Genetic programming evolves heterogeneous layer-specific scalar functions to approximate layer normalization in pre-trained ViTs, capturing 91.6% variance versus 70.2% for uniform baselines and recovering 84.25% ImageNet Top-1 accuracy after 20 epochs of adaptation.
Chen, Phil C
5 Pith papers cite this work. Polarity classification is still indexing.
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CLIPGen is a framework for automated generation of chiplet interconnect IP with PPA estimates to support 2.5D SiP architecture exploration.
A ReRAM-on-logic stacked chip delivers 14.08-135.69 tokens/s LLM inference with block-clustered compression and adaptive parallel speculative decoding, yielding 4.46-7.17x speedup over standard methods.
Digital twin ecosystem for BLE PHY allows validation of crystal-free motes, achieving commercial BLE communication and -82 dBm receiver sensitivity.
The paper reviews energy-aware computing literature and constructs a taxonomy organized by hardware/software aspects, measurement, optimizations, scheduling, scaling, consolidation, federated learning, and cooling.
citing papers explorer
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Evolving Layer-Specific Scalar Functions for Hardware-Aware Transformer Adaptation
Genetic programming evolves heterogeneous layer-specific scalar functions to approximate layer normalization in pre-trained ViTs, capturing 91.6% variance versus 70.2% for uniform baselines and recovering 84.25% ImageNet Top-1 accuracy after 20 epochs of adaptation.
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CLIPGen: A Chiplet Link IP Modeling and Generation Framework for 2.5D Architecture Exploration
CLIPGen is a framework for automated generation of chiplet interconnect IP with PPA estimates to support 2.5D SiP architecture exploration.
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31.1 A 14.08-to-135.69Token/s ReRAM-on-Logic Stacked Outlier-Free Large-Language-Model Accelerator with Block-Clustered Weight-Compression and Adaptive Parallel-Speculative-Decoding
A ReRAM-on-logic stacked chip delivers 14.08-135.69 tokens/s LLM inference with block-clustered compression and adaptive parallel speculative decoding, yielding 4.46-7.17x speedup over standard methods.
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A Digital Twin Platform Enabling Monolithic Crystal-Free Bluetooth Low Energy Single-Chip Sensor Motes
Digital twin ecosystem for BLE PHY allows validation of crystal-free motes, achieving commercial BLE communication and -82 dBm receiver sensitivity.
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Energy-Aware Computing in the Year 2026
The paper reviews energy-aware computing literature and constructs a taxonomy organized by hardware/software aspects, measurement, optimizations, scheduling, scaling, consolidation, federated learning, and cooling.