The traditional Von-Neumann architecture is reaching its limits and finding it difficult to cope up with the ever-increasing demands of modern workloads like artificial intelligence. This demand has fueled the search of technologies that can mimic human brain to efficiently combine both memory and computation within a single device. In this work, we present the state-of-the-art research in the domain of computation-in-memory. In particular, we take a look at memristors and its widespread application in neuromorphic computation. We introduce ReRAMs in terms of their novel computing paradigms and present ReRAM-specific design flows. We address the various circuit opportunities and challenges related to reliability and fault tolerance associated with them. Another high-potential candidate to leverage memory and computation from a single device is Ferroelectric Field-effect Transistor (FeFET). Here we present a co-integration of such FeFETs with another emerging nanotechnology concept, called Reconfigurable Field Effect Transistor (RFET) and discuss the impact of the higher amount of states provided by this combination.@en

Cryptanalysis is an essential part of cryptology. Not just is it useful to break ciphers for malicious applications, but it is also the basis for building secure ones. In fact almost all the ciphers still in use are trusted to be secure mainly due to the fact that many cryptanalysts are trying hard to break them publicly and failing. However, most of the time successful cryptanalytic results end up violating the cipher designers claims, but the attack itself remains theoretical due to the lack of enough resources/algorithms to efficiently implement it. For example, while the first practical SHA-1 collision was found in 2017, most of the ideas and vulnerabilities behind the attack had been discovered in 2005. The internet and IT industries didn't give much attention to the early theoretical results and it wasn't until 2016 that internet browsers starting getting rid of SHA-1. The leap from 2005 to 2017 was due to advancements in the attack algorithms, implementation techniques and hardware fabrication technologies. While hardware fabrication so far keeps on improving according to Moore's law, the other two aspects require a lot of research effort. In this survey, we touch on several examples of these efforts over the years. The survey is divided into three parts, cryptanalytic attacks designed with specific implementation requirements, previous cryptanalytic machines and quantum computers, the technology that promises to change how we think about cryptography and cryptanalysis.@en