There is a direct need for high-visibility NASA missions that provide significant scientific impact or have a high mission class using completely radiation-hardened (rad-hard) electronics solutions, to enable artifici...
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ISBN:
(纸本)9798350304626
There is a direct need for high-visibility NASA missions that provide significant scientific impact or have a high mission class using completely radiation-hardened (rad-hard) electronics solutions, to enable artificial intelligence (AI) applications in harsh environments despite severe size, weight, and power (SWaP) constraints. For these missions, where current state-of-the-art solutions are too power-demanding or are incapable of surviving the intended radiation environment, an alternative rad-hard processing architecture that can leverage the control-flow capabilities of scalar processors while also incorporating the hardware-acceleration capabilities of an FPGA is of significant value. Therefore, in this research, we propose a miniaturized (3.5 in. Chi 3.5 in. form factor) processor card featuring the GR740 quad-core rad-hard processor and the CertusPro-NX-RT radiation-tolerant FPGA, called the SpaceCube GR740 Host for Onboard Science and Telemetry (GHOST) architecture. The card will be designed to conform to the NASA Goddard Space Flight Center (GSFC) CubeSat Card Specification (CS2), which provides a common template to build new 1U CubeSat-sized cards compatible with a variety of other avionics designs. The GR740 features a fault-tolerant quad-processor LEON4FT SPARC V8 integer unit with a 7-stage pipeline and 4 Chi 4 KiB instruction and data caches. To extend the capabilities of the GR740, the CertusPro-NX-RT, a low-power radiation-tolerant FPGA, was combined to create a hybrid system architecture, providing the benefits of a programmablelogic fabric. The GHOST architecture supports high-reliability, general-purpose processing and system monitoring via the GR740 while simultaneously increasing the AI-based application performance via a combination of the GR740 and CertusPro-NX-RT.
Every aspect of the modern world is powered by technology. The development of more advanced technology has led to the creation of more sophisticated electronic devices. The automation of homes is quickly becoming one ...
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Quantum-dot Cellular Automata (QCA) is a newly-developed nanoscale electron device that has the potential to replace the conventional transistor in the future. Owing to the unique field-coupling mechanism of QCA, seve...
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The article presents a method of video output subsystem's development with an ultra-high resolution (2560 x 1440 pixels and higher) support, a method for assessing the permissible video mode parameters and setting...
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a certain embedded product failed to load FPGA configuration occasionally when it was powered on. In order to determine the cause of the failure, the principle of FPGA configuration circuit was studied, and the possib...
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The pulse width parameter of integrated circuits is an important technical indicator for measuring the system's high-speed performance and rapid response capabilities, directly affecting the device's response ...
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This research presents a real-time automatic control system for ensuring reliable power supply in distributed generation systems. Leveraging programmablelogic Controllers (PLCs) and Supervisory Control and Data Acqui...
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ISBN:
(数字)9798331515720
ISBN:
(纸本)9798331515737
This research presents a real-time automatic control system for ensuring reliable power supply in distributed generation systems. Leveraging programmablelogic Controllers (PLCs) and Supervisory Control and Data Acquisition (SCADA), the system prioritizes and dynamically switches loads based on available power sources. By utilizing ladder logic for PLC programming and SCADA for centralized monitoring, the system effectively manages power distribution and minimizes manual intervention. Demonstrated in industrial settings, this approach enhances operational efficiency and reliability, particularly in regions prone to power outages.
The present invention relates to an FPGA driven traffic management system specifically designed for five-point intersections, which are notably complex due to their unique traffic flow patterns. FPGA is field programm...
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ISBN:
(数字)9798331520762
ISBN:
(纸本)9798331520779
The present invention relates to an FPGA driven traffic management system specifically designed for five-point intersections, which are notably complex due to their unique traffic flow patterns. FPGA is fieldprogrammable gate of array basically used to implement digital virtual logic into real hardware. Here FPGAs are utilized to process and control this system periodically every 360 sec durations. This innovative approach not only improves traffic flow and reduces waiting times but also contributes to handle emergency like situation and according to that manipulate signals. The adaptability of the invention to diverse traffic conditions makes it a robust solution for urban traffic management challenges.
The latency and resource consumption are significant factors for routing lookup (RL) in network applications. This paper proposes a combined RL strategy (TCAM-Hash), which utilizes the advantages of both TCAM- based a...
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Convolutional Neural Networks (CNNs) combine large amounts of parallelizable computation with frequent memory access. fieldprogrammable Gate Arrays (FPGAs) can achieve low latency and high throughput CNN inference by...
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ISBN:
(数字)9798331530075
ISBN:
(纸本)9798331530082
Convolutional Neural Networks (CNNs) combine large amounts of parallelizable computation with frequent memory access. fieldprogrammable Gate Arrays (FPGAs) can achieve low latency and high throughput CNN inference by implementing dataflow accelerators that pipeline layer-specific hardware to implement an entire network. By implementing a different processing element for each CNN layer, these layer-pipelined accelerators can achieve high compute density, but having all layers processing in parallel requires high memory bandwidth. Traditionally this has been satisfied by storing all weights on chip, but this is infeasible for the largest CNNs, which are often those most in need of acceleration. In this work we augment a state-of-the-art dataflow accelerator (HPIPE) to leverage both High-Bandwidth Memory (HBM) and on-chip storage, enabling high performance layer-pipelined dataflow acceleration of large CNNs. Based on profiling results of HBM’s latency and throughput against expected address patterns, we develop an algorithm to choose which weight buffers should be moved off chip and how deep the on-chip FIFOs to HBM should be to minimize compute unit stalling. We integrate the new hardware generation within the HPIPE domain-specific CNN compiler and demonstrate good bandwidth efficiency against theoretical limits. Compared to the best prior work we obtain speed-ups of at least $19.4 \mathrm{x}, 5.1 \mathrm{x}$ and 10.5 x on ResNet-18, ResNet-50 and VGG-16 respectively.
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