Phasor measurement units

  • No Comments

A Standalone-in-Memory Voltage Crossover-Based Assist Switching Circuit for Reliable and Efficient Process Tracking Memory Vmin Improvement in Intel 18A-RibbonFET Technology

A Standalone-in-Memory Voltage Crossover-Based Assist Switching Circuit for Reliable and Efficient Process Tracking Memory Vmin Improvement in Intel 18A-RibbonFET Technology 150 150
Author(s): Saroj Satapathy, Amlan Ghosh, John Riley, Jalal Quadri, Jaydeep Kulkarni, Feroze Merchant

Abstract:

Advanced CMOS memory requires voltage biasing assist techniques to achieve low operating voltages (Vmin), which must be deactivated at higher voltages for high electric field reliability. Centralized power management unit (PMU) control signals face timing synchronization and process tracking challenges when distributed across cores to activate assist circuits in various …

Published in: IEEE Solid-State Circuits Letters
Page(s): 37 – 40
Year of Publication: 2026
Electronic ISSN: 2573-9603
DOI: 10.1109/LSSC.2026.3652110
Publisher: IEEE

View on IEEE Xplore

  • No Comments

A Fast Transient Response Fully Integrated LDO With a Novel Resetting Oscillator Control Method

A Fast Transient Response Fully Integrated LDO With a Novel Resetting Oscillator Control Method 150 150
Author(s): Masoud Kargaran, Amir Besharati Rad, Ali Medi

Abstract:

This article introduces a novel resetting oscillator regulator (ROR) control method for low-dropout (LDO) regulators, designed to achieve fast settling times for both load and reference input steps. The proposed ROR integrates a high-speed loop that independently functions as an oscillator in a closed-loop configuration, along with a separate high-rate …

Published in: IEEE Journal of Solid-State Circuits
Page(s): 1 – 13
Year of Publication: 2025
Electronic ISSN: 1558-173X
DOI: 10.1109/JSSC.2025.3607941
Publisher: IEEE

View on IEEE Xplore

  • No Comments

MINOTAUR: A Posit-Based 0.42–0.50-TOPS/W Edge Transformer Inference and Training Accelerator

MINOTAUR: A Posit-Based 0.42–0.50-TOPS/W Edge Transformer Inference and Training Accelerator 150 150
Author(s): Kartik Prabhu, Robert M. Radway, Jeffrey Yu, Kai Bartolone, Massimo Giordano, Fabian Peddinghaus, Yonatan Urman, Win-San Khwa, Yu-Der Chih, Meng-Fan Chang, Subhasish Mitra, Priyanka Raina

Abstract:

Transformer models have revolutionized natural language processing (NLP) and enabled many new applications, but are challenging to deploy on resource-constrained edge devices due to their high computation and memory demands. We present MINOTAUR, an edge system-on-chip (SoC) for inference and fine-tuning of Transformer models with all memory on the chip. …

Published in: IEEE Journal of Solid-State Circuits
Page(s): 1311 – 1323
Year of Publication: 2025
Electronic ISSN: 1558-173X
DOI: 10.1109/JSSC.2025.3545731
Publisher: IEEE

View on IEEE Xplore

Search this website