In-memory computing is an emerging computing paradigm that overcomes the limitations of
exiting Von-Neumann computing architectures such as the memory-wall bottleneck. In such …

The increasing amount of data and the growing complexity of problems have resulted in an
ever-growing reliance on cloud computing. However, many applications, most notably in …

We propose an In-Memory Computing (IMC) scheme to implement Fast Fourier Transform
(FFT) for noise signal processing using flash memory. By taking advantage of the algorithms …

High resolution Fast Fourier Transform (FFT) is important for various applications while
increased memory access and parallelism requirement limits the traditional hardware. In this …

The bottleneck between the processor and memory is the most significant barrier to the
ongoing development of efficient processing systems. Therefore, a research effort begun to …

Traditional convolutional neural network (CNN) architectures suffer from two bottlenecks:
computational complexity and memory access cost. In this study, an efficient in-memory …

Earables such as earphones [15, 16, 73], hearing aids [28], and smart glasses [2, 14] are
poised to be a prominent programmable computing platform in the future. In this paper, we …

Processing in memory (PIM) is a new computing paradigm that stores the function values of
some input modes in a lookup table (LUT) and retrieves their values when similar input …

In order to deal with increasingly complex computing problems, an In-memory-based
computation system was proposed to replace the traditional Von-Neumann architectures. In …

There is an emerging requirement for performing data-intensive parallel computations, eg,
machine-learning inference, locally on batteryless sensors. These devices are resource …