January 2017
Beginner to intermediate
312 pages
7h 3m
Korean
Content preview from 밑바닥부터 시작하는 딥러닝
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276
밑바닥부터 시작하는 딥러닝
8.3.3
분산 학습
GPU
로 딥러닝 연산을 꽤 가속할 수 있지만, 그래도 심층 신경망에서는 학습에 며칠 혹은 몇
주가 걸리기도 합니다. 그리고 지금까지 살펴본 것처럼 딥러닝은 많은 시행착오를 동반합니다.
뛰어난 신경망을 만들려면 시험을 수없이 반복해야 하고, 그러려면
1
회 학습에 걸리는 시간을
최대한 단축하고 싶다는 요구가 필연적으로 생겨납니다. 그래서 딥러닝 학습을 수평 확장
scale
out
하자는 아이디어(즉, ‘분산 학습’ )가 중요해지는 것입니다.
딥러닝 계산을 더욱 고속화하고자 다수의
GPU
와 기기로 계산을 분산하기도 합니다. 최근에
는 다수의
GPU
와 컴퓨터를 이용한 분산 학습을 지원한 딥러닝 프레임워크들이 나타나고 있
습니다. 그중에서도 구글의 텐서플로와 마이크로소프트의
CNTK
Computational
Network
Toolkit
는 분산
학습에 역점을 두고 개발하고 있습니다. 거대한 데이터센터의 저지연·고처리량
low
latency
,
high
throughput
네트워크 위에서 이들 프레임워크가 수행하는 분산 학습은 놀라운 효과를 보이고 있습
니다.
분산 학습까지 더하면 어느 수준까지 고속화할 수 있을까요? [그림
8
-
16
]은 텐서플로로 알아
본 분산 학습의 효과입니다.
그림
8-16
텐서플로의 분산 학습 성능
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O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.