Search NASA⌕ Search

SEARCH · Search NASA

Results for “field-programmable gate array (FPGA)”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
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 NTRS2011

High-Throughput, Adaptive FFT Architecture for FPGA-Based Spaceborne Data Processors

Exponential growth in microelectronics technology such as field-programmable gate arrays (FPGAs) has enabled high-performance spaceborne instruments with increasing onboard data processing capabilities. As a commonly used digital signal processing (DSP) building block, fast Fourier transform (FFT) has been of great interest in onboard data processing applications, which needs to strike a reasonable balance between high-performance (throughput, block size, etc.) and low resource usage (power, silicon footprint, etc.). It is also desirable to be designed so that a single design can be reused and adapted into instruments with different requirements. The Multi-Pass Wide Kernel FFT (MPWK-FFT) architecture was developed, in which the high-throughput benefits of the parallel FFT structure and the low resource usage of Singleton s single butterfly method is exploited. The result is a wide-kernel, multipass, adaptive FFT architecture. The 32K-point MPWK-FFT architecture includes 32 radix-2 butterflies, 64 FIFOs to store the real inputs, 64 FIFOs to store the imaginary inputs, complex twiddle factor storage, and FIFO logic to route the outputs to the correct FIFO. The inputs are stored in sequential fashion into the FIFOs, and the outputs of each butterfly are sequentially written first into the even FIFO, then the odd FIFO. Because of the order of the outputs written into the FIFOs, the depth of the even FIFOs, which are 768 each, are 1.5 times larger than the odd FIFOs, which are 512 each. The total memory needed for data storage, assuming that each sample is 36 bits, is 2.95 Mbits. The twiddle factors are stored in internal ROM inside the FPGA for fast access time. The total memory size to store the twiddle factors is 589.9Kbits. This FFT structure combines the benefits of high throughput from the parallel FFT kernels and low resource usage from the multi-pass FFT kernels with desired adaptability. Space instrument missions that need onboard FFT capabilities such as the proposed DESDynl, SWOT (Surface Water Ocean Topography), and Europa sounding radar missions would greatly benefit from this technology with significant reductions in non-recurring cost and risk.

NguyenKobayashi, Kayla↗
NASA NTRS2004

FPGA-Based, Self-Checking, Fault-Tolerant Computers

A proposed computer architecture would exploit the capabilities of commercially available field-programmable gate arrays (FPGAs) to enable computers to detect and recover from bit errors. The main purpose of the proposed architecture is to enable fault-tolerant computing in the presence of single-event upsets (SEUs). [An SEU is a spurious bit flip (also called a soft error) caused by a single impact of ionizing radiation.] The architecture would also enable recovery from some soft errors caused by electrical transients and, to some extent, from intermittent and permanent (hard) errors caused by aging of electronic components. A typical FPGA of the current generation contains one or more complete processor cores, memories, and highspeed serial input/output (I/O) channels, making it possible to shrink a board-level processor node to a single integrated-circuit chip. Custom, highly efficient microcontrollers, general-purpose computers, custom I/O processors, and signal processors can be rapidly and efficiently implemented by use of FPGAs. Unfortunately, FPGAs are susceptible to SEUs. Prior efforts to mitigate the effects of SEUs have yielded solutions that degrade performance of the system and require support from external hardware and software. In comparison with other fault-tolerant- computing architectures (e.g., triple modular redundancy), the proposed architecture could be implemented with less circuitry and lower power demand. Moreover, the fault-tolerant computing functions would require only minimal support from circuitry outside the central processing units (CPUs) of computers, would not require any software support, and would be largely transparent to software and to other computer hardware. There would be two types of modules: a self-checking processor module and a memory system (see figure). The self-checking processor module would be implemented on a single FPGA and would be capable of detecting its own internal errors. It would contain two CPUs executing identical programs in lock step, with comparison of their outputs to detect errors. It would also contain various cache local memory circuits, communication circuits, and configurable special-purpose processors that would use self-checking checkers. (The basic principle of the self-checking checker method is to utilize logic circuitry that generates error signals whenever there is an error in either the checker or the circuit being checked.) The memory system would comprise a main memory and a hardware-controlled check-pointing system (CPS) based on a buffer memory denoted the recovery cache. The main memory would contain random-access memory (RAM) chips and FPGAs that would, in addition to everything else, implement double-error-detecting and single-error-correcting memory functions to enable recovery from single-bit errors.

Some, Raphael↗
NASA NTRS2009

Efficient Multiplexer FPGA Block Structures Based on G4FETs

Generic structures have been conceived for multiplexer blocks to be implemented in field-programmable gate arrays (FPGAs) based on four-gate field-effect transistors (G(sup 4)FETs). This concept is a contribution to the continuing development of digital logic circuits based on G4FETs and serves as a further demonstration that logic circuits based on G(sup 4)FETs could be more efficient (in the sense that they could contain fewer transistors), relative to functionally equivalent logic circuits based on conventional transistors. Results in this line of development at earlier stages were summarized in two previous NASA Tech Briefs articles: "G(sup 4)FETs as Universal and Programmable Logic Gates" (NPO-41698), Vol. 31, No. 7 (July 2007), page 44, and "Efficient G4FET-Based Logic Circuits" (NPO-44407), Vol. 32, No. 1 ( January 2008), page 38 . As described in the first-mentioned previous article, a G4FET can be made to function as a three-input NOT-majority gate, which has been shown to be a universal and programmable logic gate. The universality and programmability could be exploited to design logic circuits containing fewer components than are required for conventional transistor-based circuits performing the same logic functions. The second-mentioned previous article reported results of a comparative study of NOT-majority-gate (G(sup 4)FET)-based logic-circuit designs and equivalent NOR- and NAND-gate-based designs utilizing conventional transistors. [NOT gates (inverters) were also included, as needed, in both the G(sup 4)FET- and the NOR- and NAND-based designs.] In most of the cases studied, fewer logic gates (and, hence, fewer transistors), were required in the G(sup 4)FET-based designs. There are two popular categories of FPGA block structures or architectures: one based on multiplexers, the other based on lookup tables. In standard multiplexer- based architectures, the basic building block is a tree-like configuration of multiplexers, with possibly a few additional logic gates such as ANDs or ORs. Interconnections are realized by means of programmable switches that may connect the input terminals of a block to output terminals of other blocks, may bridge together some of the inputs, or may connect some of the input terminals to signal sources representing constant logical levels 0 or 1. The left part of the figure depicts a four-to-one G(sup 4)FET-based multiplexer tree; the right part of the figure depicts a functionally equivalent four-to-one multiplexer based on conventional transistors. The G(sup 4)FET version would contains 54 transistors; the conventional version contains 70 transistors.

Vatan, Farrokh↗
NASA NTRS2010

A High-Throughput, Adaptive FFT Architecture for FPGA-Based Space-Borne Data Processors

Historically, computationally-intensive data processing for space-borne instruments has heavily relied on ground-based computing resources. But with recent advances in functional densities of Field-Programmable Gate-Arrays (FPGAs), there has been an increasing desire to shift more processing on-board; therefore relaxing the downlink data bandwidth requirements. Fast Fourier Transforms (FFTs) are commonly used building blocks for data processing applications, with a growing need to increase the FFT block size. Many existing FFT architectures have mainly emphasized on low power consumption or resource usage; but as the block size of the FFT grows, the throughput is often compromised first. In addition to power and resource constraints, space-borne digital systems are also limited to a small set of space-qualified memory elements, which typically lag behind the commercially available counterparts in capacity and bandwidth. The bandwidth limitation of the external memory creates a bottleneck for a large, high-throughput FFT design with large block size. In this paper, we present the Multi-Pass Wide Kernel FFT (MPWK-FFT) architecture for a moderately large block size (32K) with considerations to power consumption and resource usage, as well as throughput. We will also show that the architecture can be easily adapted for different FFT block sizes with different throughput and power requirements. The result is completely contained within an FPGA without relying on external memories. Implementation results are summarized.

Nguyen, Kayla↗
NASA NTRS2011

Fault-Tolerant, Radiation-Hard DSP

Commercial digital signal processors (DSPs) for use in high-speed satellite computers are challenged by the damaging effects of space radiation, mainly single event upsets (SEUs) and single event functional interrupts (SEFIs). Innovations have been developed for mitigating the effects of SEUs and SEFIs, enabling the use of very-highspeed commercial DSPs with improved SEU tolerances. Time-triple modular redundancy (TTMR) is a method of applying traditional triple modular redundancy on a single processor, exploiting the VLIW (very long instruction word) class of parallel processors. TTMR improves SEU rates substantially. SEFIs are solved by a SEFI-hardened core circuit, external to the microprocessor. It monitors the health of the processor, and if a SEFI occurs, forces the processor to return to performance through a series of escalating events. TTMR and hardened-core solutions were developed for both DSPs and reconfigurable field-programmable gate arrays (FPGAs). This includes advancement of TTMR algorithms for DSPs and reconfigurable FPGAs, plus a rad-hard, hardened-core integrated circuit that services both the DSP and FPGA. Additionally, a combined DSP and FPGA board architecture was fully developed into a rad-hard engineering product. This technology enables use of commercial off-the-shelf (COTS) DSPs in computers for satellite and other space applications, allowing rapid deployment at a much lower cost. Traditional rad-hard space computers are very expensive and typically have long lead times. These computers are either based on traditional rad-hard processors, which have extremely low computational performance, or triple modular redundant (TMR) FPGA arrays, which suffer from power and complexity issues. Even more frustrating is that the TMR arrays of FPGAs require a fixed, external rad-hard voting element, thereby causing them to lose much of their reconfiguration capability and in some cases significant speed reduction. The benefits of COTS high-performance signal processing include significant increase in onboard science data processing, enabling orders of magnitude reduction in required communication bandwidth for science data return, orders of magnitude improvement in onboard mission planning and critical decision making, and the ability to rapidly respond to changing mission environments, thus enabling opportunistic science and orders of magnitude reduction in the cost of mission operations through reduction of required staff. Additional benefits of COTS-based, high-performance signal processing include the ability to leverage considerable commercial and academic investments in advanced computing tools, techniques, and infra structure, and the familiarity of the science and IT community with these computing environments.

Czajkowski, David↗
DOE OSTI2025

End-to-End Workflow for Machine-Learning-Based Qubit Readout With QICK and hls4ml

In this article, we present an end-to-end workflow for superconducting qubit readout that embeds codesigned neural networks into the quantum instrumentation control kit (QICK). Capitalizing on the custom firmware and software of the QICK platform, which is built on Xilinx radiofrequency system-on-chip field-programmable gate arrays (FPGAs), we aim to leverage machine learning (ML) to address critical challenges in qubit readout accuracy and scalability. The workflow utilizes the hls4ml package and employs quantization-aware training to translate ML models into hardware-efficient FPGA implementations via user-friendly Python application programming interfaces. We experimentally demonstrate the design, optimization, and integration of an ML algorithm for single transmon qubit readout, achieving 96% single-shot fidelity with a latency of 32.25 ns and less than 16% FPGA lookup table resource utilization. Our results offer the community an accessible workflow to advance ML-driven readout and adaptive control in quantum information processing applications.

42 ENGINEERING↗
NASA NTRS2004

Digital Radar-Signal Processors Implemented in FPGAs

High-performance digital electronic circuits for onboard processing of return signals in an airborne precipitation- measuring radar system have been implemented in commercially available field-programmable gate arrays (FPGAs). Previously, it was standard practice to downlink the radar-return data to a ground station for postprocessing a costly practice that prevents the nearly-real-time use of the data for automated targeting. In principle, the onboard processing could be performed by a system of about 20 personal- computer-type microprocessors; relative to such a system, the present FPGA-based processor is much smaller and consumes much less power. Alternatively, the onboard processing could be performed by an application-specific integrated circuit (ASIC), but in comparison with an ASIC implementation, the present FPGA implementation offers the advantages of (1) greater flexibility for research applications like the present one and (2) lower cost in the small production volumes typical of research applications. The generation and processing of signals in the airborne precipitation measuring radar system in question involves the following especially notable steps: The system utilizes a total of four channels two carrier frequencies and two polarizations at each frequency. The system uses pulse compression: that is, the transmitted pulse is spread out in time and the received echo of the pulse is processed with a matched filter to despread it. The return signal is band-limited and digitally demodulated to a complex baseband signal that, for each pulse, comprises a large number of samples. Each complex pair of samples (denoted a range gate in radar terminology) is associated with a numerical index that corresponds to a specific time offset from the beginning of the radar pulse, so that each such pair represents the energy reflected from a specific range. This energy and the average echo power are computed. The phase of each range bin is compared to the previous echo by complex conjugate multiplication to obtain the mean Doppler shift (and hence the mean and variance of the velocity of precipitation) of the echo at that range.

Berkun, Andrew↗
NASA NTRS2008

Spaceborne Hybrid-FPGA System for Processing FTIR Data

Progress has been made in a continuing effort to develop a spaceborne computer system for processing readout data from a Fourier-transform infrared (FTIR) spectrometer to reduce the volume of data transmitted to Earth. The approach followed in this effort, oriented toward reducing design time and reducing the size and weight of the spectrometer electronics, has been to exploit the versatility of recently developed hybrid field-programmable gate arrays (FPGAs) to run diverse software on embedded processors while also taking advantage of the reconfigurable hardware resources of the FPGAs.

Bekker, Dmitriy↗
NASA NTRS2007

Advanced High-Definition Video Cameras

A product line of high-definition color video cameras, now under development, offers a superior combination of desirable characteristics, including high frame rates, high resolutions, low power consumption, and compactness. Several of the cameras feature a 3,840 2,160-pixel format with progressive scanning at 30 frames per second. The power consumption of one of these cameras is about 25 W. The size of the camera, excluding the lens assembly, is 2 by 5 by 7 in. (about 5.1 by 12.7 by 17.8 cm). The aforementioned desirable characteristics are attained at relatively low cost, largely by utilizing digital processing in advanced field-programmable gate arrays (FPGAs) to perform all of the many functions (for example, color balance and contrast adjustments) of a professional color video camera. The processing is programmed in VHDL so that application-specific integrated circuits (ASICs) can be fabricated directly from the program. ["VHDL" signifies VHSIC Hardware Description Language C, a computing language used by the United States Department of Defense for describing, designing, and simulating very-high-speed integrated circuits (VHSICs).] The image-sensor and FPGA clock frequencies in these cameras have generally been much higher than those used in video cameras designed and manufactured elsewhere. Frequently, the outputs of these cameras are converted to other video-camera formats by use of pre- and post-filters.

Glenn, William↗
NASA NTRS2006

Three-Function Logic Gate Controlled by Analog Voltage

The figure is a schematic diagram of a complementary metal oxide/semiconductor (CMOS) electronic circuit that performs one of three different logic functions, depending on the level of an externally applied control voltage, V(sub sel). Specifically, the circuit acts as A NAND gate at V(sub sel) = 0.0 V, A wire (the output equals one of the inputs) at V(sub sel) = 1.0 V, or An AND gate at V(sub sel) = -1.8 V. [The nominal power-supply potential (VDD) and logic "1" potential of this circuit is 1.8 V.] Like other multifunctional circuits described in several prior NASA Tech Briefs articles, this circuit was synthesized following an automated evolutionary approach that is so named because it is modeled partly after the repetitive trial-and-error process of biological evolution. An evolved circuit can be tested by computational simulation and/or tested in real hardware, and the results of the test can provide guidance for refining the design through further iteration. The evolutionary synthesis of electronic circuits can now be implemented by means of a software package Genetic Algorithms for Circuit Synthesis (GACS) that was developed specifically for this purpose. GACS was used to synthesize the present trifunctional circuit. As in the cases of other multifunctional circuits described in several prior NASA Tech Briefs articles, the multiple functionality of this circuit, the use of a single control voltage to select the function, and the automated evolutionary approach to synthesis all contribute synergistically to a combination of features that are potentially advantageous for the further development of robust, multiple-function logic circuits, including, especially, field-programmable gate arrays (FPGAs). These advantages include the following: This circuit contains only 9 transistors about half the number of transistors that would be needed to obtain equivalent NAND/wire/AND functionality by use of components from a standard digital design library. If multifunctional gates like this circuit were used in the place of the configurable logic blocks of present commercial FPGAs, it would be possible to change the functions of the resulting digital systems within shorter times. For example, by changing a single control voltage, one could change the function of thousands of FPGA cells within nanoseconds. In contrast, typically, the reconfiguration in a conventional FPGA by use of bits downloaded from look-up tables via a digital bus takes microseconds.

Zebulum, Ricardo↗
NASA NTRS2008

Replication of Space-Shuttle Computers in FPGAs and ASICs

A document discusses the replication of the functionality of the onboard space-shuttle general-purpose computers (GPCs) in field-programmable gate arrays (FPGAs) and application-specific integrated circuits (ASICs). The purpose of the replication effort is to enable utilization of proven space-shuttle flight software and software-development facilities to the extent possible during development of software for flight computers for a new generation of launch vehicles derived from the space shuttles. The replication involves specifying the instruction set of the central processing unit and the input/output processor (IOP) of the space-shuttle GPC in a hardware description language (HDL). The HDL is synthesized to form a "core" processor in an FPGA or, less preferably, in an ASIC. The core processor can be used to create a flight-control card to be inserted into a new avionics computer. The IOP of the GPC as implemented in the core processor could be designed to support data-bus protocols other than that of a multiplexer interface adapter (MIA) used in the space shuttle. Hence, a computer containing the core processor could be tailored to communicate via the space-shuttle GPC bus and/or one or more other buses.

Ferguson, Roscoe C.↗
NASA NTRS2001

Adaptive Instrument Module: Space Instrument Controller "Brain" through Programmable Logic Devices

The Adaptive Instrument Module (AIM) will be the first true demonstration of reconfigurable computing with field-programmable gate arrays (FPGAs) in space, enabling the 'brain' of the system to evolve or adapt to changing requirements. In partnership with NASA Goddard Space Flight Center and the Australian Cooperative Research Centre for Satellite Systems (CRC-SS), APL has built the flight version to be flown on the Australian university-class satellite FEDSAT. The AIM provides satellites the flexibility to adapt to changing mission requirements by reconfiguring standardized processing hardware rather than incurring the large costs associated with new builds. This ability to reconfigure the processing in response to changing mission needs leads to true evolveable computing, wherein the instrument 'brain' can learn from new science data in order to perform state-of-the-art data processing. The development of the AIM is significant in its enormous potential to reduce total life-cycle costs for future space exploration missions. The advent of RAM-based FPGAs whose configuration can be changed at any time has enabled the development of the AIM for processing tasks that could not be performed in software. The use of the AIM enables reconfiguration of the FPGA circuitry while the spacecraft is in flight, with many accompanying advantages. The AIM demonstrates the practicalities of using reconfigurable computing hardware devices by conducting a series of designed experiments. These include the demonstration of implementing data compression, data filtering, and communication message processing and inter-experiment data computation. The second generation is the Adaptive Processing Template (ADAPT) which is further described in this paper. The next step forward is to make the hardware itself adaptable and the ADAPT pursues this challenge by developing a reconfigurable module that will be capable of functioning efficiently in various applications. ADAPT will take advantage of radiation tolerant RAM-based field programmable gate array (FPGA) technology to develop a reconfigurable processor that combines the flexibility of a general purpose processor running software with the performance of application specific processing hardware for a variety of high performance computing applications.

Darrin, Ann Garrison↗
NASA NTRS2010

Reconfigurable Hardware for Compressing Hyperspectral Image Data

High-speed, low-power, reconfigurable electronic hardware has been developed to implement ICER-3D, an algorithm for compressing hyperspectral-image data. The algorithm and parts thereof have been the topics of several NASA Tech Briefs articles, including Context Modeler for Wavelet Compression of Hyperspectral Images (NPO-43239) and ICER-3D Hyperspectral Image Compression Software (NPO-43238), which appear elsewhere in this issue of NASA Tech Briefs. As described in more detail in those articles, the algorithm includes three main subalgorithms: one for computing wavelet transforms, one for context modeling, and one for entropy encoding. For the purpose of designing the hardware, these subalgorithms are treated as modules to be implemented efficiently in field-programmable gate arrays (FPGAs). The design takes advantage of industry- standard, commercially available FPGAs. The implementation targets the Xilinx Virtex II pro architecture, which has embedded PowerPC processor cores with flexible on-chip bus architecture. It incorporates an efficient parallel and pipelined architecture to compress the three-dimensional image data. The design provides for internal buffering to minimize intensive input/output operations while making efficient use of offchip memory. The design is scalable in that the subalgorithms are implemented as independent hardware modules that can be combined in parallel to increase throughput. The on-chip processor manages the overall operation of the compression system, including execution of the top-level control functions as well as scheduling, initiating, and monitoring processes. The design prototype has been demonstrated to be capable of compressing hyperspectral data at a rate of 4.5 megasamples per second at a conservative clock frequency of 50 MHz, with a potential for substantially greater throughput at a higher clock frequency. The power consumption of the prototype is less than 6.5 W. The reconfigurability (by means of reprogramming) of the FPGAs makes it possible to effectively alter the design to some extent to satisfy different requirements without adding hardware. The implementation could be easily propagated to future FPGA generations and/or to custom application-specific integrated circuits.

Aranki, Nazeeh↗
DOE OSTI2025

Real-Time Artificial Intelligence for Particle Reconstruction and Higgs Physics

With the discovery of the Higgs boson at the CERN LHC, the world's highest-energy particle accelerator complex, scientists have acquired an important tool to study the fundamental building blocks of the universe. Precision measurements of Higgs bosons produced with large momentum allow for unique insights into the structure of the interactions of the Higgs boson with other particles that may shed light on physics beyond the standard model. While experimentally challenging, exploring such interactions with novel artificial intelligence (AI) methods can advance our understanding of the Higgs sector, including the Higgs boson's self-interaction. Moreover, the LHC is undergoing a major upgrade to further increase its particle collision rate and thereby operate for an additional decade. The experimental detectors at the upgraded facility must process at least a factor of ten more data at rates of hundreds of terabytes per second all under challenging conditions. New AI techniques are required to reconstruct and select, or trigger on, the most physics-sensitive events in real-time to handle the resulting avalanche of data. The proposed research will achieve the goals of the LHC program at the CMS experiment by developing a sub-microsecond event reconstruction system using real-time AI algorithms that employ field-programmable gate array technologies. By harnessing sophisticated AI techniques, this research focuses on measuring the production of Higgs bosons at large momentum while enhancing particle reconstruction methods in the trigger and beyond. Overall, the proposed research has broader implications for the use of AI in resource-constrained, low-latency embedded applications across all fields of science.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗