Bulk bitwise operations, ie, bitwise operations on large bit vectors, are prevalent in a wide
range of important application domains, including databases, graph processing, genome …

Through the attention mechanism, Transformer-based large-scale deep neural networks
(LSDNNs) have demonstrated remarkable achievements in artificial intelligence …

Number Theoretic Transform (NTT) is an essential mathematical tool for computing
polynomial multiplication in promising lattice-based cryptography. However, costly division …

In the age of big data, information security has become a major issue of debate, especially
with the rise of the Internet of Things (IoT), where attackers can effortlessly obtain physical …

To overcome the bottleneck of the classical processor-centric architectures, Computation-in-
Memory (CiM) is a promising paradigm where operations are performed directly in memory …

In-memory computing (IMC) emerges as one of the most promising computing technologies
for data-intensive applications to ameliorate the “memory wall” bottleneck in von Neumann …

In-cache computing technology transforms existing caches into long-vector compute units
and offers low-cost alternatives to building expensive vector engines for mobile CPUs …

The modern trend of exploring Artificial Intelligence (AI) in various industries, such as big
data, edge computing, automobile, and medical applications, has increased tremendously …

Modern computing systems are limited in performance by the memory bandwidth available
to processors, a problem known as the memory wall. Processing-in-Memory (PIM) promises …

Encryption and decryption of data with very low latency and high energy efficiency is
desirable in almost every application that deals with sensitive data. The advanced …