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Dr. Malothu Amru, Dr. Somala Rama Kishore

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Open access Sep 2026

Frontier-Aware Compensated Truncated Multiplier for Energy-Efficient Edge-AI VLSI Datapaths

Approximate multiplication is attractive for VLSI accelerators used in image processing, digital signal processing, and edge artificial intelligence because many workloads can tolerate bounded numerical error in exchange for reduced switching and arithmetic complexity. This work presents a frontier-aware compensated tr...

Bitla Prabhakar T. Satyanarayana, Dr. Malothu Amru, Dr. Somala Rama Kishore · 0 citations
Open access Sep 2026

Precision-Reconfigurable Zero-Skipping SRAM Compute-in-Memory Architecture for Energy-Efficient Edge-AI Acceleration

The energy cost of data movement between static random-access memory (SRAM) and arithmetic units has become a critical limitation in edge artificial-intelligence accelerators. SRAM-based compute-in-memory (CIM) alleviates this bottleneck by executing multiply-and-accumulate operations near or inside the memory array. T...

Bitla Prabhakar T. Satyanarayana, Dr. Malothu Amru, Dr. Somala Rama Kishore · 0 citations

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