3 papers
cs.DC2025
From GPUs to RRAMs: Distributed In-Memory Primal-Dual Hybrid Gradient Method for Solving Large-Scale Linear Optimization Problem
Huynh Q. N. Vo, Md Tawsif Rahman Chowdhury, Paritosh Ramanan +4
The exponential growth of computational workloads is surpassing the capabilities of conventional architectures, which are constrained by fundamental limits. In-memory computing (IM…
physics.app-ph2025
Atomic-Scale Insights into the Switching Mechanisms of RRAM Devices
Md Tawsif Rahman Chowdhury, Alireza Moazzeni, Gozde Tutuncuoglu
The growing energy demands of information and communication technologies, driven by data-intensive computing and the von Neumann bottleneck, underscore the need for energy-efficien…
cs.DC2025
Harnessing the Full Potential of RRAMs through Scalable and Distributed In-Memory Computing with Integrated Error Correction
Huynh Q. N. Vo, Md Tawsif Rahman Chowdhury, Paritosh Ramanan +2
Exponential growth in global computing demand is exacerbated due to the higher-energy requirements of conventional architectures, primarily due to energy-intensive data movement. I…