title: ÐÐµÑÐ¾Ð´Ñ Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ Ð¸ÑÐ¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°Ð½Ð¸Ñ ÑÐ¿ÐµÑÐ¸Ð°Ð»Ð¸Ð·Ð¸ÑÐ¾Ð²Ð°Ð½Ð½ÑÑ ÑÑÐºÐ¾ÑÐ¸ÑÐµÐ»ÐµÐ¹ Ð²ÑÑÐ¸ÑÐ»ÐµÐ½Ð¸Ð¹
title: Ð²ÑÐ¿ÑÑÐºÐ½Ð°Ñ ÐºÐ²Ð°Ð»Ð¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¾Ð½Ð½Ð°Ñ ÑÐ°Ð±Ð¾ÑÐ° Ð¼Ð°Ð³Ð¸ÑÑÑÐ°
titleType: Subtitle
title: Methods of machine learning using specialized gas pedals of calculations
Creators: name: Ð§ÑÐ½Ñ ÐÐ¸Ð½Ñ
Publisher: name: Ð¡Ð°Ð½ÐºÑ-ÐÐµÑÐµÑÐ±ÑÑÐ³ÑÐºÐ¸Ð¹ Ð¿Ð¾Ð»Ð¸ÑÐµÑÐ½Ð¸ÑÐµÑÐºÐ¸Ð¹ ÑÐ½Ð¸Ð²ÐµÑÑÐ¸ÑÐµÑ ÐÐµÑÑÐ° ÐÐµÐ»Ð¸ÐºÐ¾Ð³Ð¾
Year: 2023
Subjects: ÑÐ¿ÐµÑÐ¸Ð°Ð»Ð¸Ð·Ð¸ÑÐ¾Ð²Ð°Ð½Ð½ÑÐµ ÑÑÐºÐ¾ÑÐ¸ÑÐµÐ»Ð¸ Ð²ÑÑÐ¸ÑÐ»ÐµÐ½Ð¸Ð¹
Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ðµ Ð¾Ð±ÑÑÐµÐ½Ð¸Ðµ
Ð³ÑÐ°ÑÐ¸ÑÐµÑÐºÐ¸Ðµ Ð¸ ÑÐ°Ð±Ð»Ð¸ÑÐ½ÑÐµ (ÑÐµÐºÑÑÐ¾Ð²ÑÐµ) Ð´Ð°Ð½Ð½ÑÐµ
ÑÐ²ÐµÑÑÐ¾ÑÐ½Ð¾Ðµ ÑÐµÑÐ¸
performance of built-up gas pedals
machine learning
graphical and tabular (textual) data
convolutional network

description: Ð¦ÐµÐ»Ñ BKP: ÐÐ·ÑÑÐ¸ÑÐµ ÑÐ¿ÐµÑÐ¸Ð°Ð»Ð¸Ð·Ð¸ÑÐ¾Ð²Ð°Ð½Ð½Ñe ÑÑÐºÐ¾ÑÐ¸ÑÐµÐ»Ð¸ Ð²ÑÑÐ¸ÑÐ»ÐµÐ½Ð¸Ð¹ ÑÐµÑÐµÐ½Ð¸Ñ Ð·Ð°Ð´Ð°Ñ Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ Ð¿ÑÐ¸ Ð¾Ð±ÑÐ°Ð±Ð¾ÑÐºÐµ Ð³ÑÐ°ÑÐ¸ÑÐµÑÐºÐ¸Ñ Ð¸ ÑÐ°Ð±Ð»Ð¸ÑÐ½ÑÑ (ÑÐµÐºÑÑÐ¾Ð²ÑÑ) Ð´Ð°Ð½Ð½ÑÑ. ÐÐµÑÐ¾Ð´Ñ Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ñ: ÐÐ¾Ð´ÐµÐ»Ñ Ð¿ÐµÑÐµÐ²Ð¾Ð´Ð° Ð¸Ð·Ð¾Ð±ÑÐ°Ð¶ÐµÐ½Ð¸Ð¹ Ð´Ð»Ñ ÐºÐ¸ÑÐ°Ð¹ÑÐºÐ¸Ñ Ð¸ÐµÑÐ¾Ð³Ð»Ð¸ÑÐ¾Ð² Ð½Ð° Ð¾ÑÐ½Ð¾Ð²Ðµ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½Ð¾Ð¹ ÑÐµÑÐ¸, ÑÑÐºÐ¾ÑÐ¸ÑÐµÐ»ÑÐ½Ð°Ñ ÐºÐ°ÑÑÐ° Ð¸ gpu ÑÑÑÐ°Ð½Ð¾Ð²Ð»ÐµÐ½Ð° Ð² ÐºÐ¾Ð¼Ð¿ÑÑÑÐµÑ, ÑÐµÑÑÐ¸ÑÐ¾Ð²Ð°Ð½Ð¸Ðµ Ð¿ÑÐ¾Ð¸Ð·Ð²Ð¾Ð´Ð¸ÑÐµÐ»ÑÐ½Ð¾ÑÑÐ¸. ÐÑÐ½Ð¾Ð²Ð½ÑÐµ ÑÐµÐ·ÑÐ»ÑÑÐ°ÑÑ ÑÐ°Ð±Ð¾ÑÑ: ÐÐ°ÑÑÑÐ¾Ð¹ÐºÐ° ÐºÐ¾Ð¼Ð¿ÑÑÑÐµÑÐ°-ÑÑÐºÐ¾ÑÐ¸ÑÐµÐ»Ñ Cambricon AI Ñ Ð¿Ð¾Ð¼Ð¾ÑÑÑ PyTorch Ð¸ Tensorflow Ð² Docker; ÐÐ¿Ð¿Ð°ÑÐ°ÑÐ½Ð°Ñ Ð¿Ð¾Ð´Ð´ÐµÑÐ¶ÐºÐ° Ð·Ð°Ð´Ð°Ñ Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ Ð´Ð»Ñ ÑÐµÐ°Ð»Ð¸Ð·Ð°ÑÐ¸Ð¸ Ð¿ÐµÑÐµÐ²Ð¾Ð´Ð° Ð¸Ð·Ð¾Ð±ÑÐ°Ð¶ÐµÐ½Ð¸Ð¹ ÐºÐ¸ÑÐ°Ð¹ÑÐºÐ¸Ñ Ð¸ÐµÑÐ¾Ð³Ð»Ð¸ÑÐ¾Ð²; ÐÑÐµÐ½ÐºÐ° Ð²ÑÑÐ¸ÑÐ»Ð¸ÑÐµÐ»ÑÐ½Ð¾Ð¹ Ð¼Ð¾ÑÐ½Ð¾ÑÑÐ¸ Ð¸ Ð¾Ð¿ÑÐ¸Ð¼Ð¸Ð·Ð°ÑÐ¸Ð¸ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½Ð¾Ð¹ ÑÐµÑÐ¸ ÑÑÐºÐ¾ÑÐ¸ÑÐµÐ»Ñ Cambricon AI Ð¿Ð¾ ÑÑÐ°Ð½Ð´Ð°ÑÑÑ Ð²ÑÑÐ¸ÑÐ»Ð¸ÑÐµÐ»ÑÐ½Ð¾Ð¹ Ð¼Ð¾ÑÐ½Ð¾ÑÑÐ¸ NVIDIA GPU Ð½Ð° Ð¾ÑÐ½Ð¾Ð²Ðµ Ð¾Ð´Ð¸Ð½Ð°ÐºÐ¾Ð²ÑÑ Ð²ÑÐ¾Ð´Ð½ÑÑ Ð´Ð°Ð½Ð½ÑÑ Ð¸ Ð¾Ð±ÑÐ°Ð±Ð¾ÑÐºÐ¸, ÑÑÑÑÐºÑÑÑÑ Ð¼Ð¾Ð´ÐµÐ»Ð¸ Ð¸ Ð¼ÐµÑÐ¾Ð´Ð° Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ. ÐÐ±Ð»Ð°ÑÑÑ Ð¿ÑÐ¸Ð¼ÐµÐ½ÐµÐ½Ð¸Ñ ÑÐµÐ·ÑÐ»ÑÑÐ°ÑÐ¾Ð² ÐÐÐ : ÐÐ½Ð°Ð»Ð¸Ð· Ð¿ÑÐ¾Ð¸Ð·Ð²Ð¾Ð´Ð¸ÑÐµÐ»ÑÐ½Ð¾ÑÑÐ¸ Ð°Ð¿Ð¿Ð°ÑÐ°ÑÐ½ÑÑ ÑÐµÑÑÑÑÐ¾Ð² Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ ÑÑÐ¿ÐµÑÐºÐ¾Ð¼Ð¿ÑÑÑÐµÑÐ¾Ð² Ð¸ Ð´Ð¾Ð¼ÐµÐ½Ð¾Ð² Ð°Ð¿Ð¿Ð°ÑÐ°ÑÐ½Ð¾Ð³Ð¾ ÑÑÐºÐ¾ÑÐµÐ½Ð¸Ñ Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ. ÐÑÐ²Ð¾Ð´Ñ: Ð¡Ð¿ÐµÑÐ¸Ð°Ð»Ð¸Ð·Ð¸ÑÐ¾Ð²Ð°Ð½Ð½ÑÐµ Ð²ÑÑÐ¸ÑÐ»Ð¸ÑÐµÐ»ÑÐ½ÑÐµ ÑÑÐºÐ¾ÑÐ¸ÑÐµÐ»Ð¸ Ñ Ð¾Ð¿ÑÐ¸Ð¼Ð¸Ð·Ð¸ÑÐ¾Ð²Ð°Ð½Ð½Ð¾Ð¹ Ð°Ð¿Ð¿Ð°ÑÐ°ÑÐ½Ð¾Ð¹ Ð°ÑÑÐ¸ÑÐµÐºÑÑÑÐ¾Ð¹ Ð¸ ÑÐ¾ ÑÐ¿ÐµÑÐ¸Ð°Ð»Ð¸Ð·Ð¸ÑÐ¾Ð²Ð°Ð½Ð½ÑÐ¼Ð¸ Ð¸Ð½ÑÑÑÑÐ¼ÐµÐ½ÑÐ°Ð¼Ð¸ Ð¸ Ð±Ð¸Ð±Ð»Ð¸Ð¾ÑÐµÐºÐ°Ð¼Ð¸ Ð´Ð»Ñ Ð¿ÑÐ¾Ð³ÑÐ°Ð¼Ð¼Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ñ. ÐÐ½Ð¸ Ð¿Ð¾Ð·Ð²Ð¾Ð»ÑÑÑ Ð¾Ð¿ÑÐ¸Ð¼Ð¸Ð·Ð¸ÑÐ¾Ð²Ð°ÑÑ Ð¸ ÑÐ¿ÑÐ¾ÑÑÐ¸ÑÑ Ð¿ÑÐ¾Ð³ÑÐ°Ð¼Ð¼Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ðµ Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ Ð¸ Ð¿Ð¾Ð²ÑÑÐ¸ÑÑ ÑÑÑÐµÐºÑÐ¸Ð²Ð½Ð¾ÑÑÑ Ð¾Ð±ÑÐ°Ð±Ð¾ÑÐºÐ¸ Ð´Ð°Ð½Ð½ÑÑ.
description: The aim of BKP: Study specialized computational gas pedals for solving problems of machine learning in the processing of graphical and tabular (textual) data. Research Methods: Image translation model for Chinese characters based on neural network, gas pedal card and gpu installed in computer, performance testing. Main results of work: Setting up the Cambricon AI gas pedal computer with PyTorch and Tensorflow in Docker; Hardware support for machine learning tasks to implement image translation of Chinese characters; Evaluation of computing power and optimization of the Cambricon AI gas pedal neural network by NVIDIA GPU computing power standard based on the same input data and processing, model structure and training method. Scope of the results of WCS: Performance analysis of supercomputer machine learning hardware resources and machine learning hardware acceleration domains. Conclusions: Specialized computing gas pedals with optimized hardware architecture and with specialized programming tools and libraries. They optimize and simplify machine learning programming and improve data processing efficiency.