Sharif Digital Repository

There are three types of Slices in an FPGA, and based on the functionality of these slices, SliceM has the most features especially for designs based on shift registers, adders, and ROMs, and from all of the slices, 25% of them are SliceM. Among the earlier designs that are FPGA-based, Anderson PUF is that is classified as a weak delay-based PUF. In Anderson’s design there always should be atleast two SliceMs that their LUTs are configured as shift registers, the Andersons PUF in some FPGA Architecture especially Series 7 FPGAs, consumes two SliceMs and two other SliceLs, so practically we are using four of our precious slices. Rather than these, in series 6 FPGAs, the design should change... 

Public-key cryptography is vital to secure digital communication. The classic instances of these cryptosystems are insecure against large-scale quantum computers. As a result, post-quantum cryptography has emerged as a replacement, which includes different categories. Isogeny-based schemes are one of the promising candidates mainly because of their smaller public key length. Due to high computational cost of such schemes, efficient implementations are significantly important. In this thesis, we have presented various solutions at three different abstraction layers. At the lowest layer, which deals with modular arithmetic, two hardware architectures are presented to perform modular... 

Today, the “wireless” is used almost synonymously with radio-frequency (RF) technologies as a result of the wide-scale deployment and utilization of wireless RF devices and systems. The RF band ranges from 300 kHz to 300 GHz and its use is regulated by regional and international agencies. With the ever-growing popularity of data-heavy wireless communications, wireless products and services, the demand for RF spectrum is outstripping supply, which causes the spectrum congestion. Therefore, the time has come to seriously consider other viable options for wireless communication using the upper parts of the electromagnetic spectrum. In this way, the optical band which includes infrared, visible,... 

Recently, Convolutional neural networks (CNNs) are widely used in many artificial intelligence applications such as image processing, speech processing and robotics. The neural networks superior accuracy comes at the cost of high computational complexity. Recent studies show that these operations can be performed in parallel. Therefore, as graphic processing units (GPUs) offer the best performance in terms of computational power and throughput, they are widely used to implement and accelerate neural networks. Nevertheless, the high price and power consumption of these processors have resulted in drawing more attraction towards Field-Programmable Arrays (FPGAs). In order to improve resource... 

In recent years, due to the drawback of rule-based firewalls in detecting unknown attacks, using neural networks has got more attention to be used in firewalls. As the computation load of neural networks are so much there is a need to decrease the processing time and power consumption as they are under load 24/7. Although there have been huge achievements in the usage of graphics processing units (which contain numerous processing cores) in neural networks, their high power consumption has made the scientists think about an alternative to implement neural networks. Field Programmable Gate Array (FPGA) is one of the most serious candidates to be used for implementing neural networks. The goal... 

Deep learning, as a subdivision of machine learning, attempts to model high-level concepts by using a deep graph, consisting of several layers of linear and nonlinear transformations. Implementing these algorithms on hardware is a big challenge.¬This project offers a system in which various hardware methodologies can be used to implement deep learning algorithms side by side. The overall structure of the system consists of high-level programming interfaces for implementation and expression of machine learning algorithms by the user, which will be available as libraries in a high-level programming language such as Python, Ruby, and Julia. These interfaces allow the user to evaluate their... 

Looking for eye paths is widely used in various research and even commercial areas, Eye trackers that are used commercially today do this by using infrared transmitters and receivers. As the speed and performance of the processors advanced, many efforts have been made to create an eye-tracking device using visible light without any movement restrictions for the subject, and efforts to increase the accuracy and speed of sampling are still ongoing; The initial methods proposed in this area are feature-based, but newer papers and researches have used Deep learning methods to do this. The commonly used methods for eye tracking in visible light are three main steps: 1. Fetching frames from the... 

Alignment of genetic sequences is a fundamental part of genetic and bio-science. Alignment of DNA and protein sequences has an effective role in accelerating and simplifying problems in Bioinformatics like predicting protein interactions. Smith-Waterman algorithm is a precise algorithm for performing local alignment, suffering from computation complexity. There are some implementations on CPU, GPU, and FPGA platforms in order to reduce the run time of this algorithm. FPGA implementation is considered because of low power consumption and high degree of parallelism. With using pipeline and hardware redundancy techniques, various architectures have been proposed and implemented. In the best...