Sparse matrices

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A 28-nm Digital Compute-in-Memory Ising Annealer With Asynchronous Random Number Generator for Traveling Salesman Problem

A 28-nm Digital Compute-in-Memory Ising Annealer With Asynchronous Random Number Generator for Traveling Salesman Problem 150 150
Author(s): Yuyao Kong, Haomei Liu, Vaidehi Garg, Shimeng Yu

Abstract:

This work presents a compact digital compute-in-memory (DCIM) Ising annealer targeting large-scale combinatorial optimization. A centroid-based weight mapping method combined with hierarchical clustering reduces the memory capacity required for traveling salesman problem (TSP) weights, enabling efficient mapping with limited on-chip storage. An asynchronous random number generator (ARNG) based on dual …

Published in: IEEE Solid-State Circuits Letters
Page(s): 1 – 4
Year of Publication: 2026
Electronic ISSN: 2573-9603
DOI: 10.1109/LSSC.2025.3639178
Publisher: IEEE

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Opal: A 16-nm Coarse-Grained Reconfigurable Array SoC for Full Sparse Machine Learning Applications

Opal: A 16-nm Coarse-Grained Reconfigurable Array SoC for Full Sparse Machine Learning Applications 150 150
Author(s): Po-Han Chen, Bo Wun Cheng, Michael Oduoza, Zhouhua Xie, Rupert Lu, Sai Gautham Ravipati, Kalhan Koul, Alex Carsello, Yuchen Mei, Mark Horowitz, Priyanka Raina

Abstract:

Sparsity has recently attracted increased attention in the machine learning (ML) community due to its potential to improve performance and energy efficiency by eliminating ineffectual computations. As ML models evolve rapidly, reconfigurable architectures, such as coarse-grained reconfigurable arrays (CGRAs), are being explored to adapt to and accelerate emerging models. Previous …

Published in: IEEE Solid-State Circuits Letters
Page(s): 293 – 296
Year of Publication: 2025
Electronic ISSN: 2573-9603
DOI: 10.1109/LSSC.2025.3613245
Publisher: IEEE

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