Related papers: Best CNTFET Ternary Adders?

This work introduces novel training and post-training compression schemes to reduce external memory access during transformer model inference. Additionally, a new control flow mechanism, called dynamic batching, and a novel buffer…

In this technical note, we provide a comparison of the design metrics of various quasi-delay-insensitive (QDI) asynchronous adders, where the adders correspond to diverse architectures. QDI adders are robust, and the objective of this…

While traditional implementations of variable-length digital delay lines are based on a circular buffer accessed by two pointers, we propose an implementation where a single fractional pointer is used both for read and write operations. On…

Three-dimensional integration technologies such as flip-chip bonding are a key prerequisite to realize large-scale superconducting quantum processors. Modular architectures, in which circuit elements are spread over multiple chips, can…

With the rapid advent of generative models, efficiently deploying these models on specialized hardware has become critical. Tensor Processing Units (TPUs) are designed to accelerate AI workloads, but their high power consumption…

Convolutional Neural Networks (CNNs) demonstrate excellent performance in various applications but have high computational complexity. Quantization is applied to reduce the latency and storage cost of CNNs. Among the quantization methods,…

Frequency multipliers, a class of essential electronic components, play a pivotal role in contemporary signal processing and communication systems. They serve as crucial building blocks for generating high-frequency signals by multiplying…

Advancing complementary metal-oxide-semiconductor (CMOS) technology into the sub-1-nm angstr\"om-scale technology nodes is expected to involve alternative semiconductor channel materials, as silicon transistors encounter severe performance…

This paper presents an approximate signed multiplier architecture that incorporates a sign-focused compressor, specifically designed for edge detection applications in machine learning and signal processing. The multiplier incorporates two…

Adder cells using Gate Diffusion Technique (GDI) & PTL-GDI technique are described in this paper. GDI technique allows reducing power consumption, propagation delay and low PDP (power delay product) whereas Pass Transistor Logic (PTL)…

Memristor has been identified as the fourth fundamental circuit element by Dr. Leon Chua in 1971 and since then it has gathered a lot of interest because of its non-volatility and are considered as a viable solution to the beyond CMOS era…

In this paper, we aim to design highly energy efficient end-to-end communication for millimeter wave multiple-input multiple-output systems. This is done by jointly optimizing the digital-to-analog converter (DAC)/analog-to-digital…

Over the past few years, significant growth has been observed in using MEMS based passive components in the RF microelectronics domain, especially in transceiver components. This is due to some excellent properties of the MEMS devices like…

A method for increasing efficiency of radio frequency (RF) amplifier employing laterally diffused metal oxide semiconductor (LDMOS) transistors coupled to an RF exciter depending on the emission mode of modulated RF input signals generated…

Inference efficiency is the predominant consideration in designing deep learning accelerators. Previous work mainly focuses on skipping zero values to deal with remarkable ineffectual computation, while zero bits in non-zero values, as…

In recent years, reversible logic has emerged as a promising computing paradigm having application in low power CMOS, quantum computing, nanotechnology, and optical computing. The classical set of gates such as AND, OR, and EXOR are not…

A maskless post-processing technique for CMOS chips is developed that enables the fabrication of RF MEMS parallel-plate capacitors with a high quality factor and a very compact size. Simulations and measured results are presented for…

Increase in image resolution require the ability of image sensors to pack an increased number of circuit components in a given area. On the the other hand a high speed processing of signals from the sensors require the ability of pixel to…

Function approximation from input and output data is one of the most investigated problems in signal processing. This problem has been tackled with various signal processing and machine learning methods. Although tensors have a rich history…

Quantum modular adders are one of the most fundamental yet versatile quantum computation operations. They help implement functions of higher complexity, such as subtraction and multiplication, which are used in applications such as quantum…