most citedTransformer-based Machine Learning for Fast SAT Solvers and Logic Synthesis

4 citations · 11 across the 5 of their papers we have counts for

collaborators

5 papers

physics.app-ph20221 cited

CMOS-Compatible Ising Machines built using Bistable Latches Coupled through Ferroelectric Transistor Arrays

Antik Mallick, Zijian Zhao, Mohammad Khairul Bashar +8

Realizing compact and scalable Ising machines that are compatible with CMOS-process technology is crucial to the effectiveness and practicality of using such hardware platforms for…

eess.SP20222 cited

Seeker: Synergizing Mobile and Energy Harvesting Wearable Sensors for Human Activity Recognition

Cyan Subhra Mishra, Jack Sampson, Mahmut Taylan Kandemir +1

There is an increasing demand for intelligent processing on emerging ultra-low-power internet of things (IoT) devices, and recent works have shown substantial efficiency boosts by…

cs.ET20212 cited

An Oscillator-based MaxSAT solver

Mohammad Khairul Bashar, Jaykumar Vaidya, Antik Mallick +8

The quest to solve hard combinatorial optimization problems efficiently -- still a longstanding challenge for traditional digital computers -- has inspired the exploration of many…

cs.LG20212 cited

Exploiting Activation based Gradient Output Sparsity to Accelerate Backpropagation in CNNs

Anup Sarma, Sonali Singh, Huaipan Jiang +5

Machine/deep-learning (ML/DL) based techniques are emerging as a driving force behind many cutting-edge technologies, achieving high accuracy on computer vision workloads such as i…

cs.NE20214 cited

Transformer-based Machine Learning for Fast SAT Solvers and Logic Synthesis

Feng Shi, Chonghan Lee, Mohammad Khairul Bashar +3

CNF-based SAT and MaxSAT solvers are central to logic synthesis and verification systems. The increasing popularity of these constraint problems in electronic design automation enc…