Neurostream: Scalable and Energy Efficient Deep Learning with Smart Memory Cubes

  title={Neurostream: Scalable and Energy Efficient Deep Learning with Smart Memory Cubes},
  author={Erfan Azarkhish and Davide Rossi and Igor Loi and Luca Benini},
  journal={IEEE Transactions on Parallel and Distributed Systems},
High-performance computing systems are moving towards 2.5D and 3D memory hierarchies, based on High Bandwidth Memory (HBM) and Hybrid Memory Cube (HMC) to mitigate the main memory bottlenecks. This trend is also creating new opportunities to revisit near-memory computation. In this paper, we propose a flexible processor-in-memory (PIM) solution for scalable and energy-efficient execution of deep convolutional networks (ConvNets), one of the fastest-growing workloads for servers and high-end… CONTINUE READING
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