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20232026
most citedUsing the IBM Analog In-Memory Hardware Acceleration Kit for Neural Network Training and Inference

66 citations · 77 across the 7 of their papers we have counts for

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Showing 2025Show all

2 papers · 1 filter

cs.CL2025★ 7 cited

Chain-of-Descriptions: Improving Code LLMs for VHDL Code Generation and Summarization

Prashanth Vijayaraghavan, Apoorva Nitsure, Charles Mackin +9

Large Language Models (LLMs) have become widely used across diverse NLP tasks and domains, demonstrating their adaptability and effectiveness. In the realm of Electronic Design Aut…

cs.AR2025

Rapid yet accurate Tile-circuit and device modeling for Analog In-Memory Computing

J. Luquin, C. Mackin, S. Ambrogio +11

Analog In-Memory Compute (AIMC) can improve the energy efficiency of Deep Learning by orders of magnitude. Yet analog-domain device and circuit non-idealities -- within the analog…