Publications by Soumya Subhra Basu

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The energy e fficiency of digital architectures is tightly linked to the voltage level (Vdd) at which they operate. Aggressive voltage scaling is therefore mandatory when ultra-low power processing is required. Nonetheless, the lowest admissible Vdd is o e ...

Smart health monitoring devices, known as Wireless Body Sensor Nodes (WBSN) are transforming today's health-care landscape, shifting it from traditional hospital-based methods toward more personalized approaches. Their demand is ever-increasing in the mode ...

This paper introduces an inexact, but ultra-low power, computing architecture devoted to the embedded analysis of bio-signals. The platform operates at extremely low voltage supply levels to minimize energy consumption. In this scenario, the reliability of ...

The energy efficiency of digital architectures is tightly linked to the voltage level (Vdd) at which they operate. Aggressive voltage scaling is therefore mandatory when ultra-low power processing is required. Nonetheless, the lowest admissible Vdd is ofte ...

Energy consumption is a significant obstacle to integrate deep learning into edge devices. Two common techniques to curve it are quantization, which reduces the size of the memories (static energy) and the number of accesses (dynamic energy), and voltage s ...

This paper introduces a novel computing architecture devoted to the ultra-low power analysis of multiple bio-signals. Its structure comprises several processors interfaced with a shared acceleration resource, implemented as a Coarse Grained Reconfigurable ...

In the Internet-of-Things (IoT) era, there is an increasing trend to enable intelligent behavior in edge computing sensors. Thus, a new generation of smart wearable devices for health monitoring is being developed, able to perform complex Digital Signal Pr ...

Smart edge sensors for bio-signal monitoring must support complex signal processing routines within an extremely small energy envelope. Coarse-Grained Reconfigurable Arrays (CGRAs) are good candidates for tackling these conflicting objectives because, than ...

Wearable devices performing advanced bio-signal analysis algorithms will foster a revolution in healthcare provision of chronic cardiac diseases. In this context, energy efficiency is of paramount importance, as long-term operations must be performed withi ...

Personalized healthcare devices enable low-cost, unobtrusive and long-term acquisition of clinically-relevant biosignals. These appliances, termed Wireless Body Sensor Nodes (WBSNs), are fostering a revolution in health monitoring for patients affected by ...

Soumya Subhra Basu

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An Inexact Ultra-low Power Bio-signal Processing Architecture With Lightweight Error Recovery

Hardware/Software Co-Design and Reliability Analysis of Ultra-Low Power Biomedical Devices

Inexact-Aware Architecture Design for Ultra-Low Power Bio-Signal Analysis

An Inexact Ultra-low Power Bio-signal Processing Architecture With Lightweight Error Recovery

Impact of Memory Voltage Scaling on Accuracy and Resilience of Deep Learning Based Edge Devices

A Multi-Core Reconfigurable Architecture for Ultra-Low Power Bio-Signal Analysis

Heterogeneous and Inexact: Maximizing Power Efficiency of Edge Computing Sensors for Health Monitoring Applications

i-DPs CGRA: An Interleaved-Datapaths Reconfigurable Accelerator for Embedded Bio-signal Processing

Heterogeneous Error-Resilient Scheme for Spectral Analysis in Ultra-Low Power Wearable Electrocardiogram Devices

HEAL-WEAR: an Ultra-Low Power Heterogeneous System for Bio-Signal Analysis