Related papers: Large-Scale Integrated Vector-Matrix Multiplicatio…
The development of deep neural networks is witnessing fast growth in network size, which requires novel hardware computing platforms with large bandwidth and low energy consumption. Optical computing has been a potential candidate for…
We study the problem of multiplying two bit matrices with entries either over the Boolean algebra $(0,1,\vee,\wedge)$ or over the binary field $(0,1,+,\cdot)$. We engineer high-performance open-source algorithm implementations for…
Vector-Matrix Multiplication (VMM) is the fundamental and frequently required computation in inference of Neural Networks (NN). Due to the large data movement required during inference, VMM can benefit greatly from in-memory computing.…
2D materials and their monolayers have attracted widespread interest by virtue of their unique electronic and optical properties. In addition to their remarkable physical characteristics, their atomically thin nature enables their…
The Von-Neumann bottleneck is a clear limitation for data-intensive applications, bringing in-memory computing (IMC) solutions to the fore. Since large data sets are usually stored in nonvolatile memory (NVM), various solutions have been…
Existing deep convolutional neural networks (CNNs) generate massive interlayer feature data during network inference. To maintain real-time processing in embedded systems, large on-chip memory is required to buffer the interlayer feature…
Two-dimensional (2D) layered materials-based field-effect transistors (FETs) are promising for ultimate scaled electron device applications because of the improved electrostatics to atomically thin body thickness. However, compared with the…
We propose a theoretical model for describing the operation of a transistor with a MoS2 monolayer channel, which allows to obtain an analytical approximation of the potential in the channel. This potential depends on the drain and gate…
Flash memory has become a ubiquitous solid-state memory device, it is widely used in portable digital devices, computers, and enterprise applications. The development of the information age has put forward higher requirements for memory…
The end of conventional Dennard scaling and the widening gap between memory bandwidth and arithmetic throughput have made the von Neumann partition a structural bottleneck rather than a transient one. Two-dimensional (2D) materials, with…
The successful assembly of heterostructures consisting of several layers of different 2D materials in arbitrary order by exploiting van der Waals forces has truly been a game changer in the field of low dimensional physics. For instance,…
As CMOS scaling reaches its technological limits, a radical departure from traditional von Neumann systems, which involve separate processing and memory units, is needed in order to significantly extend the performance of today's computers.…
Two-dimensional (2D) transition metal dichalcogenides (TMDCs), exemplified by molybdenum disulfide (MoS2), have shown exceptional potential for data-centred, energy-efficient electronic applications due to their unique electrical,…
Monolayer two-dimensional transitional metal dichalcogenides, such as MoS2, WS2 and WSe2, are direct band gap semiconductors with large exciton binding energy. They attract growing attentions for opto-electronic applications including solar…
The emerging mobile devices in this era of internet-of-things (IoT) require a dedicated processor to enable computationally intensive applications such as neuromorphic computing and signal processing. Vector-by-matrix multiplication (VMM)…
Ferroelecticity, one of the keys to realize nonvolatile memories owing to the remanent electric polarization, has been an emerging phenomenon in the two-dimensional (2D) limit. Yet the demonstrations of van der Waals (vdW) memories using 2D…
The screening of novel materials is an important topic in the field of materials science. Although traditional computational modeling, especially first-principles approaches, is a very useful and accurate tool to predict the properties of…
`In-memory computing' is being widely explored as a novel computing paradigm to mitigate the well known memory bottleneck. This emerging paradigm aims at embedding some aspects of computations inside the memory array, thereby avoiding…
van der Waals stacking of two-dimensional (2D) materials offers a powerful platform for engineering material interfaces with tailored electronic and optical properties. While most van der Waals multilayers have featured inorganic…
We performed density functional theory (DFT) calculations for a bi-layered heterostructure combining a graphene layer with a MoS2 layer with and without intercalated Li atoms. Our calculations demonstrate the importance of the van der Waals…