Results for “FPGA” — Page 2

NASA NTRS2018

Power and Signal Integrity Findings in a FPGA Layout for an Aerospace Application

Design principles concerning the use of FPGA are of particular importance in aerospace applications since the neglect of such design principles can cause catastrophic effects in aerospace system, as it will be explained in this paper. FPGA design rules such as power conditioning and signal integrity for properly interfacing high speed FPGA with its interface circuits are discussed in this paper as it relates to aerospace systems. Signal integrity to avoid crosstalk within a FPGA has not been a great concern because most of the attention over the years had been on signal integrity at the PCB level. However, this paper shows a real example of crosstalk within a FPGA in an aerospace application.

Perez, Reinaldo J.↗

DOE OSTI2021

Generating clock signals for a cycle accurate, cycle reproducible FPGA based hardware accelerator

A method, system and computer program product are disclosed for generating clock signals for a cycle accurate FPGA based hardware accelerator used to simulate operations of a device-under-test (DUT). In one embodiment, the DUT includes multiple device clocks generating multiple device clock signals at multiple frequencies and at a defined frequency ratio; and the FPG hardware accelerator includes multiple accelerator clocks generating multiple accelerator clock signals to operate the FPGA hardware accelerator to simulate the operations of the DUT. In one embodiment, operations of the DUT are mapped to the FPGA hardware accelerator, and the accelerator clock signals are generated at multiple frequencies and at the defined frequency ratio of the frequencies of the multiple device clocks, to maintain cycle accuracy between the DUT and the FPGA hardware accelerator. In an embodiment, the FPGA hardware accelerator may be used to control the frequencies of the multiple device clocks.

Asaad, Sameh W.↗

DOE OSTI2023

Accelerating Random Forest Classification on GPU and FPGA

Random Forests (RFs) are a commonly used machine learning method for classification and regression tasks spanning a variety of application domains, including bioinformatics, business analytics, and software optimization. While prior work has focused primarily on improving performance of the training of RFs, many applications, such as malware identification, cancer prediction, and banking fraud detection, require fast RF classification. In this work, we accelerate RF classification on GPU and FPGA. In order to provide efficient support for large datasets, we propose a hierarchical memory layout suitable to the GPU/FPGA memory hierarchy. We design three RF classification code variants based on that layout, and we investigate GPU- and FPGA-specific considerations for these kernels. Our experimental evaluation, performed on an Nvidia Xp GPU and on a Xilinx Alveo U250 FPGA accelerator card using publicly available datasets on the scale of millions of samples and tens of features, covers various aspects. First, we evaluate the performance benefits of our hierarchical data structure over the standard compressed sparse row (CSR) format. Second, we compare our GPU implementation with cuML, a machine learning library targeting Nvidia GPUs. Third, we explore the performance/accuracy tradeoff resulting from the use of different tree depths in the RF. Finally, we perform a comparative performance analysis of our GPU and FPGA implementations. Our evaluation shows that for high accuracy targets, our GPU implementation yields 5-9x speedup over CSR, and up to a 2x speedup over cuML.

FPGA, Xilinx FPGA, GPU, Random Forest classificati↗

DOE OSTI2023

Development of ML FPGA Filter for Particle Identification and Tracking in Real Time

Real-time data processing is a frontier field in experimental particle physics. Machine Learning methods are widely used and have proven to be very powerful in particle physics. The growing computational power of modern FPGA boards allows us to add more sophisticated algorithms for real time data processing. Many tasks could be solved using modern Machine Learning (ML) algorithms which are naturally suited for FPGA architectures. The FPGA-based machine learning algorithm provides an extremely low, sub-microsecond, latency decision and makes information-rich data sets for event selection. We report work has started to evaluate an FPGA based Machine Learning (ML) algorithm for a real-time particle identification and tracking with Transition Radiation Detector (TRD) and e/m calorimeter. The first target is the GlueX experiment, with a plan to build a TRD based on GEM technology. GlueX trigger latency is 3.3 μs.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

NASA NTRS2004

A Re-programmable Platform for Dynamic Burn-in Test of Xilinx Virtexll 3000 FPGA for Military and Aerospace Applications

Field Programmable Gate Arrays (FPGA) have played increasingly important roles in military and aerospace applications. Xilinx SRAM-based FPGAs have been extensively used in commercial applications. They have been used less frequently in space flight applications due to their susceptibility to single-event upsets. Reliability of these devices in space applications is a concern that has not been addressed. The objective of this project is to design a fully programmable hardware/software platform that allows (but is not limited to) comprehensive static/dynamic burn-in test of Virtex-II 3000 FPGAs, at speed test and SEU test. Conventional methods test very few discrete AC parameters (primarily switching) of a given integrated circuit. This approach will test any possible configuration of the FPGA and any associated performance parameters. It allows complete or partial re-programming of the FPGA and verification of the program by using read back followed by dynamic test. Designers have full control over which functional elements of the FPGA to stress. They can completely simulate all possible types of configurations/functions. Another benefit of this platform is that it allows collecting information on elevation of the junction temperature as a function of gate utilization, operating frequency and functionality. A software tool has been implemented to demonstrate the various features of the system. The software consists of three major parts: the parallel interface driver, main system procedure and a graphical user interface (GUI).

Field Programmable Gate Arrays (FPGA)↗

NASA NTRS2011

FPGA Implementation of Stereo Disparity with High Throughput for Mobility Applications

High speed stereo vision can allow unmanned robotic systems to navigate safely in unstructured terrain, but the computational cost can exceed the capacity of typical embedded CPUs. In this paper, we describe an end-to-end stereo computation co-processing system optimized for fast throughput that has been implemented on a single Virtex 4 LX160 FPGA. This system is capable of operating on images from a 1024 x 768 3CCD (true RGB) camera pair at 15 Hz. Data enters the FPGA directly from the cameras via Camera Link and is rectified, pre-filtered and converted into a disparity image all within the FPGA, incurring no CPU load. Once complete, a rectified image and the final disparity image are read out over the PCI bus, for a bandwidth cost of 68 MB/sec. Within the FPGA there are 4 distinct algorithms: Camera Link capture, Bilinear rectification, Bilateral subtraction pre-filtering and the Sum of Absolute Difference (SAD) disparity. Each module will be described in brief along with the data flow and control logic for the system. The system has been successfully fielded upon the Carnegie Mellon University's National Robotics Engineering Center (NREC) Crusher system during extensive field trials in 2007 and 2008 and is being implemented for other surface mobility systems at JPL.

Random access memory↗

NASA NTRS2015

New Developments in FPGA: SEUs and Fail-Safe Strategies from the NASA Goddard Perspective

It has been shown that, when exposed to radiation environments, each Field Programmable Gate Array (FPGA) device has unique error signatures. Subsequently, fail-safe and mitigation strategies will differ per FPGA type. In this session several design approaches for safe systems will be presented. It will also explore the benefits and limitations of several mitigation techniques. The intention of the presentation is to provide information regarding FPGA types, their susceptibilities, and proven fail-safe strategies; so that users can select appropriate mitigation and perform the required trade for system insertion. The presentation will describe three types of FPGA devices and their susceptibilities in radiation environments.

hardware description language (HDL)↗

NASA NTRS2016

New Developments in FPGA Devices: SEUs and Fail-Safe Strategies from the NASA Goddard Perspective

It has been shown that, when exposed to radiation environments, each Field Programmable Gate Array (FPGA) device has unique error signatures. Subsequently, fail-safe and mitigation strategies will differ per FPGA type. In this session several design approaches for safe systems will be presented. It will also explore the benefits and limitations of several mitigation techniques. The intention of the presentation is to provide information regarding FPGA types, their susceptibilities, and proven fail-safe strategies; so that users can select appropriate mitigation and perform the required trade for system insertion. The presentation will describe three types of FPGA devices and their susceptibilities in radiation environments.

Field Programmable Gate Array (FPGA)↗

NASA NTRS2016

New Developments in FPGA: SEUs and Fail-Safe Strategies from the NASA Goddard Perspective

It has been shown that, when exposed to radiation environments, each Field Programmable Gate Array (FPGA) device has unique error signatures. Subsequently, fail-safe and mitigation strategies will differ per FPGA type. In this session several design approaches for safe systems will be presented. It will also explore the benefits and limitations of several mitigation techniques. The intention of the presentation is to provide information regarding FPGA types, their susceptibilities, and proven fail-safe strategies; so that users can select appropriate mitigation and perform the required trade for system insertion. The presentation will describe three types of FPGA devices and their susceptibilities in radiation environments.

Error Correction and Detection (EDAC)↗

DOE OSTI2024

Demonstrating the Potential of Adaptive LMS Filtering on FPGA-Based Qubit Control Platforms for Improved Qubit Readout in 2D and 3D Quantum Processing Units

Advancements in quantum computing underscore the critical need for sophisticated qubit readout techniques to accurately discern quantum states. This abstract presents our research intended for optimizing readout pulse fidelity for 2D and 3D Quantum Processing Units (QPUs), the latter coupled with Superconducting Radio Frequency (SRF) cavities. Focusing specifically on the application of the Least Mean Squares (LMS) adaptive filtering algorithm, we explore its integration into the FPGA-based control systems to enhance the accuracy and efficiency of qubit state detection by improving Signal-to-Noise Ratio (SNR). Implementing the LMS algorithm on the Zynq UltraScale+ RFSoC Gen 3 devices (RFSoC 4x2 FPGA and ZCU216 FPGA) using the Quantum Instrumentation Control Kit (QICK) open-source platform, we aim to dynamically test and adjust the filtering parameters in real-time to characterize and adapt to the noise profile presented in quantum computing readout signals. Our preliminary results demonstrate the LMS filter's capability to maintain high readout accuracy while efficiently managing FPGA resources. These findings are expected to contribute to developing more reliable and scalable quantum computing architectures, highlighting the pivotal role of adaptive signal processing in quantum technology advancements.

Johnson, Hans↗

NASA NTRS2008

Testing Microshutter Arrays Using Commercial FPGA Hardware

NASA is developing micro-shutter arrays for the Near Infrared Spectrometer (NIRSpec) instrument on the James Webb Space Telescope (JWST). These micro-shutter arrays allow NIRspec to do Multi Object Spectroscopy, a key part of the mission. Each array consists of 62414 individual 100 x 200 micron shutters. These shutters are magnetically opened and held electrostatically. Individual shutters are then programmatically closed using a simple row/column addressing technique. A common approach to provide these data/clock patterns is to use a Field Programmable Gate Array (FPGA). Such devices require complex VHSIC Hardware Description Language (VHDL) programming and custom electronic hardware. Due to JWST's rapid schedule on the development of the micro-shutters, rapid changes were required to the FPGA code to facilitate new approaches being discovered to optimize the array performance. Such rapid changes simply could not be made using conventional VHDL programming. Subsequently, National Instruments introduced an FPGA product that could be programmed through a Labview interface. Because Labview programming is considerably easier than VHDL programming, this method was adopted and brought success. The software/hardware allowed the rapid change the FPGA code and timely results of new micro-shutter array performance data. As a result, numerous labor hours and money to the project were conserved.

Rapchun, David↗

NASA NTRS2011

FPGA Sequencer for Radar Altimeter Applications

A sequencer for a radar altimeter provides accurate attitude information for a reliable soft landing of the Mars Science Laboratory (MSL). This is a field-programmable- gate-array (FPGA)-only implementation. A table loaded externally into the FPGA controls timing, processing, and decision structures. Radar is memory-less and does not use previous acquisitions to assist in the current acquisition. All cycles complete in exactly 50 milliseconds, regardless of range or whether a target was found. A RAM (random access memory) within the FPGA holds instructions for up to 15 sets. For each set, timing is run, echoes are processed, and a comparison is made. If a target is seen, more detailed processing is run on that set. If no target is seen, the next set is tried. When all sets have been run, the FPGA terminates and waits for the next 50-millisecond event. This setup simplifies testing and improves reliability. A single vertex chip does the work of an entire assembly. Output products require minor processing to become range and velocity. This technology is the heart of the Terminal Descent Sensor, which is an integral part of the Entry Decent and Landing system for MSL. In addition, it is a strong candidate for manned landings on Mars or the Moon.

Berkun, Andrew C.↗

NASA NTRS2013

FPGA Flash Memory High Speed Data Acquisition

The purpose of this research is to design and implement a VHDL ONFI Controller module for a Modular Instrumentation System. The goal of the Modular Instrumentation System will be to have a low power device that will store data and send the data at a low speed to a processor. The benefit of such a system will give an advantage over other purchased binary IP due to the capability of allowing NASA to re-use and modify the memory controller module. To accomplish the performance criteria of a low power system, an in house auxiliary board (Flash/ADC board), FPGA development kit, debug board, and modular instrumentation board will be jointly used for the data acquisition. The Flash/ADC board contains four, 1 MSPS, input channel signals and an Open NAND Flash memory module with an analog to digital converter. The ADC, data bits, and control line signals from the board are sent to an Microsemi/Actel FPGA development kit for VHDL programming of the flash memory WRITE, READ, READ STATUS, ERASE, and RESET operation waveforms using Libero software. The debug board will be used for verification of the analog input signal and be able to communicate via serial interface with the module instrumentation. The scope of the new controller module was to find and develop an ONFI controller with the debug board layout designed and completed for manufacture. Successful flash memory operation waveform test routines were completed, simulated, and tested to work on the FPGA board. Through connection of the Flash/ADC board with the FPGA, it was found that the device specifications were not being meet with Vdd reaching half of its voltage. Further testing showed that it was the manufactured Flash/ADC board that contained a misalignment with the ONFI memory module traces. The errors proved to be too great to fix in the time limit set for the project.

Gonzalez, April↗

NASA NTRS2020

An Embedded Planar-Foil Capacitor Material, FPGA Based Interposer, Aimed at Improving System Performance and Reduced Board Size for Space Based Electronics

This paper presents our work to date in developing, and testing an embedded planar-foil capacitor based interposer intended to be integrated together with high-density components such as Field Programmable Gate Arrays (FPGAs), and Application Specific Integrated Circuit (ASIC) applications. FPGA devices typically have a large number of I/O and power pins. The high speed enabled by these devices requires a large number of discrete bypass capacitors as close as possible to the power pins. These capacitors take up a considerable amount of the board area on the application circuit board. Our interposer replaces these components freeing up space of traditional bypass capacitors for other circuitry. Our Interposer focuses on the needs of Micro Semi’s RTG4 FPGA. We developed the interposer using COTS embedded foil capacitors. The Interposer is customized to the capacitance requirements for each of the FPGA banks. We evaluated three foil manufactures Oak Mitsui, 3M and TDK. The three different designs were evaluated, but we will focus on the Oak-Mitsui based Interposer that we constructed and tested. Through simulations, we validate the horizontal and vertical interconnect inductances, that FPGA decoupling requirements are met. The use of the interposer results in an overall reduction in our Printed Wiring Board (PWB) area.

Hunter, Don J↗

DOE OSTI2024

Demonstrating the Potential of Adaptive LMS Filtering on FPGA-Based Qubit Control Platforms for Improved Qubit Readout in 2D and 3D Quantum Processing Units

Advancements in quantum computing underscore the critical need for sophisticated qubit readout techniques to accurately discern quantum states. This abstract presents our research intended for optimizing readout pulse fidelity for 2D and 3D Quantum Processing Units (QPUs), the latter coupled with Superconducting Radio Frequency (SRF) cavities. Focusing specifically on the application of the Least Mean Squares (LMS) adaptive filtering algorithm, we explore its integration into the FPGA-based control systems to enhance the accuracy and efficiency of qubit state detection by improving Signal-to-Noise Ratio (SNR). Implementing the LMS algorithm on the Zynq UltraScale+ RFSoC Gen 3 devices (RFSoC 4x2 FPGA and ZCU216 FPGA) using the Quantum Instrumentation Control Kit (QICK) open-source platform, we aim to dynamically test and adjust the filtering parameters in real-time to characterize and adapt to the noise profile presented in quantum computing readout signals. Our preliminary results demonstrate the LMS filter's capability to maintain high readout accuracy while efficiently managing FPGA resources. These findings are expected to contribute to developing more reliable and scalable quantum computing architectures, highlighting the pivotal role of adaptive signal processing in quantum technology advancements.

Johnson, Hans↗

DOE OSTI2023

An Analysis of FPGA LUT Bias and Entropy for Physical Unclonable Functions

Process variations within Field Programmable Gate Arrays (FPGAs) provide a rich source of entropy and are therefore well-suited for the implementation of Physical Unclonable Functions (PUFs). However, careful considerations must be given to the design of the PUF architecture as a means of avoiding undesirable localized bias effects that adversely impact randomness, an important statistical quality characteristic of a PUF. Here in this paper, we investigate a ring-oscillator (RO) PUF that leverages localized entropy from individual look-up table (LUT) primitives. A novel RO construction is presented that enables the individual paths through the LUT primitive to be measured and isolated at high precision, and an analysis is presented that demonstrates significant levels of localized design bias. The analysis demonstrates that delay-based PUFs that utilize LUTs as a source of entropy should avoid using FPGA primitives that are localized to specific regions of the FPGA, and instead, a more robust PUF architecture can be constructed by distributing path delay components over a wider region of the FPGA fabric. Compact RO PUF architectures that utilize multiple configurations within a small group of LUTs are particularly susceptible to these types of design-level bias effects. The analysis is carried out on data collected from a set of identically designed, hard macro instantiations of the RO implemented on 30 copies of a Zynq 7010 SoC.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

ESnet/JLab FPGA Accelerated Transport

To increase the science rate for high data rates/volumes, Thomas Jefferson National Accelerator Facility (JLab) has partnered with Energy Sciences Network (ESnet) to define an edge to data center traffic shaping / steering transport capability featuring data event aware network shaping and forwarding. The keystone of this ESnet+JLab FPGA Accelerated Transport (EJFAT) is the joint development of an AI/ML directed dynamic compute work Load Balancer (LB) of UDP streamed data. The LB is a suite consisting of a Field Programmable Gate Array (FPGA) executing the dynamically configurable, low fixed latency LB data plane featuring real-time packet redirection and high throughput, and a control plane running on the FPGA host computer that monitors network and compute farm telemetry in order to make dynamic AI/ML guided decisions for destination compute host redirection/load balancing and destination resource provisioning. The LB provides for three-tier horizontal scaling across LB suites, core compute hosts, and CPUs within a host. The LB effectively provides seamless integration of edge/core computing to support direct experimental data processing for immediate use by JLab science programs and others such as the EIC as well as data centers of the future requiring high throughput and low latency for both hot and cooled data for both running experiment data acquisition systems and data center use cases.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

An FPGA-based hardware accelerator supporting sensitive sequence homology filtering with profile hidden Markov models

Abstract Background Sequence alignment lies at the heart of genome sequence annotation. While the BLAST suite of alignment tools has long held an important role in alignment-based sequence database search, greater sensitivity is achieved through the use of profile hidden Markov models (pHMMs). Here, we describe an FPGA hardware accelerator, called HAVAC, that targets a key bottleneck step (SSV) in the analysis pipeline of the popular pHMM alignment tool, HMMER. Results The HAVAC kernel calculates the SSV matrix at 1739 GCUPS on a $$\sim$$ ∼ $3000 Xilinx Alveo U50 FPGA accelerator card, $$\sim$$ ∼ 227× faster than the optimized SSV implementation in nhmmer . Accounting for PCI-e data transfer data processing, HAVAC is 65× faster than nhmmer’s SSV with one thread and 35× faster than nhmmer with four threads, and uses $$\sim$$ ∼ 31% the energy of a traditional high end Intel CPU. Conclusions HAVAC demonstrates the potential offered by FPGA hardware accelerators to produce dramatic speed gains in sequence annotation and related bioinformatics applications. Because these computations are performed on a co-processor, the host CPU remains free to simultaneously compute other aspects of the analysis pipeline.

59 BASIC BIOLOGICAL SCIENCES↗