Deep Neural Networks (DNNs) have various performance requirements and power
constraints depending on applications. To maximize the energy-efficiency of hardware …

The analysis of the vascular tree is a fundamental part of the clinical assessment of retinal
images. The diversity of blood vessel calibers and curvatures, as well as the ocular vascular …

Deep learning applications have become ubiquitous in today's era and it has led to vast
development in machine learning (ML) accelerators. Systolic arrays have been a primary …

Systolic arrays are re-gaining the attention as the heart to accelerate machine learning
workloads. This paper shows that a large design space exists at the logic level despite the …

In the rapidly advancing landscape of computing, hardware accelerator designs are pivotal
for satisfying high performance and low power demands. Systolic array (SA) architectures …

This paper presents a multiply-accumulate (MAC) unit that enables a dual-mode truncation
error compensation (TEC) scheme based on a fixed-width Booth multiplier (FWBM) for …

Systolic arrays (SAs) are re-gaining the attention as the heart to accelerate machine learning
workloads. This article shows that a large design space exists at the logic level despite the …

Bit-serial multiply-accumulate units (MACs) play a crucial role in various hardware
accelerator applications, including deep learning, image processing, and signal processing …

Temporal Convolutional Networks (TCNs) involving mono channels as input, have shown
superior performance compared to state-of-the-art sequence detection recursive networks in …

Purpose Very large-scale integration (VLSI) digital signal processing became very popular
and is predominantly used in several emerging applications. The optimal design of multirate …