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- Time: 7pm Wednesdays
- Place: 106-dong 511

Day | Date | Presenter | Contents | Note |
---|---|---|---|---|

1 | Tue 6/18, 5pm | Sugil | DAC papers: Noise injection adaptation, ApproxLP, E-LSTM | |

Hyeonuk | DAC papers: 41_2, SkippyNN (SC), BitBlade, ABM | |||

2 | Wed 6/26 | Jongeun | DAC Tutorial 5 | |

3 | Fri 7/12, 1pm | Jun-gi | SOSPCS |

- https://arxiv.org/pdf/1811.07755.pdf (UGConv)
- dynamic pruning
- https://papers.nips.cc/paper/6813-runtime-neural-pruning
- https://arxiv.org/abs/1810.05331
- https://arxiv.org/abs/1805.12549
- attention mechanism paper(s)

- DAC
- 41_2.pdf Acceleration of DNN Backward Propagation by Selective Computation of Gradients
- 41_1.pdf BitBlade: Area and Energy-efficient Precision-scalable Neural Network Accelerator with Bitwise Summation
- 41_4.pdf ABM-spConv: A Novel Approach to FPGA-based Acceleration of Convolutional Neural Network Inference
- Noise Injection Adaption: End-to-End ReRAM Crossbar Non-ideal Effect Adaption for Neural Network Mapping
- ApproxLP: Approximate Multiplication with Linearization and Iterative Error Control
- How to extend it to other ranges or other types (eg, fixed-point)?

- E-LSTM: Efficient Inference of Sparse LSTM on Embedded Heterogeneous System
- SkippyNN: An Embedded Stochastic-computing Accelerator for Convolutional Neural Networks.

- SOSPCS: (TVLSI 2019 June)
- "Self-Optimizing and Self-Programming Computing Systems: A Combined Compiler, Complex Networks, and Machine Learning Approach", Xiao et al.

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Topic revision: r3 - 12 Jul 2019, JongeunLee

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