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A Synoptic System for Capturing Ecosystem Control Points Across Terrestrial‐Aquatic Interfaces
Interconnected landscape features such as terrestrial‐aquatic interfaces play an outsized role in biogeochemical cycles as ecosystem control points, but it is notoriously challenging to characterize these. Here, we document a synoptic sensor network design that is (a) flexible to accommodate diverse ecosystem interfaces and gradients, (b) adaptable to monitoring and modeling needs of small and large projects alike, (c) standardized for intercomparability across sites and field experiments, and (d) adequately replicated to capture heterogeneity of each parameter monitored. This real‐time monitoring of surface water, groundwater, soil, and vegetation supports configuration and evaluation of models that span upland, wetland, open water strata, and transitions between them. We established the network at seven sites along the Chesapeake Bay and Lake Erie coastlines, including large‐scale flood manipulation experiments in both regions. A central design element is “one data logger program to rule them all”—a collection of sensor‐specific modules deployed on 40 loggers controlling ∼2,000 sensors, with the goal of streamlining maintenance, debugging, and reproducible data processing. The network generates ∼6 M observations per month, capturing system dynamics at the broad spatial and fine temporal scales needed to initialize and benchmark models; measurement frequency can be modified remotely to capture events. This network design has also revealed behaviors not represented in Earth system models, such as transient groundwater oxygen pulses. Completely documented and open source, this standardized, flexible, and efficient sensor network design can reduce barriers to understanding environmental changes and ecosystem responses across systems and scales.
Genetic circuit characterization by inferring RNA polymerase movement and ribosome usage
To perform their computational function, genetic circuits change states through a symphony of genetic parts that turn regulator expression on and off. Debugging is frustrated by an inability to characterize parts in the context of the circuit and identify the origins of failures. Here, we take snapshots of a large genetic circuit in different states: RNA-seq is used to visualize circuit function as a changing pattern of RNA polymerase (RNAP) flux along the DNA. Together with ribosome profiling, all 54 genetic parts (promoters, ribozymes, RBSs, terminators) are parameterized and used to inform a mathematical model that can predict circuit performance, dynamics, and robustness. The circuit behaves as designed; however, it is riddled with genetic errors, including cryptic sense/antisense promoters and translation, attenuation, incorrect start codons, and a failed gate. While not impacting the expected Boolean logic, they reduce the prediction accuracy and could lead to failures when the parts are used in other designs. Finally, the cellular power (RNAP and ribosome usage) required to maintain a circuit state is calculated. This work demonstrates the use of a small number of measurements to fully parameterize a regulatory circuit and quantify its impact on host.
Production Operations Management System (POMS) for Fermilab Experiments
The Production Operations Management System (POMS) software allows production teams and analysis groups across multiple Fermilab experiments to launch, modify and monitor large scale campaigns of related Monte Carlo or data processing jobs, and currently manages the majority of production computing of experiments at Fermilab.POMS provides a web service interface that enables automated job submission on distributed resources according to customers’ requests, as well as subsequent monitoring of those submissions as well as recovery of failed submissions, debugging and record keeping.POMS interfaces with existing HEP data access, processing, movement and monitoring tools at Fermilab, including Jobsub (for job submission), SAM (for data management), and Landscape (for monitoring), and in combination with them handles the creation of intermediate datasets of files for multistage campaigns.POMS visualizes these campaigns with an interactive GUI interface. An important feature of POMS is a one-to-one connection between the GUI campaign visualizer and a text based representation of the complete campaign configuration. An extensible library of template campaign configurations is available. The templates are user modifiable and map cleanly to and from the GUI description of the campaign.This paper will discuss the current usage, history, and some technical details of POMS, as well as planned future extensions, particularly interfacing with Rucio as well as SAM for file movement.
Multithreading ATLAS offline software: A retrospective
For Run 3, ATLAS redesigned its offline software, Athena, so that the main workflows run completely multithreaded. The resulting substantial reduction in the overall memory requirements allows for better use of machines with many cores. This note will discuss the performance achieved by the multithreaded reconstruction, the process of migrating the large ATLAS code base, and tools and techniques that were useful in debugging threading-related problems.
High density, multi-range analog output Versa Module Europa board for control system applications
A new VMEDAC64, 12-bit 64 channel digital-to-analog converter, a Versa Module Europa (VME) module, features 64 analog voltage outputs with user selectable multiple ranges, has been developed for control system applications at Inter University Accelerator Centre. The FPGA (Field Programmable Gate Array) is the module's core, i.e., it implements the DAC control logic and complexity of VMEbus slave interface logic. The VMEbus slave interface and DAC control logic are completely designed and implemented on a single FPGA chip to achieve high density of 64 channels in a single width VME module and will reduce the module count in the control system applications, and hence will reduce the power consumption and cost of overall system. One of our early design goals was to develop the VME interface such that it can be easily integrated with the peripheral devices and satisfy the timing specifications of VME standard. The modular design of this module reduces the amount of time required to develop other custom modules for control system. The VME slave interface is written as a single component inside FPGA which will be used as a basic building block for any VMEbus interface project. The module offers multiple output voltage ranges depending upon the requirement. The output voltage range can be reduced or expanded by writing range selection bits in the control register. The module has programmable refresh rate and by default hold capacitors in the sample and hold circuit for each channel are charged periodically every 7.040 ms (i.e., update frequency 284 Hz). Each channel has software controlled output switch which disconnects analog output from the field. The modularity in the firmware design on FPGA makes the debugging very easy. On-board DC/DC converters are incorporated for isolated power supply for the analog section of the board.
Study of beam transverse properties of a thermionic electron gun for application to a compact THz free electron laser
A novel thermionic electron gun adopted for use in a high power THz free electron laser (FEL) is proposed in this paper. By optimization of the structural and radiofrequency (RF) parameters, the physical design of the gun is performed using dynamic calculations. Velocity bunching is used to minimize the bunch's energy spread, and the dynamic calculation results indicate that high quality beams can be provided. The transverse properties of the beams generated by the gun are also analyzed. The novel RF focusing effects of the resonance cavity are investigated precisely and are used to establish emittance compensation, which enables the injector length to be reduced. In addition, the causes of the extrema of the beam radius and the normalized transverse emittance are analyzed and interpreted, respectively, and slice simulations are performed to illustrate how the RF focusing varies along the bunch length and to determine the effects of that variation on the emittance compensation. Finally, by observation of the variations of the beam properties in the drift tube behind the electron gun, prospective assembly scenarios for the complete THz-FEL injector are discussed, and a joint-debugging process for the injector is implemented.
A field programmable gate array-based timing and control system for the dynamic compression sector
A field programmable gate array (FPGA)-based timing and trigger control system has been developed for the Dynamic Compression Sector (DCS) user facility located at the Advanced Photon Source (APS) at Argonne National Laboratory. The DCS is a first-of-its-kind capability dedicated to dynamic compression science. All components of the DCS laser shock station—x-ray choppers, single-shot shutter, internal laser triggers, and shot diagnostics—must be synchronized with respect to the arrival of x rays in the hutch. An FPGA synchronized to the APS storage ring radio frequency clock (352 MHz) generates trigger signals for each stage of the laser and x-ray shutter system with low jitter. The developed FPGA-based control system was the first system used to control the laser and the shutter system since its commissioning, and it has been developing since then to improve the timing jitter. The system is composed of a Zynq FPGA, a debug card, line drivers, and a power supply. The delay and offsets of the trigger signals can be adjusted by using a user-friendly graphical user interface with high precision. Here, the details of the system architecture, timing requirements, firmware, and software implementation along with the performance evaluation are presented in this paper. The system offers low timing jitter (15.5 ps rms) with respect to the APS 352 MHz clock, suitable for the 100 ps (FWHM) x-ray bunch duration at the APS.
Methods for analysing the quality of the element base of quantum information technologies
Methods for analysing the quality of the element base of quantum information technologies are considered. Methods for simulating quantum operations with allowance for quantum noise, based on the formalism of quantum operations (operator sum method and Choi – Jamiolkowski isomorphism), are described. Results of simulating some one- and two-qubit quantum transformations with allowance for the amplitude and phase relaxation and the presence of depolarising noise are reported. The quantum state tomography, based on the root approach and maximum likelihood method, is considered. The method of guaranteed estimation of quantum tomography accuracy, which implies quantitative estimation of measurement results, is described. Tomography of a single-qubit transformation on a superconducting quantum processor (IBM) is performed. The practical purpose of the study is to provide high quality and efficiency of quantum information technologies. The results obtained can be used to improve the quality of logic gates of quantum computers and debug the procedures of quantum state control in quantum cryptography problems. The bibliography includes 28 references. (quantum technology)
Efficient monitoring of CRAB jobs at CMS
CRAB is a tool used for distributed analysis of CMS data. Users can submit sets of jobs with similar requirements (tasks) with a single request. CRAB uses a client-server architecture, where a lightweight client, a server, and ancillary services work together and are maintained by CMS operators at CERN. As with most complex software, good monitoring tools are crucial for efficient use and longterm maintainability. This work gives an overview of the monitoring tools developed to ensure the CRAB server and infrastructure are functional, help operators debug user problems, and minimize overhead and operating cost. This work also illustrates the design choices and gives a report on our experience with the tools we developed and the external ones we used.
Effective HTCondor-based monitoring system for CMS
The CMS experiment at the LHC relies on HTCondor and glideinWMS as its primary batch and pilot-based Grid provisioning systems, respectively. Given the scale of the global queue in CMS, the operators found it increasingly difficult to monitor the pool to find problems and fix them. The operators had to rely on several different web pages, with several different levels of information, and sift tirelessly through log files in order to monitor the pool completely. Therefore, coming up with a suitable monitoring system was one of the crucial items before the beginning of the LHC Run 2 in order to ensure early detection of issues and to give a good overview of the whole pool. Our new monitoring page utilizes the HTCondor ClassAd information to provide a complete picture of the whole submission infrastructure in CMS. The monitoring page includes useful information from HTCondor schedulers, central managers, the glideinWMS frontend, and factories. It also incorporates information about users and tasks making it easy for operators to provide support and debug issues.
Benchmarking characterization methods for noisy quantum circuits
Effective methods for characterizing the noise in quantum computing devices are essential for programming and debugging circuit performance. Existing approaches vary in the information obtained as well as the amount of quantum and classical resources required, with more information generally requiring more resources. Here we benchmark the characterization methods of gate set tomography, Pauli channel noise reconstruction, and empirical direct characterization for developing models that describe noisy quantum circuit performance on a 27-qubit superconducting transmon device. We evaluate these models by comparing the accuracy of noisy circuit simulations with the corresponding experimental observations. Here, we find that the agreement of noise model to experiment does not correlate with the information gained by characterization and that the underlying circuit strongly influences the best choice of characterization approach. Empirical direct characterization scales best of the methods we tested and produced the most accurate characterizations across our benchmarks.
Distributed Order Recording Techniques for Efficient Record-and-Replay of Multi-threaded Programs
After all these years and all these other shared memory programming frameworks, OpenMP is still the most popular one. However, its greater levels of non-deterministic execution makes debugging and testing more challenging. The ability to record and deterministically replay the program execution is key to address this challenge. However, scalably replaying OpenMP programs is still an unresolved problem. In this paper, we propose two novel techniques that use Distributed Clock (DC) and Distributed Epoch (DE) recording schemes to eliminate excessive thread synchronization for OpenMP record and replay. Our evaluation on representative HPC applications with ReOMP, which we used to realize DC and DE recording, shows that our approach is 2-5x more efficient than traditional approaches that synchronize on every shared-memory access. Furthermore, we demonstrate that our approach can be easily combined with MPI-level replay tools to replay non-trivial MPI+OpenMP applications. We achieve this by integrating ReOMP into ReMPI, an existing scalable MPI record-and-replay tool, with only a small MPI-scale-independent runtime overhead.
Invited: Bambu: an Open-Source Research Framework for the High-Level Synthesis of Complex Applications
This paper presents the open-source High-Level Synthesis research framework Bambu. The framework provides an open-source starting point to experiment with new ideas across High-Level Synthesis, high-level verification and debugging, FPGA/ASIC design, design flow space exploration, and parallel hardware accelerator design. The tool accepts as input standard C/C++ specifications and compiler intermediate representations (IRs) coming from the well-known Clang/LLVM and GCC com- pilers. The broad spectrum and flexibility of input formats allow the electronic design automation (EDA) research community to explore and integrate new transformations and optimizations. The easily extendable modular framework already includes many op- timizations and HLS benchmarks. The integration with synthesis and verification backends (commercial and open-source) allows researchers to quickly test any new finding and easily obtain performance and resource usage metrics for a given application. Different FPGA devices are supported from several different vendors: AMD/XILINX, Intel/Altera, Lattice Semiconductor, and NanoXplore. Finally, integration with the OpenRoad open-source end-to-end silicon compiler perfectly fits with the recent push towards open-source EDA.
A Remote Development Process and Platform for Power Electronic Systems
Like many areas in research and development, power electronic and distributed energy resource research and development slowed during the COVID pandemic. While the presence of the virus has reduced and workers are returning to shared offices, uncertainty of potential future challenges are still present. This work proposes a development and testing network that provides researchers the ability to operate remotely and coordinate control and debug activities for power electronic systems. This development and testing network has been demonstrated in both controller hardware-in-the-loop (C-HIL) and hardware testing.
Scalable Performance Awareness for In Situ Scientific Applications
Part of the promise of exascale computing and the next generation of scientific simulation codes is the ability to bring together time and spatial scales that have traditionally been treated separately. This enables creating complex coupled simulations and in situ analysis pipelines, encompassing such things as "whole device" fusion models or the simulation of cities from sewers to rooftops. Unfortunately, the HPC analysis tools that have been built up over the preceding decades are ill suited to the debugging and performance analysis of such computational ensembles. In this paper, we present a new vision for performance measurement and understanding of HPC codes, MonitoringAnalytics (MONA). MONA is designed to be a flexible, high performance monitoring infrastructure that can perform monitoring analysis in place or in transit by embedding analytics and characterization directly into the data stream, without relying upon delivering all monitoring information to a central database for post-processing. It addresses the trade-offs between the prohibitively expensive capture of all performance characteristics and not capturing enough to detect the features of interest. We demonstrate several uses of MONA; capturing and indexing multi-executable performance profiles to enable later processing, extraction of performance primitives to enable the generation of customizable benchmarks and performance skeletons, and extracting communication and application behaviors to enable better control and placement for the current and future runs of the science ensemble. Relevant performance information based on a system for MONA built from ADIOS and SOSflow technologies is provided for DOE science applications and leadership machines.
Online Monitoring System for Performance Fault Detection
To achieve the exaFLOPS performance within a contain power budget, next supercomputers will feature hundreds of millions of components operating at low- and near-threshold voltage. As the probability that at least one of these components fails during the execution of an application approaches certainty, it seems unrealistic to expect that any run of a scientific application will not experience some performance faults. We believe that there is need of a new generation of light-weight performance and debugging tools that can be used online even during production runs of parallel applications and that can identify performance anomalies during the application execution. In this work we propose the design and implementation of a monitoring system that continuously inspects the evolution of run
Asynchronous Runtimes in Action: An Introspective Framework for a Next Gen Runtime
One of the most critical challenges that new high performance systems face is the lack of system software support for these large scale systems. Investment on system stack components is essential in the development, debugging and optimization of the new emerging programming models. These emerging models have the promise to better utilize the vast hardware resources available in current and future systems. To aid in the development of applications and new system stacks, runtimes, as instances of their respective execution models, need to produce facilities to introspect their inner workings and allow an indepth attribution of performance bottlenecks and computational patterns. In other words, the runtime systems need to reduce their opacity to observers so that users of a novel program execution model can adapt their designs to fit the intended model usage, regardless of the layer that they are working on. This design/development loop (akin to co-design) enables synergistic opportunities across the entire computational stack. This paper presents the design and implementation of a simple “gray” box performance attribution harness running inside a fine grain runtime system: the Open Community Runtime (OCR). We showcase what such a framework can indicate regarding the runtime behavior while running at scale. To this end, we have designed a set of synthetic scenarios aimed to test the runtime at their best and worst cases. We present an analysis of the most important runtime features, properties and idiosyncrasies that will affect the development of new runtime features, algorithmic selection, and application development.