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An Asynchronous Multi-core Accelerator for SNN inference
In this paper, we propose an asynchronous architecture for Spiking Neural Networks (SNNs) that eliminates the need for inter-core synchronization, thus enhancing speed and energy efficiency.
Optimizing Large Model Training through Overlapped Activation Recomputation
Our comprehensive evaluation using GPT models with 1. 3B-20B parameters shows that both OPT and HEU outperform the state-of-the-art recomputation approaches (e. g., Megatron-LM and Checkmake) by 1. 02-1. 53x.
A Comprehensive Survey of Dynamic Graph Neural Networks: Models, Frameworks, Benchmarks, Experiments and Challenges
From the analysis and evaluation results, we identify key challenges and offer principles for future research to enhance the design of models and frameworks in the dynamic GNNs field.
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