GSI Technology (Nasdaq: GSIT) announced publication of a Cornell-led paper (ACM, presented at Micro ’25) validating its Compute-In-Memory Gemini-I APU. Cornell benchmarks found the APU delivered GPU-class throughput comparable to NVIDIA A6000 on RAG workloads while using over 98% less energy than a GPU and cutting retrieval processing time by up to 80% versus CPUs on datasets from 10GB to 200GB. GSI noted Gemini-II offers ~10x faster throughput and lower latency, and Plato targets further low-power edge capability.
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