Simulating DRAM-PIM-GPU systems for LLM decode shows static power dominates efficiency accounting, channel scaling plateaus, and workload mapping gives bounded gains.
Pimba: A Processing-in-Memory Acceleration for Post- Transformer Large Language Model Serving,
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On Design Principles for Efficient Heterogeneous DRAM-PIM-GPU Systems
Simulating DRAM-PIM-GPU systems for LLM decode shows static power dominates efficiency accounting, channel scaling plateaus, and workload mapping gives bounded gains.