Transformer attention mechanisms pose significant scalability challenges due to quadratic complexity in sequence length, and existing accelerators remain bottlenecked by dense arithmetic and data movement. This paper proposes CAMformer, a hardware accelerator that reinterprets attention as an associative memory operati...
Tergel Molom-Ochir, Benjamin F. Morris, Mark Horton et al.· IEEE Transactions on Circuit...· 0 citations
Edge intelligence promises responsive, private, and energy-efficient sensing without continual dependence on remote compute. This demands convolutional neural network (CNN) accelerators that deliver substantially higher throughput and energy efficiency than conventional digital pipelines while preserving high accuracy....
Mark Horton, Changwoo Park, Tergel Molom-Ochir et al.· International Symposium on L...· 0 citations
Monte Carlo tree search (MCTS) enables artificial intelligence (AI) decision-making, but requires 55-300 W on conventional processors, limiting edge deployment. In-memory computing (IMC) is energy-efficient on regular workloads but has been considered incompatible with irregular multi-phase algorithms. We introduce pha...
Tergel Molom-Ochir, Benjamin F. Morris, Yintao He et al.· arXiv.org· 0 citations
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