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Latest
MoteNN: Memory Optimization via Fine-grained Scheduling for Deep Neural Networks on Tiny Devices
FastQuery: Communication-efficient Embedding Table Query for Private LLMs inference
Alchemist: A Unified Accelerator Architecture for Cross-Scheme Fully Homomorphic Encryption
ASCEND: Accurate yet Efficient End-to-End Stochastic Computing Acceleration of Vision Transformer
Three Papers Accepted by DAC 2024
Enhancing 3D Detection Through Feature Aligned Deep Fusion
Efficient Private Inference through Network/Protocol Co-optimization
Neural Acceleration with Full Stack Optimization
A 16.38TOPS and 4.55POPS/W SRAM Computing-in-Memory Macro for Signed Operands Computation and Batch Normalization Implementation
MixCIM: A Hybrid-Cell-Based Computing-in-Memory Macro with Less-Data-Movement and Activation-Memory-Reuse for Depthwise Separable Neural Networks
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