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cs.AR2024
Efficient Sparse Processing-in-Memory Architecture (ESPIM) for Machine Learning Inference
Mingxuan He, Mithuna Thottethodi, T. N. Vijaykumar
Emerging machine learning (ML) models (e.g., transformers) involve memory pin bandwidth-bound matrix-vector (MV) computation in inference. By avoiding pin crossings, processing in…
cs.AR2024
QED: Scalable Verification of Hardware Memory Consistency
Gokulan Ravi, Xiaokang Qiu, Mithuna Thottethodi +1
Memory consistency model (MCM) issues in out-of-order-issue microprocessor-based shared-memory systems are notoriously non-intuitive and a source of hardware design bugs. Prior har…