neural networks

RecShard: Statistical Feature-Based Memory Optimization for Industry-Scale Neural Recommendation
We propose RecShard, a fine-grained embedding table (EMB) partitioning and placement technique for deep learning recommendation models …
Geet Sethi, Bilge Acun, Niket Agarwal, Christos Kozyrakis, Caroline Trippel, Carole-Jean Wu
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TANGRAM: Optimized Coarse-Grained Dataflow for Scalable NN Accelerators
The use of increasingly larger and more complex neural networks (NNs) makes it critical to scale the capabilities and efficiency of NN …
Mingyu Gao, Xuan Yang, Jing Pu, Mark Horowitz, Christos Kozyrakis
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TETRIS: Scalable and Efficient Neural Network Acceleration with 3D Memory
The high accuracy of deep neural networks (NNs) has led to the development of NN accelerators that improve performance by two orders of …
Mingyu Gao, Jing Pu, Xuan Yang, Mark Horowitz, Christos Kozyrakis
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