はじめに こんにちは、TC3 AIチームの@mumeco_mlです！弊社は2022/10からGCP Cloud Partnerとなっておりまして、現在GCP(Google Cloud Platform)のプロジェクトでの活用をより促進しております。今回は、このGCPの機能の1つであるCompute Engineを利用したAI開発環境の作り方をご紹介いたします。GCPのVMで開発環境を作る場合、大きく分けて事前にML用に用意された環境を利用する方法と、Dockerを使ってOS環境等も含めて作る方法があると思いますが、今回は前者を説明します。需要があれば、後者の解説も作ろうと思います。 クラウド開発環境の利点・欠点 利点 高額なGPUをオンデマンドで効率的に活用できる ローカルマシンの動作が重くならない 任意のマシンスペックを利用できる 欠点 使用時間に応じて課金される 実際に開発するまでに環
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cudaとgcpに関するmasterqのブックマーク (1)
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masterq 2024/07/02
"このOSでおすすめなのがDeep Learning用に事前に設定されたDeep Learning on Linuxです。このOSを選ぶことで、煩雑なCUDAのインストールなどを簡単に済ますことが可能です。"- gcp
- nvidia
- cuda
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- linux
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