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At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRS2011

CoNNeCT Baseband Processor Module

A document describes the CoNNeCT Baseband Processor Module (BPM) based on an updated processor, memory technology, and field-programmable gate arrays (FPGAs). The BPM was developed from a requirement to provide sufficient computing power and memory storage to conduct experiments for a Software Defined Radio (SDR) to be implemented. The flight SDR uses the AT697 SPARC processor with on-chip data and instruction cache. The non-volatile memory has been increased from a 20-Mbit EEPROM (electrically erasable programmable read only memory) to a 4-Gbit Flash, managed by the RTAX2000 Housekeeper, allowing more programs and FPGA bit-files to be stored. The volatile memory has been increased from a 20-Mbit SRAM (static random access memory) to a 1.25-Gbit SDRAM (synchronous dynamic random access memory), providing additional memory space for more complex operating systems and programs to be executed on the SPARC. All memory is EDAC (error detection and correction) protected, while the SPARC processor implements fault protection via TMR (triple modular redundancy) architecture. Further capability over prior BPM designs includes the addition of a second FPGA to implement features beyond the resources of a single FPGA. Both FPGAs are implemented with Xilinx Virtex-II and are interconnected by a 96-bit bus to facilitate data exchange. Dedicated 1.25- Gbit SDRAMs are wired to each Xilinx FPGA to accommodate high rate data buffering for SDR applications as well as independent SpaceWire interfaces. The RTAX2000 manages scrub and configuration of each Xilinx.

Yamamoto, Clifford K↗
NASA NTRS2012

Hardware Implementation of Lossless Adaptive Compression of Data From a Hyperspectral Imager

Efficient onboard data compression can reduce the data volume from hyperspectral imagers on NASA and DoD spacecraft in order to return as much imagery as possible through constrained downlink channels. Lossless compression is important for signature extraction, object recognition, and feature classification capabilities. To provide onboard data compression, a hardware implementation of a lossless hyperspectral compression algorithm was developed using a field programmable gate array (FPGA). The underlying algorithm is the Fast Lossless (FL) compression algorithm reported in Fast Lossless Compression of Multispectral- Image Data (NPO-42517), NASA Tech Briefs, Vol. 30, No. 8 (August 2006), p. 26 with the modification reported in Lossless, Multi-Spectral Data Comressor for Improved Compression for Pushbroom-Type Instruments (NPO-45473), NASA Tech Briefs, Vol. 32, No. 7 (July 2008) p. 63, which provides improved compression performance for data from pushbroom-type imagers. An FPGA implementation of the unmodified FL algorithm was previously developed and reported in Fast and Adaptive Lossless Onboard Hyperspectral Data Compression System (NPO-46867), NASA Tech Briefs, Vol. 36, No. 5 (May 2012) p. 42. The essence of the FL algorithm is adaptive linear predictive compression using the sign algorithm for filter adaption. The FL compressor achieves a combination of low complexity and compression effectiveness that exceeds that of stateof- the-art techniques currently in use. The modification changes the predictor structure to tolerate differences in sensitivity of different detector elements, as occurs in pushbroom-type imagers, which are suitable for spacecraft use. The FPGA implementation offers a low-cost, flexible solution compared to traditional ASIC (application specific integrated circuit) and can be integrated as an intellectual property (IP) for part of, e.g., a design that manages the instrument interface. The FPGA implementation was benchmarked on the Xilinx Virtex IV LX25 device, and ported to a Xilinx prototype board. The current implementation has a critical path of 29.5 ns, which dictated a clock speed of 33 MHz. The critical path delay is end-to-end measurement between the uncompressed input data and the output compression data stream. The implementation compresses one sample every clock cycle, which results in a speed of 33 Msample/s. The implementation has a rather low device use of the Xilinx Virtex IV LX25, making the total power consumption of the implementation about 1.27 W.

Keymeulen, Didlier↗
NASA NTRS2012

CoNNeCT Baseband Processor Module Boot Code SoftWare (BCSW)

This software provides essential startup and initialization routines for the CoNNeCT baseband processor module (BPM) hardware upon power-up. A command and data handling (C&DH) interface is provided via 1553 and diagnostic serial interfaces to invoke operational, reconfiguration, and test commands within the code. The BCSW has features unique to the hardware it is responsible for managing. In this case, the CoNNeCT BPM is configured with an updated CPU (Atmel AT697 SPARC processor) and a unique set of memory and I/O peripherals that require customized software to operate. These features include configuration of new AT697 registers, interfacing to a new HouseKeeper with a flash controller interface, a new dual Xilinx configuration/scrub interface, and an updated 1553 remote terminal (RT) core. The BCSW is intended to provide a "safe" mode for the BPM when initially powered on or when an unexpected trap occurs, causing the processor to reset. The BCSW allows the 1553 bus controller in the spacecraft or payload controller to operate the BPM over 1553 to upload code; upload Xilinx bit files; perform rudimentary tests; read, write, and copy the non-volatile flash memory; and configure the Xilinx interface. Commands also exist over 1553 to cause the CPU to jump or call a specified address to begin execution of user-supplied code. This may be in the form of a real-time operating system, test routine, or specific application code to run on the BPM.

Yamamoto, Clifford K.↗
NASA NTRS2013

SpaceCube Version 1.5

SpaceCube 1.5 is a high-performance and low-power system in a compact form factor. It is a hybrid processing system consisting of CPU (central processing unit), FPGA (field-programmable gate array), and DSP (digital signal processor) processing elements. The primary processing engine is the Virtex- 5 FX100T FPGA, which has two embedded processors. The SpaceCube 1.5 System was a bridge to the SpaceCube 2.0 and SpaceCube 2.0 Mini processing systems. The SpaceCube 1.5 system was the primary avionics in the successful SMART (Small Rocket/Spacecraft Technology) Sounding Rocket mission that was launched in the summer of 2011. For SMART and similar missions, an avionics processor is required that is reconfigurable, has high processing capability, has multi-gigabit interfaces, is low power, and comes in a rugged/compact form factor. The original SpaceCube 1.0 met a number of the criteria, but did not possess the multi-gigabit interfaces that were required and is a higher-cost system. The SpaceCube 1.5 was designed with those mission requirements in mind. The SpaceCube 1.5 features one Xilinx Virtex-5 FX100T FPGA and has excellent size, weight, and power characteristics [4×4×3 in. (approx. = 10×10×8 cm), 3 lb (approx. = 1.4 kg), and 5 to 15 W depending on the application]. The estimated computing power of the two PowerPC 440s in the Virtex-5 FPGA is 1100 DMIPS each. The SpaceCube 1.5 includes two Gigabit Ethernet (1 Gbps) interfaces as well as two SATA-I/II interfaces (1.5 to 3.0 Gbps) for recording to data drives. The SpaceCube 1.5 also features DDR2 SDRAM (double data rate synchronous dynamic random access memory); 4- Gbit Flash for storing application code for the CPU, FPGA, and DSP processing elements; and a Xilinx Platform Flash XL to store FPGA configuration files or application code. The system also incorporates a 12 bit analog to digital converter with the ability to read 32 discrete analog sensor inputs. The SpaceCube 1.5 design also has a built-in accelerometer. In addition, the system has 12 receive and transmit RS- 422 interfaces for legacy support. The SpaceCube 1.5 processor card represents the first NASA Goddard design in a compact form factor featuring the Xilinx Virtex- 5. The SpaceCube 1.5 incorporates backward compatibility with the Space- Cube 1.0 form factor and stackable architecture. It also makes use of low-cost commercial parts, but is designed for operation in harsh environments.

Geist, Alessandro↗
NASA NTRS2010

NASA Accelerates SpaceCube Technology into Orbit

On May 11, 2009, STS-125 Space Shuttle Atlantis blasted off from Kennedy Space Center on a historic mission to service the Hubble Space Telescope (HST). In addition to sending up the hardware and tools required to repair the observatory, the servicing team at NASA's Goddard Space Flight Center also sent along a complex experimental payload called Relative Navigation Sensors (RNS). The main objective of the RNS payload was to provide real-time image tracking of HST during rendezvous and docking operations. RNS was a complete success, and was brought to life by four Xilinx FPGAs (Field Programmable Gate Arrays) tightly packed into one integrated computer called SpaceCube. SpaceCube is a compact, reconfigurable, multiprocessor computing platform for space applications demanding extreme processing capabilities based on Xilinx Virtex 4 FX60 FPGAs. In a matter of months, the concept quickly went from the white board to a fully funded flight project. The 4-inch by 4-inch SpaceCube processor card was prototyped by a group of Goddard engineers using internal research funding. Once engineers were able to demonstrate the processing power of SpaceCube to NASA, HST management stood behind the product and invested in a flight qualified version, inserting it into the heart of the RNS system. With the determination of putting Xilinx into space, the team strengthened to a small army and delivered a fully functional, space qualified system to the mission.

Petrick, David↗
NASA NTRS2018

High Performance Space Computing with System-on-Chip Instrument Avionics for Space-based Next Generation Imaging Spectrometers (NGIS).

The emergent technology of system-on-chip (SoC) devices promises lighter, smaller, cheaper, and more capable and reliable space electronic systems that could help to unveil some of the most treasured secrets in our universe. This technology is an improvement over the technology that is currently used in space applications, which lags behind stateof-the-art commercial-off-the-shelf (COTS) equipment by several generations. SoC technology integrates all computational power required by next-generation space exploration science instruments onto a single chip. This presentation will describe a Xilinx Zynq-based data acquisition, cloud-screening and compression computing system that has been developed at the Jet Propulsion Laboratory (JPL) for JPL’s Next Generation Imaging Spectrometers (NGIS). The Xilinx Zynq-based Alpha Data hardware assembly fits into a 120mm by 190m by 40mm assembly and uses 9 watts at peak performance. The computing element is a Xilinx Zynq Z7045Q which includes a Kintex-7 FPGA (equivalent to 3 RAD Virtex5 FPGAs in terms of logic cell resources) and dual-core ARM Cortex-A9 Processors (equivalent to 10 RAD750 Power PCs in term of processing capability).

Smith, Adam↗
NASA NTRS2018

High Performance Space Computing with System-on-Chip Instrument Avionics for Space-based Next Generation Imaging Spectrometers (NGIS).

The emergent technology of system-on-chip (SoC) devices promises lighter, smaller, cheaper, and more capable and reliable space electronic systems that could help to unveil some of the most treasured secrets in our universe. This technology is an improvement over the technology that is currently used in space applications, which lags behind state-of-the-art commercial-off-the-shelf (COTS) equipment by several generations. SoC technology integrates all computational power required by next-generation space exploration science instruments onto a single chip. This presentation will describe a Xilinx Zynq-based data acquisition, cloud-screening and compression computing system that has been developed at the Jet Propulsion Laboratory (JPL) for JPL’s Next Generation Imaging Spectrometers (NGIS). The Xilinx Zynq-based Alpha Data hardware assembly fits into a 120mm by 190m by 40mm assembly and uses 9 watts at peak performance. The computing element is a Xilinx Zynq Z7045Q which includes a Kintex-7 FPGA (equivalent to 3 RAD Virtex5 FPGAs in terms of logic cell resources) and dual-core ARM Cortex-A9 Processors (equivalent to 10 RAD750 Power PCs in term of processing capability).

Dolinar, Sam↗
NASA NTRS2019

High performance space computing with system-on-chip instrument avionics for space-based Next Generation Imaging Spectrometers (NGIS)

The emergent technology of system-on-chip (SoC) devices promises lighter, smaller, cheaper, and more capable and reliable space electronic systems that could help to unveil some of the most treasured secrets in our universe. This technology is an improvement over the technology that is currently used in space applications, which lags behind state-of-the-art commercial-off-the-shelf (COTS) equipment by several generations. SoC technology integrates all computational power required by next-generation space exploration science instruments onto a single chip. This presentation will describe a Xilinx Zynq-based data acquisition, cloud-screening and compression computing system that has been developed at the Jet Propulsion Laboratory (JPL) for JPL’s Next Generation Imaging Spectrometers (NGIS). The Xilinx Zynq-based Alpha Data hardware assembly fits into a 120mm by 190m by 40mm assembly and uses 9 watts at peak performance. The computing element is a Xilinx Zynq Z7045Q which includes a Kintex-7 FPGA (equivalent to 3 RAD Virtex5 FPGAs in terms of logic cell resources) and dual-core ARM Cortex-A9 Processors (equivalent to 10 RAD750 Power PCs in term of processing capability).

Dolinar, Sam↗
NASA NTRS2015

Single Event Effects in FPGA Devices 2014-2015

This presentation provides an overview of single event effects in FPGA devices 2014-2015 including commercial Xilinx V5 heavy ion accelerated testing, Xilinx Kintex-7 heavy ion accelerated testing. Mitigation study, and investigation of various types of triple modular redundancy (TMR) for commercial SRAM based FPGAs.

Single event upset (SEU)↗
NASA NTRS2016

Single Event Effects in FPGA Devices 2015-2016

This presentation provides an overview of single event effects in FPGA devices 2015-2016 including commercial Xilinx V5 heavy ion accelerated testing, Xilinx Kintex-7 heavy ion accelerated testing, mitigation study, and investigation of various types of triple modular redundancy (TMR) for commercial SRAM based FPGAs.

Xilinx V5↗
NASA NTRS2016

Single Event Effects in FPGA Devices 2015-2016

This presentation provides an overview of single event effects in FPGA devices 2015-2016 including commercial Xilinx V5 heavy ion accelerated testing, Xilinx Kintex-7 heavy ion accelerated testing. Mitigation study, and investigation of various types of triple modular redundancy (TMR) for commercial SRAM based FPGAs.

Single Event Upset (SEU) Testing↗
DOE OSTI2024

Characterization of throughput on the AXI DMA bus for burst data transfer over Ethernet

cThe Xilinx AXI Direct Memory Access (AXI DMA) module is an efficient solution for medium-speed data transfer in Xilinx SoC FPGAs, supporting data rates greater than 1000 Gbps even in very suboptimal operating modes. It facilitates direct transfer of AXI stream data into processor memory without constant software intervention, which reduces overhead and ensures consistent data logging. By utilizing the FPGA's available memory, large circular buffers (1-5 GiB) are used to buffer data and accommodate network limitations, enabling high-rate data bursts. In this study, we measured the performance of AXI DMA under conditions simulating its lowest practical data transfer speeds. The Arbitrary Length Data Sender was used to transmit AXI stream packets at 32-bit width and 100 MHz frequency, a narrow width and slow speed. Results show that the AXI DMA can transfer up to 3192.76 Mbps with large packet sizes but experiences reduced performance for smaller packets, as low as 2.6 Mbps for 4-byte packets. For Ethernet-limited applications, packet sizes between 8,000 and 16,000 bytes provided optimal transfer speeds of 874 to 1600 Mbps. These findings suggest that the AXI DMA is not the limiting factor in systems where packet sizes exceed 8,000 bytes.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

Entropy Analysis of FPGA Interconnect and Switch Matrices for Physical Unclonable Functions

Random variations in microelectronic circuit structures represent the source of entropy for physical unclonable functions (PUFs). In this paper, we investigate delay variations that occur through the routing network and switch matrices of a field-programmable gate array (FPGA). The delay variations are isolated from other components of the programmable logic, e.g., look-up tables (LUTs), flip-flops (FFs), etc., using a feature of Xilinx FPGAs called dynamic partial reconfiguration (DPR). A set of partial designs is created to fix the placement of a time-to-digital converter (TDC) and supporting infrastructure to enable the path delays through the target interconnect and switch matrices to be extracted by subtracting out common-mode delay components. Delay variations are analyzed in the different levels of routing resources available within FPGAs, i.e., local routing and across-chip routing. Data are collected from a set of Xilinx Zynq 7010 devices, and a statistical analysis of within-die variations in delay through a set of the randomly-generated and hand-crafted interconnects is presented.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1993

Splash 2

Splash 2 is an attached processor system for Sun SPARC 2 workstations that uses Xilinx 4010 Field Programmable Gate Arrays (FPGA's) as its processing elements. The purpose of this paper is to describe Splash 2. The predecessor system, Splash 1, was designed to be used as a systolic processing system. Although it was very successful in that mode, there were many other applications that were not systolic, but which were successful, nonetheless, on Splash 1, or that were not implemented successfully due to one or more architectural limitations, most notably I/O bandwidth and interprocessor communication. Although other uses to increase computational performance have been found for the Xilinx FPGA's that are Splash's processing elements. Splash is unique in its goal to be programmable in a general sense.

Arnold, Jeffrey M.↗
NASA NTRS2008

VIRTEX-4 VQ static SEU Characterization Summary

This report is the result of the combined efforts of members within the Xilinx Radiation Test Consortium (XRTC), sometimes known as the Xilinx SEE Test Consortium. The XRTC is a voluntary association of aerospace entities, including leading aerospace companies, universities and national laboratories, combining resources to characterize reconfigurable FPGAs for aerospace applications. Previous publications of Virtex-4 radiation results are for commercial (non-epitaxial) devices; see, for example, Refs. 1-4. A notable exception is Ref. 5, which presents XRTC upset measurements of storage elements in the PowerPC405s in the XQR4VFX60. This report of upset susceptibility to heavy ions and protons of the static memory elements in the Virtex-4QV family is a direct parallel to the XRTC report on the thin epitaxial devices in the Virtex-2 family released four years ago.

field programmable gate array (FPGA)↗
NASA NTRS2011

Integration of the Reconfigurable Self-Healing eDNA Architecture in an Embedded System

In this work we describe the first real world case study for the self-healing eDNA (electronic DNA) architecture by implementing the control and data processing of a Fourier Transform Spectrometer (FTS) on an eDNA prototype. For this purpose the eDNA prototype has been ported from a Xilinx Virtex 5 FPGA to an embedded system consisting of a PowerPC and a Xilinx Virtex 5 FPGA. The FTS instrument features a novel liquid crystal waveguide, which consequently eliminates all moving parts from the instrument. The addition of the eDNA architecture to do the control and data processing has resulted in a highly fault-tolerant FTS instrument. The case study has shown that the early stage prototype of the autonomous self-healing eDNA architecture is expensive in terms of execution time.

Computer architecture↗
NASA NTRS2011

FPGA for Power Control of MSL Avionics

A PLGT FPGA (Field Programmable Gate Array) is included in the LCC (Load Control Card), GID (Guidance Interface & Drivers), TMC (Telemetry Multiplexer Card), and PFC (Pyro Firing Card) boards of the Mars Science Laboratory (MSL) spacecraft. (PLGT stands for PFC, LCC, GID, and TMC.) It provides the interface between the backside bus and the power drivers on these boards. The LCC drives power switches to switch power loads, and also relays. The GID drives the thrusters and latch valves, as well as having the star-tracker and Sun-sensor interface. The PFC drives pyros, and the TMC receives digital and analog telemetry. The FPGA is implemented both in Xilinx (Spartan 3- 400) and in Actel (RTSX72SU, ASX72S). The Xilinx Spartan 3 part is used for the breadboard, the Actel ASX part is used for the EM (Engineer Module), and the pin-compatible, radiation-hardened RTSX part is used for final EM and flight. The MSL spacecraft uses a FC (Flight Computer) to control power loads, relays, thrusters, latch valves, Sun-sensor, and star-tracker, and to read telemetry such as temperature. Commands are sent over a 1553 bus to the MREU (Multi-Mission System Architecture Platform Remote Engineering Unit). The MREU resends over a remote serial command bus c-bus to the LCC, GID TMC, and PFC. The MREU also sends out telemetry addresses via a remote serial telemetry address bus to the LCC, GID, TMC, and PFC, and the status is returned over the remote serial telemetry data bus.

Wang, Duo↗
NASA NTRS2014

Aeroflex Technology as Class-Y Demonstrator

Modern space field programmable gate array (FPGA) devices with increased functional density and operational frequency, such as Xilinx Virtex 4 (V4) and S (V5), are packaged in non-hermetic ceramic flip chip forms. These next generation space parts were not qualified to the MIL-PRF-38535 Qualified Manufacturer Listing (QML) class-V when they were released because class-V was only intended for hermetic parts. In order to bring Xilinx V5 type packages into the QML system, it was suggested that class-Y be set up as a new category. From 2010 through 2014, a JEDEC G12 task group developed screening and qualification requirements for Class-Y products. The Document Standardization Division of the Defense Logistics Agency (DLA) has completed an engineering practice study. In parallel with the class-Y efforts, the NASA Electronic Parts and Packaging (NEPP) program has funded JPL to study potential reliability issues of the class-Y products. The major hurdle of this task was the absence of adequate research samples. Figure 1-1 shows schematic diagrams of typical structures of class-Y type products. Typically, class-Y products are either in ceramic flip chip column grid array (CGA) or land grid array (LGA) form. In class-Y packages, underfill and heat spread adhesive materials are directly exposed to the spacecraft environment due to their non-hermeticity. One of the concerns originally raised was that the underfill material could degrade due to the spacecraft environment and negatively impact the reliability of the package. In order to study such issues, it was necessary to use ceramic daisy chain flip chip package samples so that continuity of flip chip solder bumps could be monitored during the reliability tests. However, none of the commercially available class-Y daisy chain parts had electrical connections through flip chip solder bumps; only solder columns were daisy chained, which made it impossible to test continuity of flip chip solder bumps without using extremely costly functional parts. Among space parts manufacturers who were interested in producing class-Y products, Aeroflex Microelectronic Solutions-HiRel had been developing assembly processes using their internal R&D classy type samples. In early 2012, JPL and Aeroflex initiated a collaboration to study reliability of the Aeroflex technology as a class-Y demonstrator.

Suh, Jong-ook↗