3 papers
cs.AR2026
Space-CIM: Enabling Compute-In-Memory Accelerators for Thermally-Constrained Space Platforms
Sohan Salahuddin Mugdho, Md. Shahedul Hasan, Cheng Wang
The rapid growth in compute demand from artificial intelligence (AI) has driven a massive surge in data center construction, precipitating an energy and sustainability crisis. Moti…
cs.AR2026
CRAM-ER: Error-Resilient Spintronic Computational Random Access Memory for Scalable In-Memory Computation
Sohan Salahuddin Mugdho, Md. Shahedul Hasan, Brahmdutta Dixit +3
Deep neural networks (DNNs) have achieved state-of-the-art performance across diverse domains. However, typical Von Neumann compute paradigms face severe memory bottlenecks. Emergi…
cs.LG2025
Ultra-Efficient Decoding for End-to-End Neural Compression and Reconstruction
Ethan G. Rogers, Cheng Wang
Image compression and reconstruction are crucial for various digital applications. While contemporary neural compression methods achieve impressive compression rates, the adoption…