222 citations · 279 across the 5 of their papers we have counts for
5 papers
KAPLA: Pragmatic Representation and Fast Solving of Scalable NN Accelerator Dataflow
Zhiyao Li, Mingyu Gao
Dataflow scheduling decisions are of vital importance to neural network (NN) accelerators. Recent scalable NN accelerators support a rich set of advanced dataflow techniques. The p…
Canvas: End-to-End Kernel Architecture Search in Neural Networks
Chenggang Zhao, Genghan Zhang, Ao Shen +1
The demands for higher performance and accuracy in neural networks (NNs) never end. Existing tensor compilation and Neural Architecture Search (NAS) techniques orthogonally optimiz…
RePAST: A ReRAM-based PIM Accelerator for Second-order Training of DNN
Yilong Zhao, Li Jiang, Mingyu Gao +6
The second-order training methods can converge much faster than first-order optimizers in DNN training. This is because the second-order training utilizes the inversion of the seco…
ShEF: Shielded Enclaves for Cloud FPGAs
Mark Zhao, Mingyu Gao, Christos Kozyrakis
FPGAs are now used in public clouds to accelerate a wide range of applications, including many that operate on sensitive data such as financial and medical records. We present ShEF…
Interstellar: Using Halide's Scheduling Language to Analyze DNN Accelerators
Xuan Yang, Mingyu Gao, Qiaoyi Liu +9
We show that DNN accelerator micro-architectures and their program mappings represent specific choices of loop order and hardware parallelism for computing the seven nested loops o…