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dbprocessing

dbprocessing is a python framework for automating data processing pipelines. The dbprocessing package uses a configuration file to define the input, intermediate, and output data products for a particular data type as well as the processes that connect those data products. In addition, dbprocessing uses python scripts called inspectors to determine if a particular file matches a configured data product. If a particular data product is found, it is ingested into the dbprocessing database (sqlite3 or postgres) which then triggers all of the chained processes to the final data product. While the framework is written in python, it can run software in any language but may require a “wrapper” to translate the dbprocessing command line arguments to the form expected by the software.

Walker, Andrew↗

Studies of the trigger performance of the ICARUS T600 detector at Fermilab

In recent years, experimental neutrino anomalies were reported: if confirmed, they could hint at the existence of additional sterile neutrino states participating in the mixing phenomenon. The future Short-Baseline Neutrino (SBN) project at Fermilab will pursue sterile neutrino searches, by exploiting three Liquid Argon (LAr) Time Projection Chamber (TPC) detectors located on-axis along the Booster Neutrino Beam (BNB). Aside from SBND and MicroBooNE, ICARUS will be the far detector and will also be interested by the NuMI beam (off-axis). The trigger system is a key component of the detector: it is based on the coincidence of prompt signals from scintillation light in the LAr-TPC (recorded by a system of PhotoMultiplier Tubes, PMTs) with the proton spill extraction of the beam. The present system exploits a majority-based logic and may be complemented by a trigger system based on adder boards, that add the analog signals of the PMTs in groups of 15. Triggering on the sum may help in identifying events closer to the TPC walls, in which there is plenty of light collected by few PMTs and for which the majority condition may not be satisfied. Many tests were carried out to characterize the adder boards, both on the hardware and software sides.

43 PARTICLE ACCELERATORS↗

Bringing heterogeneity to the CMS software framework

The advent of computing resources with co-processors, for example Graphics Processing Units (GPU) or Field-Programmable Gate Arrays (FPGA), for use cases like the CMS High-Level Trigger (HLT) or data processing at leadership-class supercomputers imposes challenges for the current data processing frameworks. These challenges include developing a model for algorithms to offload their computations on the co-processors as well as keeping the traditional CPU busy doing other work. The CMS data processing framework, CMSSW, implements multithreading using the Intel Threading Building Blocks (TBB) library, that utilizes tasks as concurrent units of work. In this paper we will discuss a generic mechanism to interact effectively with non-CPU resources that has been implemented in CMSSW. In addition, configuring such a heterogeneous system is challenging. In CMSSW an application is configured with a configuration file written in the Python language. The algorithm types are part of the configuration. The challenge therefore is to unify the CPU and co-processor settings while allowing their implementations to be separate. We will explain how we solved these challenges while minimizing the necessary changes to the CMSSW framework. We will also discuss on a concrete example how algorithms would offload work to NVIDIA GPUs using directly the CUDA API.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

A VXS [VITA41] Trigger Processor for the 12GEV Experimental Programs at Jefferson Lab

The VXS_Trigger_Processor [VTP] was developed and commissioned for CLAS12 in the fall of 2016. This board is a VITA41 switch card and it collects data from a variety of front-end TDC and Flash ADC modules. The VTP has since been used in several experiments at Jefferson Lab serving as the L1 trigger module for a variety of detector types, such as stacked calorimeters, strip calorimeters, time-of-flight, Cerenkov, hodoscopes, drift chambers, and silicon strips. Trigger algorithms implemented include cluster finding (1D, 2D), drift chamber segment and road finding, geometry matching between various detectors, particle counting, and general global trigger bit processing. The VTP is also capable of reading out each front-end crate with up to 40Gbps Ethernet which is an enormous increase compared to the currently used 200MB/s VME bus. Recent progress has been made to show that a firmware and software upgrade can enable existing Jefferson Lab front-end crates to operate in a streaming DAQ mode. In February 2020, tests will be performed on a full calorimeter and matched hodoscope which are components of the CLAS12 Forward Tagger detector system with beam in Hall B. This paper details the hardware performance, triggered, and streaming applications that have been implemented using the VTP for several experiments at Jefferson Lab.

ABBOTT, David↗

The ATLAS Fast TracKer system

The ATLAS Fast TracKer (FTK) was designed to provide full tracking for the ATLAS high-level trigger by using pattern recognition based on Associative Memory (AM) chips and fitting in high-speed field programmable gate arrays. The tracks found by the FTK are based on inputs from all modules of the pixel and silicon microstrip trackers. The as-built FTK system and components are described, as is the online software used to control them while running in the ATLAS data acquisition system. Also described is the simulation of the FTK hardware and the optimization of the AM pattern banks. An optimization for long-lived particles with large impact parameter values is included. A test of the FTK system with the data playback facility that allowed the FTK to be commissioned during the shutdown between Run 2 and Run 3 of the LHC is reported. The resulting tracks from part of the FTK system covering a limited $\eta$-$\phi$ region of the detector are compared with the output from the FTK simulation. It is shown that FTK performance is in good agreement with the simulation.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

ALICE upgrades during the LHC Long Shutdown 2

A Large Ion Collider Experiment (ALICE) has been conceived and constructed as a heavy-ion experiment at the LHC. During LHC Runs 1 and 2, it has produced a wide range of physics results using all collision systems available at the LHC. In order to best exploit new physics opportunities opening up with the upgraded LHC and new detector technologies, the experiment has undergone a major upgrade during the LHC Long Shutdown 2 (2019–2022). This comprises the move to continuous readout, the complete overhaul of core detectors, as well as a new online event processing farm with a redesigned online-offline software framework. These improvements will allow to record Pb-Pb collisions at rates up to 50 kHz, while ensuring sensitivity for signals without a triggerable signature.

47 OTHER INSTRUMENTATION↗

The New Small Wheel electronics

The increase in luminosity, and consequent higher backgrounds, of the LHC upgrades require improved rejection of fake tracks in the forward region of the ATLAS Muon Spectrometer. The New Small Wheel upgrade of the Muon Spectrometer aims to reduce the large background of fake triggers from track segments that don't originate from the interaction point. The New Small Wheel employs two detector technologies, the resistive strip Micromegas detectors and the “small” Thin Gap Chambers, with a total of 2.45 million electrodes to be sensed. The two technologies require the design of a complex electronics system given that it consists of two different detector technologies and is required to provide both precision readout and a fast trigger. It will operate in a high background radiation region up to about 20 kHz/cm 2 at the expected HL-LHC luminosity of $\mathcal{L}$= 7.5 × 10 34 cm -2 s -1 . The architecture of the system is strongly defined by the GBTx data aggregation ASIC, the newly-introduced FELIX data router and the software based data handler of the ATLAS detector. The electronics complex of this new detector was designed and developed in the last ten years and consists of multiple radiation tolerant Application Specific Integrated Circuits, multiple front-end boards, dense boards with FPGA's and purpose-built Trigger Processor boards within the ATCA standard. The New Small Wheel has been installed in 2021 and is undergoing integration within ATLAS for LHC Run 3. It should operate through the end of Run 4 (December 2032). In this manuscript, the overall design of the New Small Wheel electronics is presented.

47 OTHER INSTRUMENTATION↗

Development and Implementation of Fault-Correction Algorithms in Fault Detection and Diagnostics Tools

A fault detection and diagnostics (FDD) tool is a type of energy management and information system that continuously identifies the presence of faults and efficiency improvement opportunities through a one-way interface to the building automation system and the application of automated analytics. Building operators on the leading edge of technology adoption use FDD tools to enable median whole-building portfolio savings of 8%. Although FDD tools can inform operators of operational faults, currently an action is always required to correct the faults to generate energy savings. A subset of faults, however, such as biased sensors, can be addressed automatically, eliminating the need for staff intervention. Automating this fault “correction” can significantly increase the savings generated by FDD tools and reduce the reliance on human intervention. Doing so is expected to advance the usability and technical and economic performance of FDD technologies. This paper presents the development of nine innovative fault auto-correction algorithms for Heating, Ventilation, and Air Conditioning pi(HVAC) systems. When the auto-correction routine is triggered, it overwrites control setpoints or other variables to implement the intended changes. It also discusses the implementation of the auto-correction algorithms in commercial FDD software products, the integration of these strategies with building automation systems and their preliminary testing.

field testing↗

Exploratory Investigation of Disengagements and Crashes in Autonomous Vehicles Under Mixed Traffic: An Endogenous Switching Regime Framework

Autonomous Vehicles (AVs) have a large potential to improve traffic safety but also pose some critical challenges. While AVs may help reduce crashes caused by human error, they still may experience failures of technologies and sensing, as well as decision-making errors in a mixed traffic environment. A disengagement refers to an AV transitioning control from autonomous systems to the trained test driver. The safety critical nature of disengagements makes it imperative to analyze disengagements and crashes together. In this study, we analyze both crashes and disengagements from real-world AV driving in California to fill the knowledge gap regarding the relationship between disengagements and crashes in a mixed traffic environment. A nested logit model was calibrated using three different outcomes: (1) disengagement with a crash, (2) disengagement with no crash, and (3) no disengagement with a crash. Furthermore, endogenous switching regime models were also calibrated to draw distinctions between the relation of disengagements and crashes while accounting for endogeneity effects. The results show that factors related to AV systems (such as software failures) and other roadway participants increase the propensity of a disengagement without a crash. Furthermore, AVs were observed to disengage less often as the technology matured over time. Marginal effects revealed an 8% decrease. The results thus suggest that disengagements are a part of AVs' safe performance and disengagement alerts may need to be triggered in order to avoid certain failures with current technology.

42 ENGINEERING↗

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.

47 OTHER INSTRUMENTATION↗

The Heavy Photon Search (HPS) Software Environment

The Heavy Photon Search (HPS) is an experiment at the Thomas Jefferson National Accelerator Facility (JLab) designed to search for a hidden sector photon (A’) in fixed-target electro-production. It uses a silicon microstrip tracking and vertexing detector placed inside a dipole magnet to measure charged particle trajectories and a fast lead-tungstate crystal calorimeter located just downstream of the magnet to provide a trigger and to identify electromagnetic showers. The HPS experiment uses both invariant mass and secondary vertex signatures to search for the A’. The experimental collaboration is small and quite heterogeneous: it is composed of members of the nuclear physics as well as particle physics communities, from universities and national labs from around the US and Europe. Enabling such a disparate group to concentrate on the physics aspects of the experiment required that the software be easy to install and use, and having such limited manpower meant that existing solutions had to be exploited. HPS has successfully completed two engineering runs and completed its first physics run in the summer of 2019. We begin with an overview of the physics goals of the experiment followed by a short description of the detector design. We then describe the software tools used to design the detector layout and simulate the expected detector performance. Event reconstruction involving track, cluster and vertex finding and fitting for both simulated and real data was, to first order, adopted from existing software originally developed for Linear Collider studies. Bringing it all together into a cohesive whole involved the use of multiple software solutions with common interfaces.

Graf, Norman↗

A Generic High Bandwidth Data Acquisition Card for Physics Experiments

In high energy physics and nuclear physics experiments particularly the ones based on particle accelerator, the data rate from the detector is usually in the order of Terabytes per second. This high throughput data from detector front-end electronics need to be transmitted to the back-end computing farm for high level event selection and building. A Data Acquisition (DAQ) system with features of high-density, scalable, easily upgradeable is crucial to simplify the readout architecture of whole experiment. This paper will introduce the design of a generic high bandwidth PCIe card which can be used as the important input output card in a scalable DAQ system. It can factorize front-end electronics from data handling, and reduce amount of custom hardware in favor of scalable detectorindependent commercial hardware and software. Besides the 48 channels of bidirectional high speed fiber optical links with frontends, it also supports to synchronize with the experiment timing system, and to fanout the clock and trigger information with a fixed latency to the front-end electronics.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Slow control and data acquisition systems in the Mu2e experiment

The Mu2e experiment at the Fermilab Muon Campus will search for the coherent neutrinolessconversion of a muon into an electron in the field of an aluminum nucleus with a sensitivityimprovement by a factor of 10,000 over existing limits. The Mu2e Trigger and Data AcquisitionSystem (TDAQ) usesotsdaqas the online Data Acquisition System (DAQ) solution. Developed atFermilab,otsdaqintegrates both theartdaqDAQ and theartanalysis frameworks for event transfer,filtering, and processing.otsdaqis an online DAQ software suite with a focus on flexibility andscalability and provides a multi-user, web-based, interface accessible through a web browser. Thedata stream from the detector subsystems is read by a software filter algorithm that selects eventswhich are combined with the data flux coming from a Cosmic Ray Veto System. The DetectorControl System (DCS) has been developed using the Experimental Physics and Industrial ControlSystem (EPICS) open source platform for monitoring, controlling, alarming, and archiving. TheDCS System has been integrated intootsdaq. A prototype of the TDAQ and the DCS systems hasbeen built at Fermilab’s Feynman Computing Center. In this paper, we report on the progress ofthe integration of this prototype in the onlineotsdaqsoftware.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Online DAQ and slow control interface for the Mu2e experiment

The Mu2e experiment at the Fermilab Muon Campus will search for the coherent neutrinolessconversion of a muon into an electron in the field of an aluminum nucleus with a sensitivityimprovement by a factor of 10,000 over existing limits. The Mu2e Trigger and Data AcquisitionSystem (TDAQ) usesotsdaqas the online Data Acquisition System (DAQ) solution. Developed atFermilab,otsdaqintegrates both theartdaqDAQ and theartanalysis frameworks for event transfer,filtering, and processing.otsdaqis an online DAQ software suite with a focus on flexibility andscalability and provides a multi-user, web-based, interface accessible through a web browser. Thedata stream from the detector subsystems is read by a software filter algorithm that selects eventswhich are combined with the data flux coming from a Cosmic Ray Veto System. The DetectorControl System (DCS) has been developed using the Experimental Physics and Industrial ControlSystem (EPICS) open source platform for monitoring, controlling, alarming, and archiving. TheDCS System has been integrated intootsdaq. A prototype of the TDAQ and the DCS systems hasbeen built at Fermilab’s Feynman Computing Center. In this paper, we report on the progress ofthe integration of this prototype in the onlineotsdaqsoftware.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Real-Time Testbed for Studying Cyberattacks and Defense in DER-integrated Smart Inverter Systems

In this paper, we propose a Hardware-in-the-Loop (HIL) simulation testbed suitable for the implementation and testing of realistic cyberattacks on grid-tied smart inverter systems integrated with Distributed Energy Resources (DER) that use the Distributed Network Protocol-3 (DNP3) protocol for communications between grid components. Specifically, our testbed combines a Real-Time Digital Simulator (RTDS) NovaCor device, outfitted with GNETx2 network interface cards, a gridtied DER topology implemented via the RTDS software package RSCAD, and a custom virtual network that emulates a man in the middle attacker. The Man-in-the-Middle (MITM) attacker captures DNP3 traffic and falsifies telemetry data in DNP3 packets to trigger unwarranted commands from a DNP3 controller that exploit smart inverter grid support functions. We choose DNP3 and implement grid support functions according to the IEEE Std. 1547-2018 mandated for the interconnection and interoperability of DER power systems with associated power components. Furthermore, we develop a protocol payload agnostic attack detection framework that leverages the round-trip time (RTT) anomalies between DNP3 requests and responses and can detect the presence of attacks without having to analyze the payload’s contents, while balancing trade-offs between false alarm counts, missed detections, and time to detection. To facilitate further research, we publicly release benign and attack network traffic exchanged between various sensors, controllers, and actuators in our grid-tied inverter testbed.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Enhancements and Deployment of the TDAQ System for the Mu2e Experiment

The Real Time Processing Systems Division at Fermilab has deployed new features to the Off-The-Shelf Data Acquisition framework (otsdaq) for the Mu2e experiment. The Mu2e experiment will search for the coherent neutrino-less conversion of a muon into an electron in the field of an aluminum nucleus with a sensitivity improvement of 10,000 times over existing limits. Such a charged lepton flavor-violating reaction probes new physics at a scale unavailable at present or planned high-energy colliders. The Mu2e Trigger and Data Acquisition (TDAQ) system uses otsdaq as its online Data Acquisition System (DAQ) framework. otsdaq integrates the artdaq and art frameworks for event transfer, filtering, and processing. otsdaq is a web-based DAQ software suite focusing on flexibility and scalability and provides a multi-user interface accessible through a web browser. artdaq handles the entire data stream, which is read over the peripheral component interconnect express (PCIe) bus to a software filter algorithm that selects events combined with the data flux coming from a cosmic-ray veto (CRV) system. Detector front-ends are configured through the PCIe bus by customized otsdaq plugins. The otsdaq slow controls infrastructure has been further developed using the experimental physics and industrial control system (EPICS) open-source platform for monitoring, controlling, alarming, and archiving. The detector control system (DCS) for Mu2e has been integrated into otsdaq. The production TDAQ and DCS system has been deployed at the experimental hall and is being debugged and optimized for experiment operations. We report on the feature enhancements and deployment of otsdaq for Mu2e.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Analysis and Grading of the Test Performance of PS Modules for the CMS Phase-2 Outer Tracker Upgrade

The Outer Tracker of the CMS experiment provides information about the trajectory of charged particles produced in proton-proton collisions at the LHC. During the High Luminosity LHC upgrade, scheduled for the late 2020s, the Outer Tracker will be replaced with new modules capable of transmitting data to the L1 Trigger. These modules are being assembled at several facilities around the world, including Fermilab, necessitating coordinated standards of module quality. Here I discuss the development of POTATO (Phase-2 Outer Tracker Analyzer of Test Outputs), a C++ software which provides a standardized procedure for analyzing and grading test results of the Outer Tracker modules. The particular focus of this poster is on the analysis and grading of the PS (pixel-strip) modules in POTATO.

Riggall, Caroline↗

Investigating resource-efficient neutron/gamma classification ML models targeting eFPGAs

There has been considerable interest and resulting progress in implementing machine learning (ML) models in hardware over the last several years from the particle and nuclear physics communities. A big driver has been the release of the Python package, hls4ml, which has enabled porting models specified and trained using Python ML libraries to register transfer level (RTL) code. So far, the primary end targets have been commercial field-programmable gate arrays (FPGAs) or synthesized custom blocks on application specific integrated circuits (ASICs). However, recent developments in open-source embedded FPGA (eFPGA) frameworks now provide an alternate, more flexible pathway for implementing ML models in hardware. These customized eFPGA fabrics can be integrated as part of an overall chip design. In general, the decision between a fully custom, eFPGA, or commercial FPGA ML implementation will depend on the details of the end-use application. In this work, we explored the parameter space for eFPGA implementations of fully-connected neural network (fcNN) and boosted decision tree (BDT) models using the task of neutron/gamma classification with a specific focus on resource efficiency. We used data collected using an AmBe sealed source incident on Stilbene, which was optically coupled to an OnSemi J-series silicon photomultiplier (SiPM) to generate training and test data for this study. We investigated relevant input features and the effects of bit-resolution and sampling rate as well as trade-offs in hyperparameters for both ML architectures while tracking total resource usage. The performance metric used to track model performance was the calculated neutron efficiency at a gamma leakage of 10 -3 . The results of the study will be used to aid the specification of an eFPGA fabric, which will be integrated as part of a test chip.

47 OTHER INSTRUMENTATION↗