CCSDS Spacecraft Uplink Protocol in a Space-Qualified ASIC
This paper describes the capabilities of the Hardware Command Decode (HCD) application specific integrated circuit (ASIC) developed for the Cassini spacecraft.
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Results for “application specific integrated circuits”
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Single-Event Effect Testing of the PNI RM3100 Magnetometer for Space Applications
The results of a destructive single-event effect susceptibility radiation test of the PNI RM3100 magnetometer sensor, specifically the MagI 2 C ASIC (application-specific integrated circuit) on the sensor board are presented. The sensor is a low-resource commercial off-the-shelf (COTS) magneto-inductive magnetometer. The device was monitored for destructive events and functional interruptions during exposure to a heavy ion beam at the Lawrence Berkeley National Laboratory's 88′′ Cyclotron. The RM3100 did not experience any destructive single-event effects when irradiated to a total fluence of 1.4 × 10 7 cm −2 at an effective linear energy transfer (LET) of 76.7 MeV cm 2 mg −1 while operated at nominal voltage (3.3 V) and elevated temperature (85 ∘C). When these results are combined with previous total ionizing dose tests showing no failures up to 150 kRad (Si), we conclude that the PNI RM3100 is extremely radiation tolerant and can be used in a variety of space environments.
Mark B. Moldwin↗
SODA: a New Synthesis Infrastructure for Agile Hardware Design of Machine Learning Accelerators
Next generation systems, such as edge devices, will have to provide efficient processing of machine learning (ML) algorithms along several metrics, including energy, performance, area, and latency. However, the quickly evolving field of ML makes it extremely difficult to generate accelerators able to support a wide variety of algorithms. At the same time, designing accelerators in hardware description languages (HDLs) by hand is hard and time consuming, and does not allow quick exploration of the design space. This paper discusses the SODA synthesizer, an automated open source high-level ML framework-to-Verilog compiler targeting ML Application-Specific Integrated Circuits (ASICs) chiplets based on the LLVM infrastructure. The SODA synthesizers will allow implementing optimal designs by combining templated and fully tunable IPs and macros, and fully custom components generated through high-level synthesis. All these components will be provided through an extendable resource library, characterized with both commercial and open source logic design flows. Through a closed loop design space exploration engine, developers will be able to quickly explore their hardware designs along different dimension
Minutoli, Marco↗
Towards Automatic and Agile AI/ML Accelerator Design with End-to-End Synthesis
Domain-specific designs offer greater energy efficiency and performance gain than general-purpose processors. For this reason, modern system-on-chips have a significant portion of their silicon area with custom accelerators. However, designing hardware by hand is laborious and time-consuming, given the large design space and the performance, power, and area constraints that are not realized in the software. Moreover, domain-specific algorithms (e.g., machine learning models) are evolving quickly, challenging the accelerator design further. To address these issues, this paper presents SODA Synthesizer, an automated open-source high-level ML framework to Verilog modular compiler targeting AI/ML Application-Specific Integrated Circuits (ASICs) accelerators. SODA tightly couples the Multi- Level Intermediate Representation (MLIR) compiler infrastructure [24] and open-source HLS approaches. Thus, SODA can support various ML frameworks and algorithms and can perform optimizations that combine specialized architecture templates and conventional HLS to generate the hardware modules. In addition, SODA’s closed-loop design space exploration (DSE) engine allows developers to perform end-to-end design space explorations on different metrics and technology nodes.
Zhang, Jeff↗
Peak Prediction Using Multi Layer Perceptron (MLP) for Edge Computing ASICs Targeting Scientific Applications
High data rate detectors play an integral part in scientific research and their development is actively pursued at High Energy Physics (HEP) facilities around the world. Edge Machine Learning (ML) offers the ability to reduce data rates by integrating ML algorithms into Application Specific Integrated Circuits (ASICs) on the front end electronics. In this work, we explore a set of neural network architectures for predicting the peak amplitudes in the detector's sensor response. We have designed and synthesized several MLP based neural networks comparing their inference accuracy, power consumption, and area targeting for minimal latency. The neural networks are synthesized in a commercial 65nm process. The effect of quantizing the network's weights and biases on hardware performance and area is reported. We also conduct design space exploration to compare between design alternatives
47 OTHER INSTRUMENTATION↗
An Open-Source Framework for Rapid Validation of Scientific ASICs
Spacely is an open-source framework for the post-silicon validation of analog, digital, and mixed-signal ASICs (Application-Specific Integrated Circuits) which maximizes the reuse of hardware and software, reducing the time taken to achieve meaningful test results. Spacely specifically addresses the needs of small, flexible ASIC design teams commonly found in academia or research institutions which benefit most from sharing the overhead of test stand creation between many unique ASIC designs. Spacely is a set of software, firmware, and design practices. It targets two primary hardware platforms (NI-PXI and Caribou) as well as offering extensible support for bench instruments. Spacely provides a high-level Python interface to all test hardware for accessibility, while also giving more sophisticated teams the opportunity to integrate custom test firmware. The design principles of Spacely are presented, along with a demonstrative example of using Spacely to test a pixel detector readout ASIC.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
Automating Testing of DUNE Electronics via a Finite State Machine
The Deep Underground Neutrino Experiment (DUNE) is a flagship international collaboration designed to study neutrinos—tiny, nearly massless particles that may hold answers to fundamental questions about the Universe. Fermilab’s Robotic Test Stand (RTS) plays a critical role in ensuring the quality of approximately 50,000 Application-Specific Integrated Circuit (ASIC) chips that will be used in DUNE’s massive liquid argon detectors. These electronics will be inside the cryostat; therefore, they will need to have a high yield of working chips and low noise. To improve the automation and reliability of the RTS, this project focused on designing and implementing a Python-based finite state machine (FSM) to manage chip handling workflows. The FSM was developed as a modular software framework to coordinate robotic arm movements, manage chip tray positions, and monitor system states during testing. Key features include robust error handling routines, a pause/resume system for safe mid-cycle interruptions, and a simulation mode for iterative testing without hardware dependencies. The system was designed to prepare for seamless integration with RTS hardware components such as the robotic arm and vision system. This integration will streamline collaboration and enable efficient deployment of updates across the six institutions performing testing. The outcomes of this internship contribute to Fermilab’s mission to advance high-energy physics and support the DOE’s national goals by directly improving the testing of equipment to be used in DUNE. The project also provided valuable experience in software design and contributing to the success of DUNE.
Kang, Caleb [Fermilab]↗
On-chip probabilistic inference for charged-particle tracking at the sensor edge
Modern scientific instruments operate under increasingly extreme constraints on bandwidth, latency, and power. Inference at the sensor edge determines experimental data collection efficiency by deciding which information to save for further analysis. Particle tracking detectors at the Large Hadron Collider exemplify this challenge: pixelated silicon sensors generate rich spatiotemporal ionization patterns, yet most of this information is discarded due to data-rate limitations. Concurrently, advancements in co-design tools provide rapid turn-around for incorporating machine learning into application-specific integrated circuits, motivating designs for particle detectors with new integrated technologies. We demonstrate that neural networks embedded in the front-end electronics can infer charged-particle kinematic parameters from a single silicon layer. We regress hit positions and incident angles with calibrated uncertainties, while satisfying stringent constraints on numerical precision, latency, and silicon area. Our results establish a path toward probabilistic inference directly at the edge, opening new opportunities for intelligent sensing in high-rate scientific instruments.
Das, Arghya Ranjan [Purdue U.] (ORCID:000000018451↗
A Sub-electron-noise Skipper-CCD Readout ASIC with Improved Channel-to-channel Isolation and an Integrated Cryogenic Voltage Reference
The MIDNA application specific integrated circuits (ASICs) are a series of skipper-CCD readout chips fabricated in a 65 nm low-power CMOS process that implement a correlated double sampling signal processing chain based on dual-slope integrators. They are capable of working from room to cryogenic temperatures, down to 84 K. The present iteration of the ASIC has been fabricated including several design updates and the addition of an on-chip voltage reference, resulting in improved performance. This work presents the main vulnerabilities solved, the changes carried out, and the resulting performance benefits. Measurements with a skipper-CCD and the ASIC at 140 K showed that the single-electron resolution can be reached by averaging the measured charge in the analog domain using the analog pile-up technique with a readout noise as low as 0.11 erms of equivalent charge for 1200 samples. The channel-to-channel crosstalk was also characterized showing values better than -62 dB.
Alcalde Bessia, Fabricio↗
A Sub-electron-noise Skipper-CCD Readout ASIC with Improved Channel-to-channel Isolation and an Integrated Cryogenic Voltage Reference
The MIDNA application specific integrated circuits (ASICs) are a series of skipper-CCD readout chips fabricated in a 65 nm low-power CMOS process that implement a correlated double sampling signal processing chain based on dual-slope integrators. They are capable of working from room to cryogenic temperatures, down to 84 K. The present iteration of the ASIC has been fabricated including several design updates and the addition of an on-chip voltage reference, resulting in improved performance. This work presents the main vulnerabilities solved, the changes carried out, and the resulting performance benefits. Measurements with a skipper-CCD and the ASIC at 140 K showed that the single-electron resolution can be reached by averaging the measured charge in the analog domain using the analog pile-up technique with a readout noise as low as 0.11 erms of equivalent charge for 1200 samples. The channel-to-channel crosstalk was also characterized showing values better than -62 dB.
Alcalde Bessia, Fabricio↗
Graphical User Interface for a Biasing Board for the PSEC6
The PSEC6 is an application-specific integrated circuit (ASIC) designed for a readout system for a large area picosecond photodetector (LAPPD). The PSEC6 is currently in fabrication and pending testing. The testing system for the PSEC5, the previous iteration of the ASIC, required expensive and non-portable equipment, because the ASIC needs twelve adjustable reference voltages. The new testing system consists of an low-cost, open-source, cross-platform graphical user interface (GUI), a digital system, and a biasing board. The digital system is the interface between the GUI and biasing board, and can be implemented on a microcontroller or field-programmable gate array (FPGA). The biasing board contains twelve digital-to-analog converters (DACs) that are configurable via the GUI, which gives users the ability to write voltage values to all or specific DACs. The GUI was developed in C on Linux using the widget library GTK4 and cross-compiled for Windows compatibility. I2C and SPI protocols were implemented on an Adafruit Feather ESP32-S3 microcontroller to write commands to the DACs and PSEC6. A hardware implementation of the I2C protocol is in development on an FPGA. Since LAPPDs will be used by the Accelerator Neutrino Neutron Interaction Experiment (ANNIE) at Fermilab, the PSEC6 testing system in this internship project can potentially benefit future neutrino research. The project is relevant to the Department of Energy’s microelectronics mission, because the PSEC6 is an ASIC that will handle fast time signals arriving from the detector for readout. It also provided experience with building a cross-platform user interface, practicing digital design and implementation in hardware description language (HDL), and using simulations to inform new design iterations.
Guerrero, Sasha Camila [North Central Coll.]↗
Characterization of System on a Chip (SoC) Single Event Upset (SEU) Responses Using SEU Data, Classical Reliability Models, and Space Environment Data
We propose a method for the application of single event upset (SEU) data towards the analysis of complex systems using transformed reliability models (from the time domain to the particle fluence domain) and space environment data.
Single Event Upsets (SEUs)↗
Integrated Circuit Design for Radiation-Hardened Charge-Sensitive Amplifier Survived up to 2 Mrad
According to the continuous development of metal-oxide semiconductor (MOS) fabrication technology, transistors have naturally become more radiation-tolerant through steadily decreasing gate-oxide thickness, increasing the tunneling probability between gate-oxide and channel. Unfortunately, despite this radiation-hardened property of developed transistors, the field of nuclear power plants (NPPs) requires even higher radiation hardness levels. Particularly, total ionizing dose (TID) of approximately 1 Mrad could be required for readout circuitry under severe accident conditions with 100 Mrad around a reactor in-core required. In harsh radiating environments such as NPPs, sensors such as micro-pocket-fission detectors (MPFD) would be a promising technology to be operated for detecting neutrons in reactor cores. For those sensors, readout circuits should be fundamentally placed close to sensing devices for minimizing signal interferences and white noise. Therefore, radiation hardening ability is necessary for the circuits under high radiation environments. This paper presents various integrated circuit designs for a radiation hardened charge-sensitive amplifier (CSA) by using SiGe 130 nm and Si 180 nm fabrication processes with different channel widths and transistor types of complementary metal-oxide-semiconductor (CMOS) and bipolar CMOS (BiCMOS). These circuits were tested under γ–ray environment with Cobalt-60 of high level activity: 490 kCi. The experiment results indicate amplitude degradation of 2.85%–34.3%, fall time increase of 201–1730 ns, as well as a signal-to-noise ratio (SNR) of 0.07–11.6 dB decrease with irradiation dose increase. These results can provide design guidelines for radiation hardening operational amplifiers in terms of transistor sizes and structures.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
Cryogenic electronics for noble liquid neutrino detectors
In this paper we present the general features of cryogenic (or “cold”) electronics for noble liquid time projection chambers, with design principles and details for neutrino physics, a brief history of the technology and details of recent research and development that is driving the design of the detectors under construction. Finally, some comments on future R&D envisioned and the impact of this work on other fields is described. “Cold” in the context of this work applies to CMOS devices operated at 77 K and above, at liquids temperatures of LAr (89 K), LKr (125 K) and LXe (165 K), with most of the tests performed in, or at LN 2 (77 K). Additionally, the paper is concentrated on the design of cold electronics for large liquid argon TPCs, those that have been successfully operated, MicroBooNE and ProtoDUNE, and those designed or under construction, such as SBND and DUNE first and second 10 kton modules. The high performance achieved with MicroBooNE and ProtoDUNE – a high signal-to-noise ratio combined with high stability of response – is mainly due to the integral approach to design and construction of sensing electrodes with cold readout electronics in a modular approach with the cryostat signal feed-throughs incorporating warm interface electronics into a Faraday cage with the cryostat. The integral concept is described in some detail in this paper.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
Fault tolerant state machines
Explore the source record for details and available documents.
state machines↗
Introduction to FPGA Devices and The Challenges for Critical Application - A User's Perspective
This presentation is an introduction to Field Programmable Gate Array (FPGA) devices and the challenges of critical application including: safety, reliability, availability, recoverability, and security.
Application Specific Integrated Circuit (ASIC)↗
The Effects of Race Conditions When Implementing Single-Source Redundant Clock Trees in Triple Modular Redundant Synchronous Architectures
We present the challenges that arise when using redundant clock domains due to their time-skew. Radiation data show that a singular clock domain provides an improved triple modular redundant (TMR) scheme over redundant clocks.
Single Event Upset (SEU)↗
Analyzing Test-As-You-Fly Single Event Upset (SEU) Responses using SEU Data, Classical Reliability Models, and Space Environment Data
We propose a method for the application of single event upset (SEU) data towards the analysis of complex systems using transformed reliability models (from the time domain to the particle fluence domain) and space environment data.
Application Specific Integrated Circuit (ASIC)↗