Search results for "Field-programmable gate array"
showing 10 items of 175 documents
Architecture of a digital PFM controller for IC implementation
2006
This paper presents a digital controller architecture oriented to IC implementation. The classical digital pulse width modulator (D-PWM), using digital analog converter (DAC), is replaced with a Sigma-Delta (/spl Sigma//spl Delta/) modulator based on pulse frequency modulator (PFM) technique. Results of an investigation from a prototype for DC-DC converter, in terms of simulated and experimental performances, are reported, together with harmonic frequency investigation. The control function design is implemented on a field programmable gate array (FPGA). As a consequence of good agreement between simulated and experimental results, the proposed architecture realizes a digital control loop w…
A Hardware and Secure Pseudorandom Generator for Constrained Devices
2018
Hardware security for an Internet of Things or cyber physical system drives the need for ubiquitous cryptography to different sensing infrastructures in these fields. In particular, generating strong cryptographic keys on such resource-constrained device depends on a lightweight and cryptographically secure random number generator. In this research work, we have introduced a new hardware chaos-based pseudorandom number generator, which is mainly based on the deletion of an Hamilton cycle within the $N$ -cube (or on the vectorial negation), plus one single permutation. We have rigorously proven the chaotic behavior and cryptographically secure property of the whole proposal: the mid-term eff…
Highly Performant, Deep Neural Networks with sub-microsecond latency on FPGAs for Trigger Applications
2020
Artificial neural networks are becoming a standard tool for data analysis, but their potential remains yet to be widely used for hardware-level trigger applications. Nowadays, high-end FPGAs, often used in low-level hardware triggers, offer theoretically enough performance to include networks of considerable size. This makes it very promising and rewarding to optimize a neural network implementation for FPGAs in the trigger context. Here an optimized neural network implementation framework is presented, which typically reaches 90 to 100% computational efficiency, requires few extra FPGA resources for data flow and controlling, and allows latencies in the order of 10s to few 100s of nanoseco…
Efficient MLP Digital Implementation on FPGA
2005
The efficiency and the accuracy of a digital feed-forward neural networks must be optimized to obtain both high classification rate and minimum area on chip. In this paper an efficient MLP digital implementation. The key features of the hardware implementation are the virtual neuron based architecture and the use of the sinusoidal activation function for the hidden layer. The effectiveness of the proposed solutions has been evaluated developing different FPGA based neural prototypes for the High Energy Physics domain and the automatic Road Sign Recognition domain. The use of the sinusoidal activation function decreases hardware resource employment of about 32% when compared with the standar…
Experimental Evaluation of the Performance of a Three-Phase Five-Level Cascaded H-Bridge Inverter by Means FPGA-Based Control Board for Grid Connecte…
2018
Over the last decades, plants devoted to the generation of green energy significantly increased their number, together with the demand of same electrical energy, also stored in battery systems. This fact produced the growth of energy conversion systems with advanced performances with respect to the traditional ones. In this circumstance, multilevel converters play a significant role for their great advantages in performances, flexibility, fault-tolerability, employment of renewable energy sources and storage systems and finally yet importantly reduced filter requirements. In this context, this paper faces the performance of a cascaded H-bridge 5 level inverter in terms of harmonic distortio…
Moving Learning Machine Towards Fast Real-Time Applications: A High-Speed FPGA-based Implementation of the OS-ELM Training Algorithm
2018
Currently, there are some emerging online learning applications handling data streams in real-time. The On-line Sequential Extreme Learning Machine (OS-ELM) has been successfully used in real-time condition prediction applications because of its good generalization performance at an extreme learning speed, but the number of trainings by a second (training frequency) achieved in these continuous learning applications has to be further reduced. This paper proposes a performance-optimized implementation of the OS-ELM training algorithm when it is applied to real-time applications. In this case, the natural way of feeding the training of the neural network is one-by-one, i.e., training the neur…
An efficient hardware implementation of MQ decoder of the JPEG2000
2014
Abstract JPEG2000 is an international standard for still images intended to overcome the shortcomings of the existing JPEG standard. Compared to JPEG image compression techniques, JPEG2000 standard has not only better not only has better compression ratios, but it also offers some exciting features. As it’s hard to meet the real-time requirement of image compression systems by software, it is necessary to implement compression system by hardware. The MQ decoder of the JPEG2000 standard is an important bottleneck for real-time applications. In order to meet the real-time requirement we propose in this paper a novel architecture for a MQ decoder with high throughput which is comparable to tha…
Multiprocessor SoC Implementation of Neural Network Training on FPGA
2008
Software implementations of artificial neural networks (ANNs) and their training on a sequential processor are inefficient because they do not take advantage of parallelism. ASIC and FPGA implementations employ specific hardware structures to exploit parallelism in order to improve processing speed; however, optimizing resource usage requires the use of fixed-point arithmetic, thereby losing precision, and the final system is restricted to a particular network topology. This paper presents a mixed approach based on a multiprocessor system-on-chip (SoC) on a FPGA. The use of software-driven embedded microprocessors with custom floating-point extensions for ANN related functions allows for gr…
SVM approximation for real-time image segmentation by using an improved hyperrectangles-based method
2003
A real-time implementation of an approximation of the support vector machine (SVM) decision rule is proposed. This method is based on an improvement of a supervised classification method using hyperrectangles, which is useful for real-time image segmentation. The final decision combines the accuracy of the SVM learning algorithm and the speed of a hyperrectangles-based method. We review the principles of the classification methods and we evaluate the hardware implementation cost of each method. We present the combination algorithm, which consists of rejecting ambiguities in the learning set using SVM decision, before using the learning step of the hyperrectangles-based method. We present re…
Modeling RISC-V Processor in IP-XACT
2018
IP-XACT is the most used standard in IP (Intellectual Property) integration. It is intended as a language neutral golden reference, from which RTL and HW dependent SW is automatically generated. Despite its wide popularity in the industry, there are practically no public and open design examples for any part of the design flow from IP-XACT to synthesis. One reason is the difficulty of creating IP-XACT models for existing RTL projects. In this paper, we address the issues by modeling the PULPino RISC-V microprocessor that is written in SystemVerilog (SV) and the project distributed over several repositories. We propose how to solve the mismatching concepts between SV project and IP-XACT, and…