5 citations · 5 across the 3 of their papers we have counts for
4 papers
Vortex: Efficient Sample-Free Dynamic Tensor Program Optimization via Hardware-aware Strategy Space Hierarchization
Yangjie Zhou, Honglin Zhu, Qian Qiu +9
Dynamic-shape deep neural networks (DNNs) are rapidly evolving, attracting attention for their ability to handle variable input sizes in real-time applications. However, existing c…
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…
Characterizing and Demystifying the Implicit Convolution Algorithm on Commercial Matrix-Multiplication Accelerators
Yangjie Zhou, Mengtian Yang, Cong Guo +5
Many of today's deep neural network accelerators, e.g., Google's TPU and NVIDIA's tensor core, are built around accelerating the general matrix multiplication (i.e., GEMM). However…
Balancing Efficiency and Flexibility for DNN Acceleration via Temporal GPU-Systolic Array Integration
Cong Guo, Yangjie Zhou, Jingwen Leng +6
The research interest in specialized hardware accelerators for deep neural networks (DNN) spikes recently owing to their superior performance and efficiency. However, today's DNN a…