CN113228056A - 运行时硬件模拟仿真方法、装置、设备及存储介质 - Google Patents
运行时硬件模拟仿真方法、装置、设备及存储介质 Download PDFInfo
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Abstract
适用于人工智能领域，提供一种运行时硬件模拟仿真方法、装置、计算机设备及存储介质，其中，所述方法包括：获取神经网络结构图与神经网络参数(S101)；根据神经网络结构图模拟构建对应的神经网络(S102)；获取待仿真数据，并对待仿真数据按量化信息进行量化，得到仿真输入数据(S103)，仿真输入数据与神经网络参数为同一硬件数据类型；将神经网络参数与仿真输入数据输入到神经网络进行卷积计算，得到卷积结果(S104)；基于卷积结果，得到仿真结果进行输出(S105)。由于将待仿真数据量化为与神经网络参数相同的硬件数据类型，在使用软件仿真时，使得仿真计算更贴近硬件计算的结果，且硬件数据类型的数据计算量小于浮点类型的计算量，还可以提高神经网络仿真的计算速度。
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PCT国内申请，说明书已公开。
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- PCT国内申请，权利要求书已公开。
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| PCT/CN2019/110840 WO2021068249A1 (zh) | 2019-10-12 | 2019-10-12 | 运行时硬件模拟仿真方法、装置、设备及存储介质 |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114004352A (zh) * | 2021-12-31 | 2022-02-01 | 杭州雄迈集成电路技术股份有限公司 | 一种仿真实现方法、神经网络编译器以及计算机可读存储介质 |
| CN115656747A (zh) * | 2022-12-26 | 2023-01-31 | 南方电网数字电网研究院有限公司 | 基于异构数据的变压器缺陷诊断方法、装置和计算机设备 |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109002881A (zh) * | 2018-06-28 | 2018-12-14 | 郑州云海信息技术有限公司 | 基于fpga的深度神经网络的定点化计算方法及装置 |
| CN109284761A (zh) * | 2018-09-04 | 2019-01-29 | 苏州科达科技股份有限公司 | 一种图像特征提取方法、装置、设备及可读存储介质 |
| EP3438890A1 (en) * | 2017-08-04 | 2019-02-06 | Samsung Electronics Co., Ltd. | Method and apparatus for generating fixed-point quantized neural network |
| CN109753903A (zh) * | 2019-02-27 | 2019-05-14 | 北航（四川）西部国际创新港科技有限公司 | 一种基于深度学习的无人机检测方法 |
| CN110245741A (zh) * | 2018-03-09 | 2019-09-17 | 佳能株式会社 | 多层神经网络模型的优化和应用方法、装置及存储介质 |
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2019
- 2019-10-12 WO PCT/CN2019/110840 patent/WO2021068249A1/zh active Application Filing
- 2019-10-12 CN CN201980067042.8A patent/CN113228056B/zh active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP3438890A1 (en) * | 2017-08-04 | 2019-02-06 | Samsung Electronics Co., Ltd. | Method and apparatus for generating fixed-point quantized neural network |
| CN110245741A (zh) * | 2018-03-09 | 2019-09-17 | 佳能株式会社 | 多层神经网络模型的优化和应用方法、装置及存储介质 |
| CN109002881A (zh) * | 2018-06-28 | 2018-12-14 | 郑州云海信息技术有限公司 | 基于fpga的深度神经网络的定点化计算方法及装置 |
| CN109284761A (zh) * | 2018-09-04 | 2019-01-29 | 苏州科达科技股份有限公司 | 一种图像特征提取方法、装置、设备及可读存储介质 |
| CN109753903A (zh) * | 2019-02-27 | 2019-05-14 | 北航（四川）西部国际创新港科技有限公司 | 一种基于深度学习的无人机检测方法 |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114004352A (zh) * | 2021-12-31 | 2022-02-01 | 杭州雄迈集成电路技术股份有限公司 | 一种仿真实现方法、神经网络编译器以及计算机可读存储介质 |
| CN114676830A (zh) * | 2021-12-31 | 2022-06-28 | 杭州雄迈集成电路技术股份有限公司 | 一种基于神经网络编译器的仿真实现方法 |
| CN114707650A (zh) * | 2021-12-31 | 2022-07-05 | 杭州雄迈集成电路技术股份有限公司 | 一种提高仿真效率的仿真实现方法 |
| CN115656747A (zh) * | 2022-12-26 | 2023-01-31 | 南方电网数字电网研究院有限公司 | 基于异构数据的变压器缺陷诊断方法、装置和计算机设备 |
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| WO2021068249A1 (zh) | 2021-04-15 |
| CN113228056B (zh) | 2023-12-22 |
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