TensorShader : Deep Learning Framework for High-Dimensional Neural Networks

DOI

Bibliographic Information

Other Title
  • TensorShader : 高次元ニューラルネットワーク深層学習フレームワーク

Abstract

<p>In recent years, research on high-dimensional neural networks based on hyper-complex number such as complex numbers and quaternions has been advanced. On the other hand, there are still few deep learning frameworks that can handle high-dimensional neural networks on GPUs, which hinders experiments. In this study, I developed a deep learning framework based on complex numbers, quaternions, and 3D vectors. In this framework, a dedicated CUDA kernel was implemented to eliminate the increase in the temporary calculation area, which is a problem when implementing a high-dimensional neural network, and FP32-FP32 arithmetic was used to avoid accumulation of rounding errors. These results show that my framework is superior to existing frameworks in reducing space complexity and calculation errors.</p>

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Details 詳細情報について

  • CRID
    1390003825189220992
  • NII Article ID
    130007856785
  • DOI
    10.11517/pjsai.jsai2020.0_1j5gs201
  • Text Lang
    ja
  • Data Source
    • JaLC
    • CiNii Articles
  • Abstract License Flag
    Disallowed

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