AndyBlocker
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HYTE: Flexible Tiling for Sparse Accelerators via Hybrid Static-Dynamic Approaches
Published: at 16:27ISCA2025,做稀疏数据流分块的,后半截没什么精力看了,现在的工作还没做稀疏编码。
Swin Transformer: Hierarchical Vision Transformer using Shifted Windows
Published: at 17:47看看Shift-Window Attention。
SpikeVideoFormer: An Efficient Spike-Driven Video Transformer with Hamming Attention and O(T) Complexity
Published: at 16:56用汉明距离替换Attention中的点乘操作,避免出现Spike错开的情况。中间的做法比较有趣,但是实验感觉做的一般般,尤其是claim了自己有硬件实现的情况下energy计算还用的是纯算法的计算,并且FPGA的具体实现也没有透露,说了也没有说清楚。精度没有超过ANN2SNN的SOTA。重点还是需要用一些其他的操作替换掉对SNN不适应的算子。
Sparse Spiking Neural Network: Exploiting Heterogeneity in Timescales for Pruning Recurrent SNN
Published: at 19:11ICLR 2024 Spotlight, 利用Lyapunov Noise进行SNN Pruning。
Prosperity: Accelerating Spiking Neural Networks via Product Sparsity
Published: at 16:52HPCA在投的一篇SNN加速器文章,里面的“Product Sparsity”本质是减少相同内容的重复计算,和一般讨论的稀疏是两种不同的概念。
Towards Scalable GPU-Accelerated SNN Training via Temporal Fusion
Published: at 14:34意义不明,用Layer-By-Layer写了一下LIF就没别的Contribution了,发在了一个叫做ICANN的会上。工作量也太小了。
Recurrent Residual Module for Fast Inference in Videos
Published: at 15:25CVPR2018, DiffEncode + 稀疏加速,但感觉太老了。
Efficient Spatially Sparse Inference for Conditional GANs and Diffusion Models
Published: at 14:18NIPS2022上一篇比较有影响力的论文,对GAN和扩散模型做推理加速的工作,提出了Spatially Sparse Inference,仅在被编辑区域上稀疏地应用卷积滤波器,同时对未编辑区域复用缓存的特征
SlowFast Networks for Video Recognition
Updated: at 06:15Published: at 16:57多分支CNN,会不会有一些分支能学到更加相似的帧间变化?
DeltaCNN: End-to-End CNN Inference of Sparse Frame Differences in Videos
Updated: at 15:07Published: at 12:11利用CNN Layer的“线性”特征在帧之间做feature的差分,并且做了CUDA加速。和ViStream几乎一样的思路,能不能解决我们现在的问题?