arXiv: cs.AI preprintsInternational6 November 2026
CAMP: Context-Aware Mapping and Placement for LLMs on 3D-IMC Arrays
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arXiv:2611.07707v1 Announce Type: cross Abstract: Large Language Models (LLMs) incur severe memory-access overheads due to the cost of loading large weight matrices and key-value (KV) caches. Analog In-Memory Computing (AIMC) is an emerging solution that enables computation directly on static weights stored in memory, substantially reducing energy and latency. 3D-IMC further stacks memory arrays into vertical tiers, increasing capacity but revealing a new challenge: how weights are placed in memory determines which matrix-vector multiplications (MVMs) can execute concurrently, affecting latenc
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