RACE-AIMC: Selective Inference for Heterogeneous Analog In-Memory Accelerators at the Edge
cs.ET, cs.AR, cs.LG
Submitted: 2026-09-02
Updated: 2026-09-02
Comments: 6 pages, 2 figures, 3 tables
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Terminology
Sources
- XBTorch: A Unified Framework for Modeling and Co-Design of Crossbar-Based Deep Learning Accelerators
- Mitigating Edge Machine Learning Inference Bottlenecks: An Empirical Study on Accelerating Google Edge Models
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