39 citations · 47 across the 3 of their papers we have counts for
5 papers
Compiling ONNX Neural Network Models Using MLIR
Tian Jin, Gheorghe-Teodor Bercea, Tung D. Le +8
Deep neural network models are becoming increasingly popular and have been used in various tasks such as computer vision, speech recognition, and natural language processing. Machi…
Profiling based Out-of-core Hybrid Method for Large Neural Networks
Yuki Ito, Haruki Imai, Tung Le Duc +4
GPUs are widely used to accelerate deep learning with NNs (NNs). On the other hand, since GPU memory capacity is limited, it is difficult to implement efficient programs that compu…
Fast and Accurate 3D Medical Image Segmentation with Data-swapping Method
Haruki Imai, Samuel Matzek, Tung D. Le +2
Deep neural network models used for medical image segmentation are large because they are trained with high-resolution three-dimensional (3D) images. Graphics processing units (GPU…
TFLMS: Large Model Support in TensorFlow by Graph Rewriting
Tung D. Le, Haruki Imai, Yasushi Negishi +1
While accelerators such as GPUs have limited memory, deep neural networks are becoming larger and will not fit with the memory limitation of accelerators for training. We propose a…
Profile-guided memory optimization for deep neural networks
Taro Sekiyama, Takashi Imamichi, Haruki Imai +1
Recent years have seen deep neural networks (DNNs) becoming wider and deeper to achieve better performance in many applications of AI. Such DNNs however require huge amounts of mem…