density of ion beams which can be achieved in practice. We describe a new experiment to study electron cooling of 2.5 MeV protons at the intensity limit using the Integrable Optics Test Accelerator (IOTA), which is a storage ring dedicated to beam physics research at Fermilab. This system will enable the study of magnetized electron cooling of a proton beam with transverse incoherent tune shifts approaching -0.5 due to the presence of intense space-charge forces. We present an overview of the hardware design, simulations and specific experiments planned for this project.

43 PARTICLE ACCELERATORS↗

NASA NTRS2000

The Interplay Between Hardware and Control System Design in the Development of the Active Rack Isolation System

A primary mission of the International Space Station (ISS) is to provide a premier microgravity laboratory environment for conducting acceleration sensitive scientific research. In order to accomplish this goal, vibroacoustic disturbances caused by station activities that occur during the microgravity mode of operation, must be controlled. In addition to source isolation and other passive isolation methods, the ISS uses active isolation at the receiver, through the use of an Active Rack Isolation System (ARIS), as part of its overall vibration isolation strategy. A schematic diagram of a typical ARIS payload rack is shown. The ARIS isolation control system senses rack acceleration via three triaxial accelerometer heads and uses eight pushrod actuators to perform active vibration attenuation. Position sensors housed in the actuator assembly are used to sense the relative position between the rack and the station. Electrical power, data and other essential resources are routed through a set of umbilicals that interface with a passthrough panel at the bottom of the rack. A representative umbilical set is shown.

Fialho, Ian J.↗

DOE OSTI2024

Progress in developing a superconducting accelerator for efficient eBeam and X-ray production

The PIP-II Accelerator is an 800 MeV superconducting Linac in the injection chain of the Fermilab accelerator complex. The LLRF systems for the 125 cavities which include a few normal conducting cavities in the warm front-end section, use a variety of LLRF hardware components and sub-systems that are part of the timing and synchronization system. This includes a master oscillator and phase averaging reference line, a beam pattern generator to enable beam transfer between non-harmonic RF systems and beam loading compensation systems synchronized to a start of beam trigger. The timing signals are based on a 650 MHz clock with manchester encoded event information and data provided over optical fiber. The timing and synchronization systems and their performance parameters will be described here.

43 PARTICLE ACCELERATORS↗

DOE OSTI2025

Optical neural engine for solving scientific partial differential equations

Abstract Solving partial differential equations (PDEs) is the cornerstone of scientific research and development. Data-driven machine learning (ML) approaches are emerging to accelerate time-consuming and computation-intensive numerical simulations of PDEs. Although optical systems offer high-throughput and energy-efficient ML hardware, their demonstration for solving PDEs is limited. Here, we present an optical neural engine (ONE) architecture combining diffractive optical neural networks for Fourier space processing and optical crossbar structures for real space processing to solve time-dependent and time-independent PDEs in diverse disciplines, including Darcy flow equation, the magnetostatic Poisson’s equation in demagnetization, the Navier-Stokes equation in incompressible fluid, Maxwell’s equations in nanophotonic metasurfaces, and coupled PDEs in a multiphysics system. We numerically and experimentally demonstrate the capability of the ONE architecture, which not only leverages the advantages of high-performance dual-space processing for outperforming traditional PDE solvers and being comparable with state-of-the-art ML models but also can be implemented using optical computing hardware with unique features of low-energy and highly parallel constant-time processing irrespective of model scales and real-time reconfigurability for tackling multiple tasks with the same architecture. The demonstrated architecture offers a versatile and powerful platform for large-scale scientific and engineering computations.

Tang, Yingheng (ORCID:0009000153622546)↗

DOE OSTI2026

Conceptual design of a replacement 2.1 K cold box for the Spallation Neutron Source Central Helium Liquefier

Abstract After more than 20 years of operation, the cold compressor technology in use at the Spallation Neutron Source (SNS) is obsolete, and replacement parts and service are no longer available. SNS has partnered with Jefferson Lab to design and construct a replacement sub-atmospheric cold box outfitted with modern cold compressor technology. The general design follows from Jefferson Lab’s experience on other recent sub-atmospheric cold box projects. Design decisions are backed by thorough engineering analysis to ensure technical requirements are met in a cost-effective manner. Conceptual design of the replacement cold box has been completed, and will be summarized in this paper. It features five cold compressors with an operating flow range of 80-140 g/s, and includes piping and valving to support cold compressor maintenance without interrupting flow circulation to the load. The approach to thermal shielding, insulation, and integration of the upgraded cold compressor hardware into the existing SNS control system will also be addressed.

Mastracci, B [Thomas Jefferson National Accelerato↗

DOE OSTI2026

The Memory Scaling of Reverse-Mode Differentiation in Particle Accelerator Simulations with Space Charge

The recent development of differentiable simulation codes for particle accelerators has enabled gradient-based workflows that promise finer control and more realistic modeling of accelerator facilities. However, when using reverse-mode automatic differentiation, the memory usage continuously increases during the simulation, and can potentially exceed the available hardware memory - especially when costly space charge computation is included. To study the memory requirements for differentiable simulations, we have implemented space charge in Cheetah, a PyTorch-based beam tracking code that supports reverse-mode differentiation. We find that the memory usage for reverse-mode differentiation grows linearly with the number of macroparticles and cells, and that it is proportional to the number of space charge kicks involved in the simulation. This general scaling can be used to evaluate whether a given differentiable simulation is feasible given hardware memory constraints.

Dhamrait, Arjun↗

NASA NTRS2000

Microgravity Disturbance Characterization of the Quench Module Insert (QMI) Phase Change Device (PCD)

The Materials Science Research Facility (MSRF) is a multi-user, multi-purpose facility for materials science research. One experiment within the MSRF will be the Quench Module Insert (QMI), a high-temperature furnace with unique capabilities for processing different classes of materials. The primary functions of the QMI furnace are to melt, directionally solidify, and quench metallic samples, providing data to aid in understanding the effects of the microgravity environment on the characteristics of these processed metals. The QMI houses sealed individual sample ampoules containing material to be processed. Quenching of the samples in the QMI furnace is accomplished by releasing low-melting-point metallic shoes into contact with the outside of the sample ampoule, dissipating heat and cooling the sample inside. The impact from this method of quench will induce sample vibrations which could be large enough to adversely affect sample quality. Utilizing breadboard hardware, the sample quench sequence, releasing the shoes, was conducted. Data was collected from accelerometers located on the breadboard sample cartridge, indicating the maximum acceleration achieved by the sample. The primary objective of the test described in this presentation was to determine the acceleration imparted on the sample by the shoe contact. From this information, the science community can better assess whether this method of quench will allow them to obtain the data they need.

Gattis, Christy↗

NASA NTRS2018

Learning Model Structural Uncertainty with Gaussian Processes

The advent of commercially available quantum computers has marked the beginning of quantum computing as a reality. Both quantum gate and annealing computers have been released by major computer hardware companies. In this work, the D-Wave 2XTM quantum annealing computer housed at the NASA Advanced Systems computational facility is investigated to accelerate Machine Learning (ML) for image registration. NASA collects large amounts of images over the globe remotely using space-based monitoring. Images of a fixed areas of the land surface are taken over time. Due to the orbit of the sensors, the viewing angles deviate slightly, and it is necessary to align or register the images precisely to create image time series over the land surface. Unaligned images can lead to substantial analysis errors. These time-series are then used in modeling Earth Systems models such as hydrological, weather, and carbon monitoring models. In this work, we consider the Moderate Resolution Image Spectrometer (MODIS) data collected by the NASA's terra satellite. Artificial Neural Networks (ANNs) is a natural fit for ML modelling of images. Several successes have been reported using machine learning related to image processing. We investigate the use of ML to register MODIS images. ANNs are investigated in combination with a Restricted Boltzmann Machines (RBM) as an auto-encoder. We will present results showing the accuracy and efficiency of this approach.The D-Wave 2XTM quantum annealer samples the ground-state wave-function of a spin-Ising systems with quadratic interactions between qubits and a Chimera connectivity. The system sits in a ~15 mK thermal bath. One can think of the system as being placed in the ground state initially and subject to thermal excitations governed by Boltzmann statistics. If this is assumed true, one can use the statistics from the D-Wave 2XTM to train RBMs. Generating statistics for training Boltzmann machines is an NP-hard problem and constitutes the largest compute cost. We investigate the use of the D-Wave 2XTM to accelerate the training of the RBMs in our ANNs and report on the results.

Kouatchou, Jules↗

DOE OSTI2022

Designing a Magnetic Measurement Data Acquisition and Control System With Reuse in Mind: A Rotating Coil System Example

Accelerator magnet test facilities frequently need to measure different magnets on differently equipped test stands and with different instrumentation. Designing a modular and highly reusable system that combines flexibility built-in at the architectural level as well as on the component level addresses this need. Specification of the backbone of the system, with the interfaces and dataflow for software components and core hardware modules, serves as a basis for building such a system. The design process and implementation of an extensible magnetic measurement data acquisition and control system are described, including techniques for maximizing the reuse of software. The discussion is supported by showing the application of this methodology to constructing two dissimilar systems for rotating coil measurements, both based on the same architecture and sharing core hardware modules and many software components. The first system is for production testing 10 m long cryo-assemblies containing two MQXFA quadrupole magnets for the high-luminosity upgrade of the Large Hadron Collider and the second for testing IQC conventional quadrupole magnets in support of the accelerator system at Fermilab.

43 PARTICLE ACCELERATORS↗

DOE OSTI2020

OpenACC unified programming environment for GPU and FPGA multi-hybrid acceleration

Attached accelerators have been frequently used in recent High Per- formance Computing (HPC) systems because of their high performance/power ratio. In particular, the Graphics Processing Unit (GPU) is the most popu- lar accelerator owing to its high peak FLOPS performance and high memory bandwidth supported by HBM2, etc. However, the performance of GPU depends highly on a large degree of SIMD parallelism and has difficulty sustaining a high performance on programs with frequent branch operations or a partially low degree of parallelism.By contrast, a Field Programmable Gate Array (FPGA) has received attention as a different type of accelerator than GPU as a fully reconfigurable processor fitting the target applications. The high performance of FPGA is mainly provided by a pipelined operation and optimized circuit suitable for any operation even with frequent conditional branches. We have been focusing on the flexibility of FPGA to compensate for the weakness of GPU. We believe that the coupling of GPU with FPGA can result in one of the most powerful accelerating platforms available.However, the program coding of GPU and FPGA coupling can be quite difficult for application users. Traditionally, CUDA by NVIDIA has been the most popular programming language with the largest share of GPUs used in HPC, whereas a hardware description language such as Verilog HDL has been used in FPGA programming. OpenCL coding has recently become available even on high-end FPGAs. Moreover, several recent studies have also enabled the OpenACC coding for use in FPGA. In this study, we provide a unified programming system based on OpenACC for a platform equipped with both GPU and FPGA aiming at the next-generation accelerated supercomputer framework. Our programming environment is called Multi-Hybrid OpenACC Translator (MHOAT), and in this paper, we describe the basic concept and prototype system of MHOAT based on an evaluation on the amount of coding required and the performance of a hybrid multi-device accelerated system.

Tsunashima, Ryuta↗

DOE OSTI2026

FitCache: A Transparent Drop-In Framework for Multi-Tier Caching to Accelerate Distributed Deep Learning Workloads

Training in Deep learning (DL) remains highly compute- and data-intensive, with I/O becoming a critical bottleneck as models and datasets scale. Recent studies report that data loading can dominate training time, especially on large-scale HPC systems with shared parallel file systems (PFS). Existing caching approaches either rely on single-tier designs or require intrusive modifications to training pipelines, limiting their portability and effectiveness. In this work, we present FitCache, a transparent drop-in framework for multi-tier caching to accelerate distributed DL training by coordinating fast local memory (e.g., DRAM, Persistent Memory (PMem)) and NVMe as hierarchical caches atop PFS. Our design adapts to hardware diversity, i.e., if NVMe is missing, memory transparently acts as a caching tier, ensuring stable performance. FitCache transparently intercepts I/O requests and issues concurrent fetches across all tiers, returning data from the fastest responder without centralized metadata or static redirection paths. FitCache adapts to dynamic workloads and heterogeneous clusters while maintaining POSIX compatibility. Experiments on Frontier (2048 GPUs) and smaller research clusters show that FitCache reduces training time by up to 40% and per-batch I/O latency by up to 71.6% compared to Lustre Orion PFS, offering a drop-in solution for scalable DL training.

Hu, Guangxing [ORNL] (ORCID:0009000283203614)↗

NASA NTRS1975

Impact accelerations

The degree to which impact acceleration is an important factor in space flight environments depends primarily upon the technology of capsule landing deceleration and the weight permissible for the associated hardware: parachutes or deceleration rockets, inflatable air bags, or other impact attenuation systems. The problem most specific to space medicine is the potential change of impact tolerance due to reduced bone mass and muscle strength caused by prolonged weightlessness and physical inactivity. Impact hazards, tolerance limits, and human impact tolerance related to space missions are described.

Henning E. von Gierke↗

NASA NTRS2015

Optimization of Selected Remote Sensing Algorithms for Embedded NVIDIA Kepler GPU Architecture

This paper evaluates the potential of embedded Graphic Processing Units (GPUs) in Nvidia's Tegra K1 (based on Kepler (TM) hardware) for onboard processing. The performance is compared to a general purpose multi-core CPU (Central Processing Unit) and a fully-fledged GPU accelerator. This study uses two algorithms: Wavelet Spectral Dimension Reduction of Hyperspectral Imagery and Automated Cloud-Cover Assessment (ACCA) Algorithm. Tegra K1 achieved 51 for the ACCA algorithm and 20 for the dimension reduction algorithm, as compared to the performance of the high-end 8-core server Intel Xeon CPU with 13.5 times higher power consumption.

data reduction↗

DOE OSTI2022

Performance for GPU exceptions

Techniques for improving performance of accelerated processing devices (“APDs”) when exceptions occur are provided. In APDs, the very large number of parallel processing execution units, and the complexity of the hardware used to execute a large number of work-items in parallel, means that APDs typically stall when an exception occurs (unlike in central processing units (“CPUs”), which are able to execute speculatively and out-of-order). However, the techniques provided herein allow at least some execution to occur past exceptions. Execution past an exception generating instruction occurs by executing instructions that would not lead to a corruption while skipping those that would lead to a corruption. After the exception has been satisfied, execution occurs in a replay mode in which the potentially exception-generating instruction is executed and in which instructions that did not execute in the exception-wait mode are executed. A mask and counter are used to control execution in replay mode.

Gutierrez, Anthony T.↗

DOE OSTI2025

Surrogate Neural Architecture Codesign Package (SNAC-Pack)

Neural Architecture Search is a powerful approach for automating model design, but existing methods struggle to accurately optimize for real hardware performance, often relying on proxy metrics such as bit operations. We present Surrogate Neural Architecture Codesign Package (SNAC-Pack), an integrated framework that automates the discovery and optimization of neural networks focusing on FPGA deployment. SNAC-Pack combines Neural Architecture Codesign's multi-stage search capabilities with the Resource Utilization and Latency Estimator, enabling multi-objective optimization across accuracy, FPGA resource utilization, and latency without requiring time-intensive synthesis for each candidate model. We demonstrate SNAC-Pack on a high energy physics jet classification task, achieving 63.84% accuracy with resource estimation. When synthesized on a Xilinx Virtex UltraScale+ VU13P FPGA, the SNAC-Pack model matches baseline accuracy while maintaining comparable resource utilization to models optimized using traditional BOPs metrics. This work demonstrates the potential of hardware-aware neural architecture search for resource-constrained deployments and provides an open-source framework for automating the design of efficient FPGA-accelerated models.

Weitz, Jason [UC, San Diego] (ORCID:00090004631535↗

DOE OSTI2021

The High Luminosity LHC interaction region magnets towards series production

The High Luminosity Large Hadron Collider (HL-LHC) is the new flagship project of CERN. First endorsed in 2013 and approved in 2016, HL-LHC is an upgrade of the accelerator aiming to increase by a factor of ten the statistics of the LHC collisions at the horizon of 2035-2040. HL-LHC relies on cutting edge technologies: among them, large aperture superconducting magnets will replace the present hardware to allow a smaller beam size in two interaction points (IPs). The project involves the construction of about 150 magnets of six different types: the quadrupole triplet, two main dipoles and three orbit correctors. The triplet, manufactured at CERN and in the USA, will consist of 30 magnets based on Nb3Sn technology, with an operational peak field of 11.4 T. These will be the first quadrupole Nb3Sn magnets installed in a particle accelerator. The other five types of magnets, all relying on Nb-Ti technology, present non-trivial challenges in the design and construction; they will be manufactured as part of in-kind contribution under the responsibility of institutes in Japan, China, Spain, and Italy. The project is now in the phase of transition between qualification through short models and prototypes and the beginning of the series construction. In this paper we review the magnet requirements, the reasons for selecting the design, the technological challenges with respect to previous projects, and we summarize the steps that have been taken to validate the baseline.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2020

Laser Transport System Vacuum Simulations and LED Atom Tracker

MAGIS-100 is an experiment using atom interferometry on strontium atoms in a 100m vacuum chamber. The laser travels through a laser transport system (LTS) before going down the chamber. Two projects were completed over the course of the internship. One project was conducting vacuum simulations on the LTS to ensure it meets the experimental pressure requirement of 10-11 torr. This was done by characterizing the pressure profile with variations in pump size, pump spacing, and orifice size. The initial design of the LTS included one 30 L/s ion pump in the high vacuum (HV) region, a lens mount with holes of diameter 0.788”, and three 150 L/s ion pumps in the ultra-high vacuum (UHV) region. After adjusting these variables, it was concluded that the lens mount holes could be reduced to 0.200” in diameter and one 150 L/s ion pump in the UHV could be removed and still meet the experimental requirements. The other project was to design an LED atom tracker that shows the position of the strontium atoms in the 100m shaft. This will help with public outreach by allowing visitors to have a visual of the experiment. An Arduino Uno and Arduino Due were programmed using classical physics formulas to direct the RGB LED strips to flash in sync with the falling atoms. The requirements for powering and connecting the hardware were calculated and recommendations for scaling the system to 100m were made.

43 PARTICLE ACCELERATORS↗

NASA NTRS1972

Rotor blade boundary layer measurement hardware feasibility demonstration

A traverse mechanism which allows the measurement of the three dimensional boundary layers on a helicopter rotor blade has been built and tested on a full scale rotor to full scale conditions producing centrifugal accelerations in excess of 400 g and Mach numbers of 0.6 and above. Boundary layer velocity profiles have been measured over a range of rotor speeds and blade collective pitch angles. A pressure scanning switch and transducer were also tested on the full scale rotor and found to be insensitive to centrifugal effects within the normal main rotor operating range. The demonstration of the capability to measure boundary layer behavior on helicopter rotor blades represents the first step toward obtaining, in the rotating system, data of a quality comparable to that already existing for flows in the fixed system.

Clark, D. R.↗