Results for “FPGA implementation” — Page 8

NASA NTRSDate not supplied

Parallelized Convolutional Interleaver Implementation for Efficient DDR Memory Access

Convolutional interleavers are used in many different communications systems to correct for burst errors due to atmospheric fades and scintillation. The interleaver size is related to the channel coherence time and the data rate. Small convolutional interleavers can be implemented in a field programmable gate array (FPGA) block random access memory (BRAM). However, large interleavers exceeding the size of the BRAM on the FPGA are necessary for channels with longer fades and higher data rates. Therefore, an implementation utilizing double data rate (DDR) memory external to the FPGA is necessary. Wide DDR memory data buses can make the use of DDR memory for convolutional interleavers inefficient when individual symbols are written to and read from the memory. DDR memory operational speeds can also limit the data rate of the interleaver. The Consultative Committee for Space Data Systems (CCSDS) Optical Communications High Photon Efficiency (HPE) standard utilizes a convolutional channel symbol interleaver. A previous implementation of the HPE standard utilized BRAM for the convolutional interleaver, but mission requirements for the upcoming Optical Artemis-2 Orion (O2O) communications demonstration dictate the use of an interleaver exceeding the size of the BRAM. An algorithm and method for implementing the convolutional interleaver in the FPGA with DDR memory is described in this paper.

optical communications↗

NASA NTRSDate not supplied

Parallelized convolutional interleaver implementation for efficient DDR memory access

Convolutional interleavers are used in many different communications systems to correct for burst errors due to atmospheric fades and scintillation. The interleaver size is related to the channel coherence time and the data rate. Small convolutional interleavers can be implemented in a field programmable gate array (FPGA) block random access memory (BRAM). However, large interleavers exceeding the size of the BRAM on the FPGA are necessary for channels with longer fades and higher data rates. Therefore, an implementation utilizing double data rate (DDR) memory external to the FPGA is necessary. Wide DDR memory data buses can make the use of DDR memory for convolutional interleavers inefficient when individual symbols are written to and read from the memory. DDR memory operational speeds can also limit the data rate of the interleaver. The Consultative Committee for Space Data Systems (CCSDS) Optical Communications High Photon Efficiency (HPE) standard utilizes a convolutional channel symbol interleaver. A previous implementation of the HPE standard utilized BRAM for the convolutional interleaver, but mission requirements for the upcoming Optical Artemis-2 Orion (O2O) communications demonstration dictate the use of an interleaver exceeding the size of the BRAM. An algorithm and method for implementing the convolutional interleaver in the FPGA with DDR memory is described in this paper.

Optical communications↗

NASA NTRS2011

IONAC-Lite

The Interplanetary Overlay Net - working Protocol Accelerator (IONAC) described previously in The Inter - planetary Overlay Networking Protocol Accelerator (NPO-45584), NASA Tech Briefs, Vol. 32, No. 10, (October 2008) p. 106 (http://www.techbriefs.com/component/ content/article/3317) provides functions that implement the Delay Tolerant Networking (DTN) bundle protocol. New missions that require high-speed downlink-only use of DTN can now be accommodated by the unidirectional IONAC-Lite to support high data rate downlink mission applications. Due to constrained energy resources, a conventional software implementation of the DTN protocol can provide only limited throughput for any given reasonable energy consumption rate. The IONAC-Lite DTN Protocol Accelerator is able to reduce this energy consumption by an order of magnitude and increase the throughput capability by two orders of magnitude. In addition, a conventional DTN implementation requires a bundle database with a considerable storage requirement. In very high downlink datarate missions such as near-Earth radar science missions, the storage space utilization needs to be maximized for science data and minimized for communications protocol-related storage needs. The IONAC-Lite DTN Protocol Accelerator is implemented in a reconfigurable hardware device to accomplish exactly what s needed for high-throughput DTN downlink-only scenarios. The following are salient features of the IONAC-Lite implementation: An implementation of the Bundle Protocol for an environment that requires a very high rate bundle egress data rate. The C&DH (command and data handling) subsystem is also expected to be very constrained so the interaction with the C&DH processor and the temporary storage are minimized. Fully pipelined design so that bundle processing database is not required. Implements a lookup table-based approach to eliminate multi-pass processing requirement imposed by the Bundle Protocol header s length field structure and the SDNV (self-delimiting numeric value) data field formatting. 8-bit parallel datapath to support high data-rate missions. Reduced resource utilization implementation for missions that do not require custody transfer features. There was no known implementation of the DTN protocol in a field programmable gate array (FPGA) device prior to the current implementation. The combination of energy and performance optimization that embodies this design makes the work novel.

Torgerson, Jordan L.↗

NASA NTRS2013

An Efficient, Highly Flexible Multi-Channel Digital Downconverter Architecture

In this innovation, a digital downconverter has been created that produces a large (16 or greater) number of output channels of smaller bandwidths. Additionally, this design has the flexibility to tune each channel independently to anywhere in the input bandwidth to cover a wide range of output bandwidths (from 32 MHz down to 1 kHz). Both the flexibility in channel frequency selection and the more than four orders of magnitude range in output bandwidths (decimation rates from 32 to 640,000) presented significant challenges to be solved. The solution involved breaking the digital downconversion process into a two-stage process. The first stage is a 2 oversampled filter bank that divides the whole input bandwidth as a real input signal into seven overlapping, contiguous channels represented with complex samples. Using the symmetry of the sine and cosine functions in a similar way to that of an FFT (fast Fourier transform), this downconversion is very efficient and gives seven channels fixed in frequency. An arbitrary number of smaller bandwidth channels can be formed from second-stage downconverters placed after the first stage of downconversion. Because of the overlapping of the first stage, there is no gap in coverage of the entire input bandwidth. The input to any of the second-stage downconverting channels has a multiplexer that chooses one of the seven wideband channels from the first stage. These second-stage downconverters take up fewer resources because they operate at lower bandwidths than doing the entire downconversion process from the input bandwidth for each independent channel. These second-stage downconverters are each independent with fine frequency control tuning, providing extreme flexibility in positioning the center frequency of a downconverted channel. Finally, these second-stage downconverters have flexible decimation factors over four orders of magnitude The algorithm was developed to run in an FPGA (field programmable gate array) at input data sampling rates of up to 1,280 MHz. The current implementation takes a 1,280-MHz real input, and first breaks it up into seven 160-MHz complex channels, each spaced 80 MHz apart. The eighth channel at baseband was not required for this implementation, and led to more optimization. Afterwards, 16 second stage narrow band channels with independently tunable center frequencies and bandwidth settings are implemented A future implementation in a larger Xilinx FPGA will hold up to 32 independent second-stage channels.

Goodhart, Charles E.↗

NASA NTRS2000

Asynchronous FPGA risks

The worst case timing margin of a synchronous design implemented with a field-programmable gate array (FPGA) is easy to perform using available FPGA design tools. However, it may be difficult to impossible to verify that worst case timing requirements are met for complex asynchronous logic design.

risk FPGA asynchronous↗

NASA NTRS2013

Implementing a Microcontroller Watchdog with a Field-Programmable Gate Array (FPGA)

Reliability is crucial to safety. Redundancy of important system components greatly enhances reliability and hence safety. Field-Programmable Gate Arrays (FPGAs) are useful for monitoring systems and handling the logic necessary to keep them running with minimal interruption when individual components fail. A complete microcontroller watchdog with logic for failure handling can be implemented in a hardware description language (HDL.). HDL-based designs are vendor-independent and can be used on many FPGAs with low overhead.

Straka, Bartholomew↗

DOE OSTI2024

Low duty cycle pulsed UV technique for spectroscopy of aluminum monochloride

We present what we believe to be a novel technique to minimize UV-induced damage in experiments that employ second-harmonic generation cavities. The principle of our approach is to reduce the duty cycle of the UV light as much as possible to prolong the lifetime of the used optics. The low duty cycle is achieved by ramping the cavity into resonance for a short time during the experimental cycle when the light is used and tuning it to an off-resonant state otherwise. The necessary fast ramp and length-stabilization control of the cavity is implemented with the FPGA-based STEMlab platform. We demonstrate the utility of this method by measuring the isotope shift of the electronic transition (X 1 Σ ← A 1 Π) in AlCl at 261.5 nm in a pulsed molecular beam experiment.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Disentangling Beam Losses in The Fermilab Main Injector Enclosure Using Real-Time Edge AI

The Fermilab Main Injector enclosure houses two accelerators, the Main Injector and Recycler Ring. During normal operation, high intensity proton beams exist simultaneously in both. The two accelerators share the same beam loss monitors (BLM) and monitoring system. Deciphering the origin of any of the 260 BLM readings is often difficult. The (Accelerator) Real-time Edge AI for Distributed Systems project, or READS, has developed an AI/ML model, and implemented it on fast FPGA hardware, that disentangles mixed beam losses and attributes probabilities to each BLM as to which machine(s) the loss originated from in real-time. The model inferences are then streamed to the Fermilab accelerator controls network (ACNET) where they are available for operators and experts alike to aid in tuning the machines.

43 PARTICLE ACCELERATORS↗

NASA NTRS1999

A Multichannel Averaging Phasemeter for Picometer Precision Laser Metrology

The Micro-Arcsecond Metrology (MAM) team at the Jet Propulsion Laboratory has developed a precision phasemeter for the Space Interferometry Mission (SIM). The current version of the phasemeter is well-suited for picometer accuracy distance measurements and tracks at speeds up to 50 cm/sec, when coupled to SIM's 1.3 micron wavelength heterodyne laser metrology gauges. Since the phasemeter is implemented with industry standard FPGA chips, other accuracy/speed trade-off points can be programmed for applications such as metrology for earth-based long-baseline astronomical interferometry (planet finding), and industrial applications such as translation stage and machine tool positioning. The phasemeter is a standard VME module, supports 6 metrology gauges, a 128 MHz clock, has programmable hardware averaging, and a maximum range of 232 cycles (2000 meters at 1.3 microns).

Halverson, Peter G.↗

NASA NTRS2008

STRS Compliant FPGA Waveform Development

The Space Telecommunications Radio System (STRS) Architecture Standard describes a standard for NASA space software defined radios (SDRs). It provides a common framework that can be used to develop and operate a space SDR in a reconfigurable and reprogrammable manner. One goal of the STRS Architecture is to promote waveform reuse among multiple software defined radios. Many space domain waveforms are designed to run in the special signal processing (SSP) hardware. However, the STRS Architecture is currently incomplete in defining a standard for designing waveforms in the SSP hardware. Therefore, the STRS Architecture needs to be extended to encompass waveform development in the SSP hardware. The extension of STRS to the SSP hardware will promote easier waveform reconfiguration and reuse. A transmit waveform for space applications was developed to determine ways to extend the STRS Architecture to a field programmable gate array (FPGA). These extensions include a standard hardware abstraction layer for FPGAs and a standard interface between waveform functions running inside a FPGA. A FPGA-based transmit waveform implementation of the proposed standard interfaces on a laboratory breadboard SDR will be discussed.

Nappier, Jennifer↗

NASA NTRS2014

Single Event Analysis and Fault Injection Techniques Targeting Complex Designs Implemented in Xilinx-Virtex Family Field Programmable Gate Array (FPGA) Devices

An informative session regarding SRAM FPGA basics. Presenting a framework for fault injection techniques applied to Xilinx Field Programmable Gate Arrays (FPGAs). Introduce an overlooked time component that illustrates fault injection is impractical for most real designs as a stand-alone characterization tool. Demonstrate procedures that benefit from fault injection error analysis.

Single Event Upset Testing↗

NASA NTRS2016

Reconfigurable, Intelligently-Adaptive, Communication System, an SDR Platform

The Space Telecommunications Radio System (STRS) provides a common, consistent framework to abstract the application software from the radio platform hardware. STRS aims to reduce the cost and risk of using complex, configurable and reprogrammable radio systems across NASA missions. The NASA Glenn Research Center (GRC) team made a software defined radio (SDR) platform STRS compliant by adding an STRS operating environment and a field programmable gate array (FPGA) wrapper, capable of implementing each of the platforms interfaces, as well as a test waveform to exercise those interfaces. This effort serves to provide a framework toward waveform development onto an STRS compliant platform to support future space communication systems for advanced exploration missions. The use of validated STRS compliant applications provides tested code with extensive documentation to potentially reduce risk, cost and e ort in development of space-deployable SDRs. This paper discusses the advantages of STRS, the integration of STRS onto a Reconfigurable, Intelligently-Adaptive, Communication System (RIACS) SDR platform, and the test waveform and wrapper development e orts. The paper emphasizes the infusion of the STRS Architecture onto the RIACS platform for potential use in next generation flight system SDRs for advanced exploration missions.

space communications↗

NASA NTRS2016

Reconfigurable, Intelligently-Adaptive, Communication System, an SDR Platform

The Space Telecommunications Radio System (STRS) provides a common, consistent framework to abstract the application software from the radio platform hardware. STRS aims to reduce the cost and risk of using complex, configurable and reprogrammable radio systems across NASA missions. The Glenn Research Center (GRC) team made a software-defined radio (SDR) platform STRS compliant by adding an STRS operating environment and a field programmable gate array (FPGA) wrapper, capable of implementing each of the platforms interfaces, as well as a test waveform to exercise those interfaces. This effort serves to provide a framework toward waveform development on an STRS compliant platform to support future space communication systems for advanced exploration missions. Validated STRS compliant applications provided tested code with extensive documentation to potentially reduce risk, cost and efforts in development of space-deployable SDRs. This paper discusses the advantages of STRS, the integration of STRS onto a Reconfigurable, Intelligently-Adaptive, Communication System (RIACS) SDR platform, the sample waveform, and wrapper development efforts. The paper emphasizes the infusion of the STRS Architecture onto the RIACS platform for potential use in next generation SDRs for advance exploration missions.

space communications↗

NASA NTRS2009

Digital Beamforming Scatterometer

This paper discusses scatterometer measurements collected with multi-mode Digital Beamforming Synthetic Aperture Radar (DBSAR) during the SMAP-VEX 2008 campaign. The 2008 SMAP Validation Experiment was conducted to address a number of specific questions related to the soil moisture retrieval algorithms. SMAP-VEX 2008 consisted on a series of aircraft-based.flights conducted on the Eastern Shore of Maryland and Delaware in the fall of 2008. Several other instruments participated in the campaign including the Passive Active L-Band System (PALS), the Marshall Airborne Polarimetric Imaging Radiometer (MAPIR), and the Global Positioning System Reflectometer (GPSR). This campaign was the first SMAP Validation Experiment. DBSAR is a multimode radar system developed at NASA/Goddard Space Flight Center that combines state-of-the-art radar technologies, on-board processing, and advances in signal processing techniques in order to enable new remote sensing capabilities applicable to Earth science and planetary applications [l]. The instrument can be configured to operate in scatterometer, Synthetic Aperture Radar (SAR), or altimeter mode. The system builds upon the L-band Imaging Scatterometer (LIS) developed as part of the RadSTAR program. The radar is a phased array system designed to fly on the NASA P3 aircraft. The instrument consists of a programmable waveform generator, eight transmit/receive (T/R) channels, a microstrip antenna, and a reconfigurable data acquisition and processor system. Each transmit channel incorporates a digital attenuator, and digital phase shifter that enables amplitude and phase modulation on transmit. The attenuators, phase shifters, and calibration switches are digitally controlled by the radar control card (RCC) on a pulse by pulse basis. The antenna is a corporate fed microstrip patch-array centered at 1.26 GHz with a 20 MHz bandwidth. Although only one feed is used with the present configuration, a provision was made for separate corporate feeds for vertical and horizontal polarization. System upgrades to dual polarization are currently under way. The DBSAR processor is a reconfigurable data acquisition and processor system capable of real-time, high-speed data processing. DBSAR uses an FPGA-based architecture to implement digitally down-conversion, in-phase and quadrature (I/Q) demodulation, and subsequent radar specific algorithms. The core of the processor board consists of an analog-to-digital (AID) section, three Altera Stratix field programmable gate arrays (FPGAs), an ARM microcontroller, several memory devices, and an Ethernet interface. The processor also interfaces with a navigation board consisting of a GPS and a MEMS gyro. The processor has been configured to operate in scatterometer, Synthetic Aperture Radar (SAR), and altimeter modes. All the modes are based on digital beamforming which is a digital process that generates the far-field beam patterns at various scan angles from voltages sampled in the antenna array. This technique allows steering the received beam and controlling its beam-width and side-lobe. Several beamforming techniques can be implemented each characterized by unique strengths and weaknesses, and each applicable to different measurement scenarios. In Scatterometer mode, the radar is capable to.generate a wide beam or scan a narrow beam on transmit, and to steer the received beam on processing while controlling its beamwidth and side-lobe level. Table I lists some important radar characteristics

Rincon, Rafael F.↗

NASA NTRSDate not supplied

A System to Provide Deterministic Flight Software Operation and Maximize Multicore Processing Performance: The Safe and Precise Landing – Integrated Capabilities Evolution (SPLICE) Datapath

A method and design are described for a system that processes multiple data streams, utilizing a multicore asymmetric processing architecture, that eliminates data interrupts to the application processors. The design supports a deterministic environment for flight software in NASA’s Safe and Precise Landing – Integrated Capabilities Evolution (SPLICE) project. The SPLICE project develops sensor, algorithm, and compute technologies for Precision Landing and Hazard Avoidance (PL&HA) capabilities. The compute technology for SPLICE is the Descent and Landing Computer (DLC). The DLC hosts several SPLICE algorithms with high computational resource requirements that must be executed in a real-time and deterministic manner. The software runs on a custom Single Board Computer (SBC), with a Xilinx Ultrascale+ Multiprocessor System-on-a-Chip (MPSoC). Input data for the flight software is from a variety of sensors, unique with respect to data rate and packet size. A data path between the SPLICE sensors and algorithms is designed to efficiently deliver this data to the flight software using the MPSoC asymmetric processing cores and Field Programmable Gate Array (FPGA) fabric. This is implemented in a manner that isolates the application processors running the flight software from interrupts associated with the input data. By leveraging real-time processors on the MPSoC, and a structure with the appropriate interfaces in the shared memory on the SBC, the flight software can use the full set of application processors. The available utilization for each processor in this set is also maximized for the SPLICE applications, providing a sufficiently deterministic execution environment without the cost and overhead of a real-time operating system.

heterogeneous processing system↗

NASA NTRS2023

A System to Provide Deterministic Flight Software Operation and Maximize Multicore Processing Performance: The Safe and Precise Landing – Integrated Capabilities Evolution (SPLICE) Datapath

A method and design are described for a system that processes multiple data streams, utilizing a multicore asymmetric processing architecture, that eliminates data interrupts to the application processors. The design supports a deterministic environment for flight software in NASA’s Safe and Precise Landing – Integrated Capabilities Evolution (SPLICE) project. The SPLICE project develops sensor, algorithm, and compute technologies for Precision Landing and Hazard Avoidance (PL&HA) capabilities. The compute technology for SPLICE is the Descent and Landing Computer (DLC). The DLC hosts several SPLICE algorithms with high computational resource requirements that must be executed in a real-time and deterministic manner. The software runs on a custom Single Board Computer (SBC), with a Xilinx Ultrascale+ Multiprocessor System-on-a-Chip (MPSoC). Input data for the flight software is from a variety of sensors, unique with respect to data rate and packet size. A data path between the SPLICE sensors and algorithms is designed to efficiently deliver this data to the flight software using the MPSoC asymmetric processing cores and Field Programmable Gate Array (FPGA) fabric. This is implemented in a manner that isolates the application processors running the flight software from interrupts associated with the input data. By leveraging real-time processors on the MPSoC, and a structure with the appropriate interfaces in the shared memory on the SBC, the flight software can use the full set of application processors. The available utilization for each processor in this set is also maximized for the SPLICE applications, providing a sufficiently deterministic execution environment without the cost and overhead of a real-time operating system.

David K. Rutishauser↗

DOE OSTI2024

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↗

DOE OSTI2024

FiberFlex: Real-time FPGA-based Intelligent and Distributed Fiber Sensor System for Pedestrian Recognition

In recent years, security monitoring of public places and critical infrastructure has heavily relied on the widespread use of cameras, raising concerns about personal privacy violations. To balance the need for effective security monitoring with the protection of personal privacy, we explore the potential of optical fiber sensors for this application. This article proposes FiberFlex, an intelligent and distributed fiber sensor system. Ultizing Field Programmable Gate Arrays (FPGA) high-level synthesis (HLS) acceleration, FiberFlex offers real-time pedestrian detection by co-designing the entire pipeline of optical signal acquisition, processing, and recognition networks based on the principles of optical fiber sensing. As a promising alternative to traditional camera-based monitoring systems, FiberFlex achieves pedestrian detection by analyzing the vibration patterns caused by pedestrian footsteps, enabling security monitoring while preserving individual privacy. FiberFlex comprises three modules: First , fiber-optic sensing system: A fiber-optic distributed acoustic sensing (DAS) system is built and used to measure the ground vibration waves generated by people walking. Second , algorithms: We first collect the training data by measuring the ground vibration waves, label the data, and use the data to train the neural network models to perform pedestrian recognition. Third , hardware accelerators: We use HLS tools to design hardware modules on FPGA for data collection and pre-processing and integrate them with the downstream neural network accelerators to perform in-line real-time pedestrian detection. The final detection results are sent back from FPGA to the host CPU. We implement our system FiberFlex with the in-house built DAS system and AMD/Xilinx Kintex7 FPGA KC705 board and verify the whole system using the real-world collected data. We conduct recognition tests on five test subjects of varying ages, heights, and weights in a fixed sensing area. Each subject experienced 20 real-time recognition tests using their daily walking habits, and the subjects were given adequate rest between tests. After 100 tests on five test subjects, the overall real-time recognition accuracy exceeded \(88.0\%\) . The whole system uses 55 W of power, 33 W in the optical DAS system and 22 W in the FPGA. Relying on its end-to-end interdisciplinary design, FiberFlex seamlessly combines fiber-optic sensors with FPGA accelerators to enable low-power real-time security monitoring without compromising privacy, making it a valuable addition to the existing security monitoring network. According to FiberFlex, more valuable research can be conducted in the future, such as fall monitoring for the elderly, migration of identification networks between different application scenarios, and improvement of anti-interference performance in more complex environments. In future perception networks, where the “eyes” are not feasible, let’s use fiber optic touch instead.

Distributed↗