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cs.DC2023
DistSim: A performance model of large-scale hybrid distributed DNN training
Guandong Lu, Runzhe Chen, Yakai Wang +8
With the ever-increasing computational demand of DNN training workloads, distributed training has been widely adopted. A combination of data, model and pipeline parallelism strateg…
cs.DC2023
AdaptGear: Accelerating GNN Training via Adaptive Subgraph-Level Kernels on GPUs
Yangjie Zhou, Yaoxu Song, Jingwen Leng +7
Graph neural networks (GNNs) are powerful tools for exploring and learning from graph structures and features. As such, achieving high-performance execution for GNNs becomes crucia…
cs.DC2020★ 1 cited
DLFusion: An Auto-Tuning Compiler for Layer Fusion on Deep Neural Network Accelerator
Zihan Liu, Jingwen Leng, Quan Chen +4
Many hardware vendors have introduced specialized deep neural networks (DNN) accelerators owing to their superior performance and efficiency. As such, how to generate and optimize…