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DOE OSTI2020

An Analysis of System Balance and Architectural Trends Based on Top500 Supercomputers

Supercomputer design is a complex, multi-dimensional optimization process, wherein several subsystems need to be reconciled to meet a desired figure of merit performance for a portfolio of applications and a budget constraint. However, overall, the HPC community has been gravitating towards ever more FLOPS, at the expense of many other subsystems. To draw attention to overall system balance, in this paper, we analyze balance ratios and architectural trends in the world's most powerful supercomputers. Specifically, we have collected performance characteristics of systems between1993 and 2018 based on the Top500 lists, and then analyzed their architectures from diverse system design perspectives. Notably, our analysis studies the performance balance of the machines, across a variety of subsystems such as compute, memory, I/O, interconnect, intra-node connectivity and power. Our analysis reveals that balance ratios of the various subsystems need to be considered carefully alongside the application workload portfolio to provision the subsystem capacity and bandwidth specifications, which can help achieve optimal performance.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

3D printing of High Precision Radiation Filters for next generation Cosmic Background (CMB) studies (Final Report)

The terahertz (THz) spectral range is the part of the electromagnetic spectrum between 0.1–10 THz or 0.03–3 mm wavelength. For a long period, the terahertz band was relatively unexplored due to the unavailability of cost-effective and powerful sources. Due to the evolution of these devices in the mid-1980s, however, terahertz radiation has attracted much more attention. Since this part of the spectrum is between the infrared (IR) and microwave frequency ranges, the development of waveguides, filters, polarizers, lenses, and other optical components. Since terahertz waves to penetrate most dielectric materials offers the possibility of many applications. Since terahertz radiation can pass through organic tissue without causing damage, and it can be safely applied for biomedical applications. Radio astronomy and wireless communication are also fields with great interest in this spectral range. For example, terahertz waves could be used to detect cold bodies and debris in space or to increase data transmission using the larger bandwidth of the terahertz band.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2020

Noise Erasure in Quantum-Limited Current Amplifiers

Superconducting quantum interference devices (SQUIDs) are extraordinarily sensitive to magnetic flux and thus make excellent current amplifiers for cryogenic applications. One such application of high interest to Sandia is the set-up and state read-out of quantum dot based qubits, where a qubit state is read out from a short current pulse (microseconds to milliseconds long) of approximately 100 pA, a signal that is easily corrupted by noise in the environment. A Parametric SQUID Amplifier can be high bandwidth (in the GHz range), low power dissipation (less than 1pW), and can be easily incorporated into multi-qubit systems. In this SAIL LDRD, we will characterize the noise performance of the parametric amplifier front end -- the SQUID -- in an architecture specific to current readout for spin qubits. Noise is a key metric in amplification, and identifying noise sources will allow us to optimize the system to reduce its effects, resulting in higher fidelity readout. This effort represents a critical step in creating the building blocks of a high speed, low power, parametric SQUID current amplifier that will be needed in the near term as quantum systems with many qubits begin to come on line in the next few years.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2020

Two new SciDAC institutes promote mathematical tools and software technology for high-performance computing

Bigger is often said to be better, and the newest extreme-scale computers certainly are bigger, with millions of processing units. Moreover, the breadth of science performed on the U.S. Department of Energy (DOE) computing facilities is expanding, with new technology such as artificial intelligence emerging. These advances are exciting, creating new opportunities for scientific discovery; however, they also raise new questions for scientists who want to exploit these advances for tackling more complex problems. Will my simulation code be able to utilize the accelerators in extreme-scale computing systems? Can I take advantage of the deepening memory hierarchy in heterogeneous processors? Is there a way around bottlenecks caused by the widening ratio of peak floating-point operations per second to I/0 bandwidth? How can I manage my huge amounts of data effectively? Can I analyze data in situ, or must I transfer it to offline storage for later analysis? To address such questions, DOE announced that it is providing $57.5 million over the next five years for two multidisciplinary teams — FASTMath and RAPIDS2 — to develop new tools and techniques to harness supercomputers for scientific discovery. The teams, called SciDAC Institutes, are part of the Scientific Discovery through Advanced Computing program.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

Multichannel Deconvolution of Vibrational Shock Signals: An Inverse Filtering Approach

When transporting critical systems of national security interest, out-of-the ordinary, impulsive events that can potentially be undetected and affect overall system performance are of great concern. Impulsive events that can occur are essentially pulse-like, transient signals of short duration that evolve from various phenomena. Here the event can be created by either the dropping of a test object, the system, subjecting it to a compact high-energy blow or being struck unintentionally during transit resulting in potential damage. The intensity and location of the strike can cause an inoperability condition that is unacceptable in a national security environment. Therefore, it is essential to detect, classify and localize damage of any test object subjected to an impulsive-event. This effort was targeted to evaluate the vibrational response of test objects that are subjected to “transport” shocks and roadway vibrations during shipping and handling. Any potential damage that could be inflicted during transportation must not only be detected, but also be evaluated to determine the operational readiness of a test object before and after transport. This event is a critical task that must be addressed as part of the Lawrence Livermore National Laboratory (LLNL) national security mission. The estimation of excitation signals from noisy data is termed the deconvolution problem in the signal processing literature. The deconvolution problem is based on recovering the input excitation signal from a system characterized by its impulse response sequence. Using this model of the system, an “inverse” representation or filter is developed to remove the system from the measured data and recover the input. Deconvolution techniques have existed for a long-time; however, transient deconvolution presents a few uncommon problems, since the signal has a finite-length time duration resulting in a limited amount of data containing information about the excitation process. The transient is wideband in the frequency domain relative to any measurement sensor implying that the smaller bandwidth sensor system “filters” the excitation eliminating some of its essential information for recovery. This fact, coupled with the filtering effect of the test object itself makes this excitation recovery (deconvolution) problem a challenge for signal processing.

42 ENGINEERING↗

DOE OSTI2021

Plasma Photonics: Manipulating Light Using Plasmas (Full Technical Final Report)

In this LDRD, we made significant advances on multiple fronts on the investigation and design of plasma-based optical structures to manipulate light at extreme intensities. We have unveiled new fundamental properties of laser-plasma interaction that were leveraged to introduce transformative applications. We first investigated new ways to generate high-amplitude plasma-based optical structures, based on the auto-resonance mechanism in order to produce refractive structures in plasmas. New insights into the interaction of such plasma structures with light waves allowed us to propose new methods for polarization manipulation and control for high-intensity lasers in the nonlinear regime, i.e. allowing the manipulation of an intense laser via its interaction with a less intense “control” laser beam in plasmas. Another application that we demonstrated experimentally is the capability to manipulate the velocity of light waves in plasmas by tailoring its refractive index; we reported the first demonstration of “slow light” and supra-luminal light propagation in plasmas. We also developed a new technological concept that would allow the probing of the type of plasma structures investigated in such applications, using high-bandwidth laser probing [Ludwig Phys. Plasmas 2019]. Finally, first steps were taken towards the demonstration of a plasma-based amplifier and compressor for the National Ignition Facility, in order to achieve powers equal of greater than those delivered by the Advanced Radiographic Capability (ARC). This technique uses a plasma-based grating acting like a compressor and amplifier, which could potentially compress and amplify an 88 ps, 56 J beam from the National Ignition Facility to <10 ps and hundreds of J.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2020

Technical report: Design of the accessor

As we have seen the arithmetic power of hardware architectures growing much faster than the memory bandwidth, there is an urgent need to rethink the way we operate, communicate, and store data. A promising strategy for overcoming the “memory wall” is the decoupling of memory precision from arithmetic precision as proposed in Anzt et al. Such a decoupling of memory precision and arithmetic precision requires an “accessor” that handles the conversion between formats (resp. compression of the data) on the fly in registers. Such an accessor has to be general in the sense that it can handle a wide range of floating point formats and compression strategies, and still allows for further extension. At the same time, is important that the use of the accessor is not a burden for the developer. Therefore, it is important to abstract all implementation details from the user, hide the underlying storage format from the user, and make the accessor cross-platform portable. In this document we present the design of an accessor that aims at fulfilling all these requirements.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Understanding HPC Benchmark Performance on Intel Broadwell and Cascade Lake Processors

Hardware platforms in high performance computing are constantly getting more complex to handle even when considering multicore CPUs alone. Numerous features and configuration options in the hardware and the software environment that are relevant for performance are not even known to most application users or developers. Microbenchmarks, i.e., simple codes that fathom a particular aspect of the hardware, can help to shed light on such issues, but only if they are well understood and if the results can be reconciled with known facts or performance models. The insight gained from microbenchmarks may then be applied to real applications for performance analysis or optimization. In this paper we investigate two modern Intel x86 server CPU architectures in depth: Broadwell EP and Cascade Lake SP. We highlight relevant hardware configuration settings that can have a decisive impact on code performance and show how to properly measure on-chip and off-chip data transfer bandwidths. The new victim L3 cache of Cascade Lake and its advanced replacement policy receive due attention. Finally we use DGEMM, sparse matrix-vector multiplication, and the HPCG benchmark to make a connection to relevant application scenarios.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Technical Report: Accessor Realization

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Sensors with Intelligent Measurement Platform and Low-cost Equipment (SIMPLE) for Monitoring and Control of Medium Voltage Distribution Systems with High Penetration of Intermittent Distributed Energy Resources

The primary focus of the SIMPLE project was to develop, commission, test and introduce intelligent voltage and current sensor platform with enhanced characteristics (accuracy, bandwidth and harmonic range) and high measurement granularity for medium voltage distribution system monitoring, protection and control. The enhancements incorporated existing (commercially available) sensors and made them suitable for applications such as voltage regulation, frequency support, fault detection and location, distribution system state estimation, power quality measurements and electrical distribution network topology processing. The development of the intelligent sensor platform was driven by the need for high-fidelity monitoring and control of medium voltage distribution feeder to enable higher penetration of renewable resources and microgrid operation.

14 SOLAR ENERGY↗

DOE OSTI2021

Milestone M6 Report: Reducing Excess Data Movement Part 1

This is the second in a sequence of three Hardware Evaluation milestones that provide insight into the following questions: What are the sources of excess data movement across all levels of the memory hierarchy, going out to the network fabric? What can be done at various levels of the hardware/software hierarchy to reduce excess data movement? How does reduced data movement track application performance? The results of this study can be used to suggest where the DOE supercomputing facilities, working with their hardware vendors, can optimize aspects of the system to reduce excess data movement. Quantitative analysis will also benefit systems software and applications to optimize caching and data layout strategies. Another potential avenue is to answer cost-benefit questions, such as those involving memory capacity versus latency and bandwidth. This milestone focuses on techniques to reduce data movement, quantitatively evaluates the efficacy of the techniques in accomplishing that goal, and measures how performance tracks data movement reduction. We study a small collection of benchmarks and proxy mini-apps that run on pre-exascale GPUs and on the Accelsim GPU simulator. Our approach has two thrusts: to measure advanced data movement reduction directives and techniques on the newest available GPUs, and to evaluate our benchmark set on simulated GPUs configured with architectural refinements to reduce data movement.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

A Low Cost SIPM Evaluation and Control Prototyping System including accurate bias voltage generation, leakage current measurement, and temperature control using Peltier cooling

We describe an electronics system to operate SIPMs in the laboratory. The system is comprised of a single channel amplifier board (SIPM Amp) and a 4-channel control board to which up to 4 SIPM Amp boards can be connected. The control board supplies a common low voltage power for the amplifiers. All channels feature individually regulated bias and Peltier power voltages, along withPt10K RTD readout. A graphical user interface allows control of the bias voltages, amplifier voltage, Peltier voltages, and also provides for readback of leakage currents and other voltages. The GUI app has a feedback loop to measure the SIPM temperature (with the PT10K) and generate correction voltages to the Peltier to regulate the temperature. The temperatures, which can be achieved by Peltier cooling depend on the thermal design of the setup, the practical limit being about 50C below ambient. The SIPM Amp. board is a small (3x5cm) PCB that has a single SIPM readout channel. The SIPM scan be surface mounted on the pcb or connected to a 2-pin 0.100" socket. The area around the SIPM footprint is thermally isolated by perforations in the PCB. The RTD is located inside the thermal break. Onboard is BV and LV filtering. The 10X amplifier is based on MiniCircuits' GALI-S66+ integrated circuit, tweaked for a 6V power. The amplifier was selected for a combination of high bandwidth, low noise, and low power. An accoupled amplifier output is connected to an SMA connector. For best operation of this inverting amplifier the output signal should be in the range of 0 to -1V.The Amplifier board is connected to the Control board with a 10-conductor 0.025" pitch ribbon cable, carrying all the services. Peltier power for currents more than 1A should use a separate 2-contact connector.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2021

Performance Characteristics of the BlueField-2 SmartNIC

High-performance computing (HPC) researchers have long envisioned scenarios where application workflows could be improved through the use of programmable processing elements embedded in the network fabric. Recently, vendors have introduced programmable Smart Network Interface Cards (SmartNICs) that enable computations to be offloaded to the edge of the network. There is great interest in both the HPC and high-performance data analytics (HPDA) communities in understanding the roles these devices may play in the data paths of upcoming systems. This paper focuses on characterizing both the networking and computing aspects of NVIDIA’s new BlueField-2 SmartNIC when used in a 100Gb/s Ethernet environment. For the networking evaluation we conducted multiple transfer experiments between processors located at the host, the SmartNIC, and a remote host. These tests illuminate how much effort is required to saturate the network and help estimate the processing headroom available on the SmartNIC during transfers. For the computing evaluation we used the stress-ng benchmark to compare the BlueField-2 to other servers and place realistic bounds on the types of offload operations that are appropriate for the hardware. Our findings from this work indicate that while the BlueField-2 provides a flexible means of processing data at the network’s edge, great care must be taken to not overwhelm the hardware. While the host can easily saturate the network link, the SmartNIC’s embedded processors may not have enough computing resources to sustain more than half the expected bandwidth when using kernel-space packet processing. From a computational perspective, encryption operations, memory operations under contention, and on-card IPC operations on the SmartNIC perform significantly better than the general-purpose servers used for comparisons in our experiments. Therefore, applications that mainly focus on these operations may be good candidates for offloading to the SmartNIC.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Real-time data reduction at 100 Tbps: Challenge and opportunity for AI-based data reduction for next-generation large-scale nuclear physics collider experiment

The modern large-scale nuclear physics (NP) experiments in high-energy particle colliders utilize streaming-readout electronics to digitize detector response at O(100) Tbps bandwidth. Prominent examples at Brookhaven National Lab (BNL) include the sPHENIX experiment at Relativistic Heavy Ion Collider (RHIC), which is under construction, and the experiments proposed for the Electron-Ion Collider (EIC), planned for the 2030s . One of the main challenges for these streaming readout systems is to manage the data rate with sufficient data reduction in real time so the end-data fit persistent storage for offline analysis, which is typically at O(1000) times smaller and O(100) Gbps. Such data reduction traditionally is achieved via real-time high level triggers, which select and save a small subset of collisions of interest. Although triggering is applicable to high energy collider experiments such as those at the Large Hardron Collider at CERN, it is insufficient for these nuclear physics experiments which study diverse collision topologies. And traditional triggering approach is inefficient to preserve the max information harvested from the operation of colliders that costs O(100)M per year to DOE. Meanwhile, in recent years, ML-based high-throughput data reduction has emerged as a promising approach to efficiently preserve max information for a given space of persistent storage, e.g. via AI data compression, feature extraction, and noise filtering.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2022

The Motional Stark Effect Diagnostic for NSTX-U

This report describes the development of the motional Stark Effect diagnostic for NSTX. The MSE concept relies upon observation of the Balmer-alpha (n=3 to n=2) emission from a neutral hydrogen beam traversing a plasma. As a beam at high velocity, $\vec{ν}$, passes through the magnetic field in the plasma, $\vec{B}$, it experiences in its reference frame a Lorentz electric field, $\vec{E}$ = $\vec{ν}$ x $\vec{B}$. This electric field causes the spectral emission to be split and polarized as described by the Stark effect. The transition is separated into a set of lines in which the line spacing is linearly proportional to the electric field magnitude, and the line polarization is dependent on the electric field direction. Traditionally, MSE has used polarimetry to determine the polarization angle of the light, and related that to the magnetic field pitch angle in the plasma. The MSE diagnostic was developed under high magnetic field ($>$ 1~T) conditions, and the lower fields of recent high-beta experiments such as NSTX posed challenges to the technique. At low magnetic fields Doppler broadening effects mask the Stark effect. With the use of a narrow bandwidth filter MSE measurements at very low magnetic fields have been obtained.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2022

SMALE: Enhancing Scalability of Machine Learning Algorithms on Extreme-Scale Computing Platforms

Deployment and execution of machine learning tasks on extreme-scale computing platforms face several significant technical challenges: 1) High computing cost incurred by dense networks – The computing workload of deep networks with densely-connected topology increases rapidly with the network size, imposing a non-scalable computing model of extreme-scale computing platforms; 2) Non-optimized workload distribution – Many advanced deep learning algorithms, e.g., sparsification and irregular net-work topology, produce very unbalanced workload distribution on extreme-scale computing platforms. The computation efficiency is greatly hindered by the incurred data and computation redundancies as well as long tails of the node with extensive workload; 3) Constraints in data movement and I/O bottle-neck – Inter-node data movement in extreme-scale computing platforms are associated with high energy and latency costs, and subject to the constraints of I/O bandwidth; and 4) Generalization of algorithm realization and acceleration on computing platforms – The large varieties of machine learning algorithms and structures of extreme-scale computing platforms make the derivation of a generalized algorithm realization and acceleration method very challenging, which, however, is the requirement by domain scientists and interested users. We call the above challenges Smale’s Problems in Machine Learning and Understanding for High-Performance Computing Scientific Discovery. The objective of our three-year research project is to develop a holistic innovation set at structure, assembly, and acceleration layers of machine learning algorithms to address the above challenges in algorithm deployment and execution. Three tasks are particularly performed, including: At the algorithm structure level, we investigate the techniques that can structurally sparsify on the topology of deep networks for computing workload reduction. We also study clustering and pruning techniques that can optimize the workload distributions over the extreme-scale computing platforms; At the algorithm assembly level, we derive a unified learning framework for unsupervised transfer learning and dynamic growing capabilities. Novel training methods are also exploited to enhance the training efficiency of the proposed framework; At the algorithm acceleration level, we will develop a series of techniques that can accelerate the computation of sparse matrix operations, which are one of the core executions in deep learning and optimize memory access of the concerned platforms. Our proposed techniques attack the fundamental problems in machine learning algorithms running on extreme-scale computing platforms by vertically integrating the solutions at three closely entangled layers, paving the long-term scaling path of machine learning applications under DOE context. Three tasks corresponding to the above respective research orientations are performed during the three-year project period with our collaborators at ORNL. The outcome of the proposed project is anticipated to form a holistic solution set of novel algorithms and network topologies, efficient training techniques, and fast acceleration methods to promote the computing scalability of the machine learning applications of particular interest to DOE.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Experimental demonstration of OSC at IOTA: IOTA Run #3 (Report)

Optical Stochastic Cooling (OSC) is an optical-bandwidth extension of Stochastic Cooling that could advance the state-of-the-art cooling rate in beam cooling by three to four orders of magnitude. The concept of OSC was first suggested in the early 1990s by Zolotorev, Zholents and Mikhailichenko, and replaced the microwave hardware of SC with optical analogs, such as wigglers and optical amplifiers. A number of variations on the original OSC concept have been proposed, and while a variety of proof-of-principle demonstrations and operational uses have been considered, the concept was not experimentally demonstrated up to now. An OSC R&D program has been underway at IOTA for the past several years. Run #3 of the IOTA ring, which began in Nov. 2020 and concluded in Aug. 2021, was focused on the world’s first experimental demonstration of OSC. The experimental program was successful in demonstrating and characterizing the OSC physics with the major outcomes including strong cooling in one, two and three dimensions, validation of the theoretical models of OSC and the demonstration of OSC with a single electron. This report briefly describes the activities and major milestones of the OSC program during Run #3.

42 ENGINEERING↗

DOE OSTI2022

Hybrid Hydraulic-Electric Architecture (HHEA) for Mobile Machines (Final Report)

Traditionally, off-road mobile machines such as excavators and wheel loaders are primarily powered by hydraulics, and throttling valves are used to control their work circuits. In recent years, two general trends are towards more energy efficient systems and electrification. With electrification, both efficiency and control performance can be improved by the elimination of throttling losses and the use of high-bandwidth inverter control. Electrification is generally accomplished with Electro-hydraulic actuators (EHA) but they are limited to lower powered systems due to the high cost of electric machines capable of high power or high torque. This project proposes a new system architecture for off-road vehicles - Hybrid Hydraulic Electric Architecture (HHEA) to improve efficiency and control performance without requiring large electric machines. The widely applicable architecture combines hydraulic power and electric power in such a way that the majority of power is provided hydraulically while electric drives are used to modulate this power. In particular, HHEA utilizes multiple common pressure rails to transmit the majority of power and small electric machines to modulate the power. The energy-saving potential of the the HHEA has been validated for the work circuits of a variety of mobile machines, from small 5-ton excavators to medium sized 20-ton excavators and wheel loaders, and representative duty cycles to reduce energy input by 50-80% compared to the commercial state-of-art load-sensing systems. In addition, the corner power requirements of the electrical machines can be downsized by 85% compared to the EHA approach. Various tradeoff studies have also been conducted, including sensitivities to individual components performances, controllers, accumulator sizes, and variations of the system architecture etc. A control strategy has been developed to maintain or exceed the motion control precision compared to current systems. The motion control strategy consists of a nominal controller, based on a passivity-based backstepping design, and a transition controller, based on least-norn feedforward design. The nominal controller is used in between common pressure rail switches whereas the transition controller compensates for any disturbance that common pressure rail switchings inflict on the system. The control strategy has been experimentally validated on both a medium pressure (200bar) hardware-in-the-loop (HIL) testbed and a high pressure (300+bar) HIL testbed. An efficient and power-dense integrated electric-hydraulic machine consisting of an axial flux electric machine and a radial hydrostatic piston hydraulic machine has been designed, constructed and tested. The machine has an active material power density of 6.1kW/kg, a rated speed of 12500 RPM, and a design efficiency of 85%. This is among the highest power density electric machines using conventional materials. While the integrated machine was designed for modulating the hydraulic power within the HHEA, it can also be used in other applications.

24 POWER TRANSMISSION AND DISTRIBUTION↗