{"id":3316,"date":"2020-07-01T09:30:08","date_gmt":"2020-07-01T00:30:08","guid":{"rendered":"https:\/\/www.kagoya.jp\/howto\/?p=3316"},"modified":"2023-07-19T13:28:37","modified_gmt":"2023-07-19T04:28:37","slug":"gpu-container1","status":"publish","type":"post","link":"https:\/\/www.kagoya.jp\/howto\/engineer\/hpc\/gpu-container1\/","title":{"rendered":"GPU\u30b3\u30f3\u30c6\u30ca\u3068\u306f\u4f55\u304b\uff1f\u4f55\u304c\u4fbf\u5229\u306a\u306e\u304b\uff1f\u3010\u7b2c1\u56de\uff1aGPU\u30b3\u30f3\u30c6\u30ca\u3067\u901f\u653b\u74b0\u5883\u69cb\u7bc9\u3011"},"content":{"rendered":"
\u3010\u9023\u8f09\u4f01\u753b\u3011GPU\u30b3\u30f3\u30c6\u30ca\u6d3b\u7528 \u3010\u51686\u56de\u3011<\/th> <\/tr> <\/thead>
GPU\u30b3\u30f3\u30c6\u30ca\u3068\u306f\u4f55\u304b\uff1f\u4f55\u304c\u4fbf\u5229\u306a\u306e\u304b\uff1f\u3010\u7b2c1\u56de\uff1aGPU\u30b3\u30f3\u30c6\u30ca\u3067\u901f\u653b\u74b0\u5883\u69cb\u7bc9\u3011 <\/td> <\/tr>
TensorFlow\u3068Keras\u306b\u3088\u308b\u30c7\u30a3\u30fc\u30d7\u30e9\u30fc\u30cb\u30f3\u30b0\u2460\u3010\u7b2c2\u56de:GPU\u30b3\u30f3\u30c6\u30ca\u3067\u753b\u50cf\u89e3\u6790\u301c\u6e96\u5099\u7de8\u301c\u3011<\/a> <\/td> <\/tr>
TensorFlow\u3068Keras\u306b\u3088\u308b\u30c7\u30a3\u30fc\u30d7\u30e9\u30fc\u30cb\u30f3\u30b0\u2461\u3010\u7b2c3\u56de:GPU\u30b3\u30f3\u30c6\u30ca\u3067\u753b\u50cf\u89e3\u6790\u301c\u5b9f\u8df5\u7de8\u301c\u3011<\/a> <\/td> <\/tr>
Chainer\u3092\u4f7f\u3063\u305f\u30c7\u30a3\u30fc\u30d7\u30e9\u30fc\u30cb\u30f3\u30b0\u3010\u7b2c4\u56de:GPU\u30b3\u30f3\u30c6\u30ca\u3067\u6a5f\u68b0\u5b66\u7fd2\u3059\u308b\u3011<\/a> <\/td> <\/tr>
PyTorch\u3067\u6a5f\u68b0\u5b66\u7fd2\u3010\u7b2c5\u56de:GPU\u30b3\u30f3\u30c6\u30ca\u3067\u30c6\u30f3\u30bd\u30eb\u306e\u57fa\u672c\u3092\u7406\u89e3\u3059\u308b\u3011<\/a> <\/td> <\/tr> <\/tbody> <\/table><\/div>
\n
\"GPU\u30b3\u30f3\u30c6\u30ca\u3068\u306f\u4f55\u304b\uff1f\u4f55\u304c\u4fbf\u5229\u306a\u306e\u304b\uff1f\u3010\u7b2c1\u56de\uff1aGPU\u30b3\u30f3\u30c6\u30ca\u3067\u901f\u653b\u74b0\u5883\u69cb\u7bc9\u3011\"<\/figure>\n<\/div>\n\n\n

\u9ad8\u901f\u63cf\u753b\u51e6\u7406\u304c\u5fc5\u8981\u3068\u3055\u308c\u308bCG\u3001VR\u30013DCAD\u7b49\u3067\u5229\u7528\u3055\u308c\u3066\u304d\u305fGPU\uff08Graphics Processing Unit\uff1a\u30b0\u30e9\u30d5\u30a3\u30c3\u30af\u30b9 \u30d7\u30ed\u30bb\u30c3\u30b7\u30f3\u30b0 \u30e6\u30cb\u30c3\u30c8\uff09<\/mark>\u3067\u3059\u304c\u3001\u8fd1\u5e74\u306fIoT\u3084AI\u306e\u9700\u8981\u304c\u5897\u3048\u308b\u306b\u3064\u308c\u3066\u79d1\u5b66\u6280\u8853\u8a08\u7b97\u3084\u30c7\u30a3\u30fc\u30d7\u30e9\u30fc\u30cb\u30f3\u30b0\u306a\u3069\u81a8\u5927\u306a\u30c7\u30fc\u30bf\u3092\u6271\u3046\u5834\u9762\u3067\u306e\u5229\u7528\u304c\u5897\u3048\u3066\u3044\u307e\u3059\u3002
\u3072\u3068\u3053\u3068\u3067GPU\u3068\u8a00\u3063\u3066\u3082\u3001\u30b2\u30fc\u30df\u30f3\u30b0PC\u306e\u30b0\u30e9\u30d5\u30a3\u30c3\u30af\u30dc\u30fc\u30c9\u306b\u642d\u8f09\u3055\u308c\u308b\u30d1\u30fc\u30bd\u30ca\u30eb\u30e6\u30fc\u30b9\u306eGPU\u304b\u3089\u3001CPU\u306e\u6570\u500d\u304b\u3089100\u500d\u4ee5\u4e0a\u306e\u901f\u5ea6\u3067\u8a08\u7b97\u51e6\u7406\u884c\u3046\u3053\u3068\u3092\u53ef\u80fd\u3068\u3059\u308b\u30c7\u30fc\u30bf\u30bb\u30f3\u30bf\u30fc\u5411\u3051GPU\u307e\u3067\u69d8\u3005\u306a\u7a2e\u985e\u304c\u5b58\u5728\u3057\u307e\u3059\u3002<\/p>\n\n\n\n

[5\u5206\u3067\u7406\u89e3]GPU\u3068\u306f\uff1fCPU\u3068\u306e\u9055\u3044\u3084\u6027\u80fd\u3068\u6d3b\u7528<\/strong>
https:\/\/www.kagoya.jp\/howto\/rentalserver\/gpu1\/<\/a><\/p>\n\n\n\n

\u3053\u306e\u3088\u3046\u306bGPU\u306e\u5229\u7528\u5834\u9762\u304c\u5e83\u7bc4\u306b\u308f\u305f\u308b\u4e2d\u3067\u3001\u6a5f\u68b0\u5b66\u7fd2\u3084\u30c7\u30a3\u30fc\u30d7\u30e9\u30fc\u30cb\u30f3\u30b0\u306b\u9069\u3057\u305f\u30e9\u30a4\u30d6\u30e9\u30ea\u304c\u516c\u958b\u3055\u308c\u3066\u304d\u307e\u3057\u305f\u3002\u672c\u6765\u3067\u3042\u308c\u3070GPU\u3092\u5b9f\u88c5\u3057\u305f\u30b3\u30f3\u30d4\u30e5\u30fc\u30bf\u30fc\u4e0a\u3067\u5373\u5ea7\u306b\u30d7\u30ed\u30b0\u30e9\u30e0\u3084\u30e9\u30a4\u30d6\u30e9\u30ea\u304c\u7a3c\u50cd\u3059\u308c\u3070\u3001\u52b9\u7387\u3088\u304f\u8ab2\u984c\u89e3\u6c7a\u3067\u304d\u308b\u306e\u3067\u3059\u304c\u3001OS\u306e\u7a2e\u985e\u3084\u30c7\u30d0\u30a4\u30b9\u30c9\u30e9\u30a4\u30d0\u30fc\u306e\u7d44\u307f\u5408\u308f\u305b\u3001\u30e9\u30a4\u30d6\u30e9\u30ea\u306e\u30d0\u30fc\u30b8\u30e7\u30f3\u3068\u306e\u76f8\u6027\u306a\u3069\u304b\u3089\u74b0\u5883\u69cb\u7bc9\u4f5c\u696d\u306b\u5de5\u6570\u3092\u8cbb\u3084\u3059\u3053\u3068\u304c\u591a\u3005\u3042\u308a\u307e\u3059\u3002\u3053\u306e\u554f\u984c\u3092\u89e3\u6c7a\u3059\u308b\u305f\u3081\u306e\u3072\u3068\u3064\u306e\u624b\u6bb5\u3068\u3057\u3066\u3001\u30b3\u30f3\u30c6\u30ca\u6280\u8853\u3092\u6d3b\u7528\u3057\u3001\u74b0\u5883\u69cb\u7bc9\u306e\u7c21\u6613\u5316\u3068\u30b3\u30f3\u30c6\u30ca\u304b\u3089GPU\u3092\u52b9\u7387\u3088\u304f\u7a3c\u50cd\u3055\u305b\u308b\u3053\u3068<\/mark>\u3092\u76ee\u6307\u3057\u307e\u3059\u3002<\/p>\n\n\n\n

\u3053\u306e\u9023\u8f09\u306b\u3064\u3044\u3066<\/h2>\n\n\n\n

\u672c\u9023\u8f09\u306f\u3001\u51685\u56de\u306e\u30b7\u30ea\u30fc\u30ba\u3092\u901a\u3057\u3066\u3067\u304d\u308b\u3060\u3051\u52b9\u7387\u7684\u306b\u3001GPU\u306e\u74b0\u5883\u69cb\u7bc9\u3092\u884c\u3046\u305f\u3081\u306b\u30b3\u30f3\u30c6\u30ca\u306e\u6d3b\u7528\u3092\u884c\u3063\u3066\u3044\u304d\u307e\u3059\u3002<\/mark>\u300c\u6a5f\u68b0\u5b66\u7fd2\u3084\u30c7\u30a3\u30fc\u30d7\u30e9\u30fc\u30cb\u30f3\u30b0\u3092GPU\u3067\u5b9f\u884c\u3057\u3066\u307f\u305f\u3044\u3051\u3069\u96e3\u3057\u305d\u3046\u2026\u300d\u306a\u3069\u5c0e\u5165\u306b\u30cf\u30fc\u30c9\u30eb\u3092\u611f\u3058\u3089\u308c\u3066\u3044\u308b\u65b9\u306b\u3001\u30b3\u30f3\u30c6\u30ca\u3092\u6d3b\u7528\u3059\u308b\u3053\u3068\u3067\u3001\u74b0\u5883\u69cb\u7bc9\u306b\u8981\u3059\u308b\u5de5\u6570\u3092\u5727\u5012\u7684\u306b\u524a\u6e1b\u3057\u3001\u5373\u5ea7\u306b\u8ab2\u984c\u306b\u53d6\u308a\u7d44\u3080\u3053\u3068\u304c\u3067\u304d\u308b\u30e1\u30ea\u30c3\u30c8\u3092\u611f\u3058\u3066\u3044\u305f\u3060\u304d\u307e\u3059\u3002\u305d\u306e\u305f\u3081\u306b\u5fc5\u8981\u306a\u77e5\u8b58\u3084\u64cd\u4f5c\u65b9\u6cd5\u3092\u3001\u5f53\u793e\u306eGPU\u30b5\u30fc\u30d0\u30fc\u3092\u4f7f\u3044\u89e3\u8aac\u3057\u3066\u3044\u304d\u307e\u3059\u3002
\u9023\u8f09\u3092\u8aad\u307f\u7d42\u3048\u308b\u3053\u308d\u306b\u306f\u3001TensorFlow<\/mark>\u3084PyTorch<\/mark>\u306a\u3069\u306e\u30e1\u30b8\u30e3\u30fc\u306a\u30d5\u30ec\u30fc\u30e0\u30ef\u30fc\u30af\u3092\u4f7f\u3063\u305f\u6f14\u7fd2\u304c\u3067\u304d\u308b\u3088\u3046\u306b\u306a\u3063\u3066\u3044\u308b\u306f\u305a\u3067\u3059\u3002<\/p>\n\n\n

\n
\"\"<\/figure>\n<\/div>\n\n\n

\u672c\u9023\u8f09\u306f\u6b21\u56de\u4ee5\u964d\u3001\u3053\u3061\u3089\u306e\u624b\u9806\u3067\u9032\u3081\u3066\u3044\u304d\u307e\u3059<\/h3>\n\n\n\n

\u30fbTensorFlow\u3068Keras\u306b\u3088\u308b\u30c7\u30a3\u30fc\u30d7\u30e9\u30fc\u30cb\u30f3\u30b0\uff08\u7b2c2\u56de\uff09<\/h4>\n\n\n\n

OSS\uff08\u30aa\u30fc\u30d7\u30f3\u30bd\u30fc\u30b9\u30bd\u30d5\u30c8\u30a6\u30a8\u30a2\uff09\u306e\u6a5f\u68b0\u5b66\u7fd2\u30e9\u30a4\u30d6\u30e9\u30ea\u306e\u4e2d\u304b\u3089TensorFlow\uff08\u30c6\u30f3\u30bd\u30eb\u30d5\u30ed\u30fc\uff09<\/mark>\u3001Keras\uff08\u30b1\u30e9\u30b9\uff09<\/mark>\u3092\u53d6\u308a\u4e0a\u3052\u3001\u3053\u308c\u3089\u304c\u7a3c\u50cd\u3059\u308b\u30b3\u30f3\u30c6\u30ca\u3092\u4f5c\u6210\u3057\u3001\u30b3\u30f3\u30c6\u30ca\u5185\u304b\u3089GPU\u3092\u6307\u5b9a\u3059\u308b\u65b9\u6cd5\u306b\u3064\u3044\u3066\u7d39\u4ecb\u3057\u307e\u3059\u3002TensorFlow\u306fKeras\u3092\u53d6\u308a\u8fbc\u3080\u5f62\u3067\u516c\u958b\u3055\u308c\u3066\u3044\u3066\u3001\u30c7\u30a3\u30fc\u30d7\u30e9\u30fc\u30cb\u30f3\u30b0\u3092\u3059\u308b\u969b\u306e\u4f7f\u3044\u52dd\u624b\u306e\u826f\u3055\u304b\u3089\u3001\u591a\u304f\u306e\u30e6\u30fc\u30b6\u30fc\u306b\u5229\u7528\u3055\u308c\u3066\u3044\u307e\u3059\u3002\u3053\u306e\u56de\u3067\u306fKeras\u3092\u4f7f\u3063\u3066\u753b\u50cf\u8a8d\u8b58\u3092\u884c\u3044\u307e\u3059\u3002<\/p>\n\n\n\n

\u30fbChainer\u3092\u4f7f\u3063\u305f\u30c7\u30a3\u30fc\u30d7\u30e9\u30fc\u30cb\u30f3\u30b0\uff08\u7b2c3\u56de\uff09<\/h4>\n\n\n\n

\u30c7\u30a3\u30fc\u30d7\u30e9\u30fc\u30cb\u30f3\u30b0\u306e\u30d5\u30ec\u30fc\u30e0\u30ef\u30fc\u30af\u3068\u3057\u3066\u6709\u540d\u306aChainer\uff08\u30c1\u30a7\u30a4\u30ca\u30fc\uff09<\/mark>\u306e\u5229\u7528\u65b9\u6cd5\u3092\u7d39\u4ecb\u3057\u307e\u3059\u3002\u30b3\u30f3\u30c6\u30ca\u304b\u3089GPU\u3092\u5229\u7528\u3059\u308b\u624b\u9806\u3068\u3001GPU\u306b\u3088\u3063\u3066\u3069\u308c\u3060\u3051\u9ad8\u901f\u5316\u306b\u5bc4\u4e0e\u3067\u304d\u305f\u304b\u306b\u3064\u3044\u3066\u3001Python\u306e\u30d7\u30ed\u30b0\u30e9\u30e0\u5b9f\u884c\u7d50\u679c\u3092\u901a\u3057\u3066\u78ba\u8a8d\u3057\u307e\u3059\u3002C\u8a00\u8a9e\u306b\u6bd4\u3079\u3066\u51e6\u7406\u6642\u9593\u304c\u304b\u304b\u308b\u3068\u8a00\u308f\u308c\u3066\u3044\u308bPython\u3067\u3059\u304c\u3001\u6570\u5024\u8a08\u7b97\u3092\u52b9\u7387\u7684\u306b\u884c\u3046\u305f\u3081\u306e\u62e1\u5f35\u30e2\u30b8\u30e5\u30fc\u30eb\u3067\u3042\u308bNumPy\uff08\u30ca\u30e0\u30d1\u30a4\uff09<\/mark>\u306b\u3064\u3044\u3066\u3082\u53d6\u308a\u4e0a\u3052\u307e\u3059\u3002<\/p>\n\n\n\n

\u30fbPytorch\u3067\u30cb\u30e5\u30fc\u30e9\u30eb\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\uff08\u7b2c4\u56de\uff09<\/h4>\n\n\n\n

Python\u306e\u6a5f\u68b0\u5b66\u7fd2\u7528\u30d5\u30ec\u30fc\u30e0\u30ef\u30fc\u30af\u3067\u3042\u308bPytorch\uff08\u30d1\u30a4\u30c8\u30fc\u30c1\uff09<\/mark>\u3092\u53d6\u308a\u4e0a\u3052\u307e\u3059\u3002PyTorch\u3067\u306fTensor\uff08\u30c6\u30f3\u30bd\u30eb\uff09\u3068\u3044\u3046\u578b\u3067\u884c\u5217\u3092\u8868\u73fe\u3057\u307e\u3059\u3002Tensor\u306f\u591a\u6b21\u5143\u914d\u5217\u3092\u6271\u3046\u305f\u3081\u306e\u30c7\u30fc\u30bf\u69cb\u9020\u3067\u3042\u308a\u3001GPU\u3092\u30b5\u30dd\u30fc\u30c8\u3057\u3066\u3044\u308b\u3053\u3068\u304b\u3089\u3001Pytorch\u304c\u7a3c\u50cd\u3059\u308b\u30b3\u30f3\u30c6\u30ca\u3092\u5229\u7528\u3057\u3001GPU\u306b\u3088\u308b\u9ad8\u901f\u51e6\u7406\u3092\u884c\u3046\u624b\u9806\u306b\u3064\u3044\u3066\u7d39\u4ecb\u3057\u307e\u3059\u3002<\/p>\n\n\n\n

\u30fbOpenPose\u306b\u3088\u308b\u95a2\u7bc0\u70b9\u62bd\u51fa\u30fb\u59ff\u52e2\u63a8\u5b9a\uff08\u7b2c5\u56de\uff09<\/h4>\n\n\n\n

\u30ab\u30e1\u30e9\u753b\u50cf\u306eAI\u753b\u50cf\u8a8d\u8b58\u3068\u8a00\u3048\u3070\u300c\u9854\u8a8d\u8a3c\u300d\u3092\u601d\u3044\u6d6e\u304b\u3079\u308b\u4eba\u304c\u591a\u3044\u3068\u601d\u3044\u307e\u3059\u304c\u3001\u6700\u8fd1\u306f\u4e00\u6b69\u9032\u307f\u3001\u4eba\u304c\u6620\u3063\u305f\u9759\u6b62\u753b\u3084\u52d5\u753b\u304b\u3089\u95a2\u7bc0\u70b9\u62bd\u51fa\u30fb\u59ff\u52e2\u63a8\u5b9a\u306b\u53d6\u308a\u7d44\u3080\u30b1\u30fc\u30b9\u304c\u5897\u3048\u3066\u3044\u307e\u3059\u3002\u4eba\u4f53\u3001\u9854\u3001\u624b\u8db3\u306a\u3069\u306e\u30ad\u30fc\u30dd\u30a4\u30f3\u30c8\u3092\u753b\u50cf\u304b\u3089\u691c\u51fa\u3059\u308b\u6280\u8853\u304c\u30c7\u30a3\u30fc\u30d7\u30e9\u30fc\u30cb\u30f3\u30b0\u306b\u3088\u308a\u3001\u5b9f\u7528\u30ec\u30d9\u30eb\u307e\u3067\u5411\u4e0a\u3057\u3066\u3044\u308b\u304b\u3089\u3067\u3059\u3002\u3053\u306e\u56de\u3067\u306fOpenPose\uff08\u30aa\u30fc\u30d7\u30f3\u30dd\u30fc\u30ba\uff09<\/mark>\u3068\u3044\u3046\u30e9\u30a4\u30d6\u30e9\u30ea\u3092GPU\u4e0a\u3067\u52d5\u304b\u3059\u30b3\u30f3\u30c6\u30ca\u3092\u4f7f\u3044\u3001\u52d5\u753b\u30d5\u30a1\u30a4\u30eb\u306e\u95a2\u7bc0\u70b9\u62bd\u51fa\u624b\u9806\u3092\u7d39\u4ecb\u3057\u307e\u3059\u3002<\/p>\n\n\n\n

GPU\u30b3\u30f3\u30c6\u30ca\u306e\u57fa\u790e\u77e5\u8b58<\/h2>\n\n\n\n

\u3067\u306f\u3001\u3053\u3053\u304b\u3089\u306fGPU\u30b3\u30f3\u30c6\u30ca\u3092\u6d3b\u7528\u3059\u308b\u305f\u3081\u306e\u57fa\u790e\u77e5\u8b58\u3084\u74b0\u5883\u69cb\u7bc9\u306e\u624b\u9806\u306b\u3064\u3044\u3066\u7d39\u4ecb\u3057\u307e\u3059\u3002<\/p>\n\n\n\n

\u305d\u3082\u305d\u3082\u30b3\u30f3\u30c6\u30ca\u6280\u8853\u3068\u306f\uff1f<\/h3>\n\n\n\n

\u4e0b\u56f3\u306e\u3088\u3046\u306b\u30db\u30b9\u30c8OS\u306e\u4e0a\u306b\u30b3\u30f3\u30c6\u30ca\u7ba1\u7406\u30bd\u30d5\u30c8\u3092\u5b9f\u88c5\u3057\u3001\u305d\u306e\u4e0a\u306b\u30b3\u30f3\u30c6\u30ca\u3068\u547c\u3070\u308c\u308b\u8ad6\u7406\u7684\u306a\u533a\u753b\u3092\u4f5c\u308a\u307e\u3059\u3002\u3053\u306e\u30b3\u30f3\u30c6\u30ca\u5185\u3067\u30a2\u30d7\u30ea\u3092\u52d5\u4f5c\u3055\u305b\u308b\u305f\u3081\u306b\u5fc5\u8981\u306a\u30e9\u30a4\u30d6\u30e9\u30ea\u7b49\u306e\u30df\u30c9\u30eb\u30a6\u30a8\u30a2\u3068\u3044\u3063\u3057\u3087\u306b\u3072\u3068\u3064\u306b\u307e\u3068\u3081\u305f\u6982\u5ff5\u3067\u3059\u3002\u3053\u306e\u3088\u3046\u306b\u3059\u308b\u3053\u3068\u3067\u3072\u3068\u3064\u306e\u30b3\u30f3\u30c6\u30ca\u3092\u3072\u3068\u3064\u306e\u30b5\u30fc\u30d0\u30fc\u306e\u3088\u3046\u306b\u4f7f\u7528\u3059\u308b\u3053\u3068\u304c\u53ef\u80fd\u306b\u306a\u308a\u307e\u3059\u3002<\/p>\n\n\n

\n
\"\"<\/figure>\n<\/div>\n\n\n

\u30b3\u30f3\u30c6\u30ca\u306b\u3064\u3044\u3066\u306f\u3001\u4ee5\u4e0b\u306e\u30b3\u30e9\u30e0\u306b\u8a18\u8f09\u3055\u308c\u3066\u3044\u307e\u3059\u306e\u3067\u3001\u53c2\u8003\u306b\u3057\u3066\u304f\u3060\u3055\u3044\u3002<\/p>\n\n\n\n

\u3010\u518d\u5165\u9580\u3011\u30b3\u30f3\u30c6\u30ca\u6280\u8853\u3068\u306f\uff1f\u57fa\u672c\u3092\u308f\u304b\u308a\u3084\u3059\u304f\u89e3\u8aac\u3057\u307e\u3059<\/strong>
https:\/\/www.kagoya.jp\/howto\/rentalserver\/container-03\/<\/a><\/p>\n\n\n\n

\u672c\u9023\u8f09\u8a18\u4e8b\u3067\u306f\u3001TensorFlow\u306a\u3069\u306e\u30e1\u30b8\u30e3\u30fc\u306a\u30d5\u30ec\u30fc\u30e0\u30ef\u30fc\u30af\u3092\u542b\u3080\u30b3\u30f3\u30c6\u30ca\u3092\u5229\u7528\u3057\u3001GPU\u306e\u52b9\u679c\u7684\u306a\u6d3b\u7528\u65b9\u6cd5\u3092\u5177\u4f53\u7684\u306b\u7d39\u4ecb\u3057\u3066\u3044\u304d\u307e\u3059\u3002<\/p>\n\n\n\n

GPU\u30b3\u30f3\u30c6\u30ca\u306e\u8003\u3048\u65b9<\/h3>\n\n\n\n

\u30fbGPU\u5411\u3051\u30b3\u30f3\u30c6\u30ca\u304c\u5fc5\u8981\u306a\u7406\u7531<\/h4>\n\n\n\n

AI\u306e\u521d\u5b66\u8005\u304cGPU\u30de\u30b7\u30f3\u4e0a\u3067\u30c7\u30a3\u30fc\u30d7\u30e9\u30fc\u30cb\u30f3\u30b0\u7b49\u3092\u884c\u3046\u305f\u3081\u306e\u30cf\u30fc\u30c9\u30eb\u306e\u3072\u3068\u3064\u3068\u3057\u3066\u3001\u958b\u767a\u74b0\u5883\u3092\u69cb\u7bc9\u3059\u308b\u305f\u3081\u306e\u5de5\u6570\u304c\u6319\u3052\u3089\u308c\u307e\u3059\u3002<\/mark>\u30c9\u30e9\u30a4\u30d0\u3001\u30d5\u30ec\u30fc\u30e0\u30ef\u30fc\u30af\u3001\u30e9\u30a4\u30d6\u30e9\u30ea\u306e\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb\u3092\u884c\u3063\u3066\u3082\u3001\u305d\u308c\u305e\u308c\u306e\u30d0\u30fc\u30b8\u30e7\u30f3\u306e\u7d44\u307f\u5408\u308f\u305b\u3084\u76f8\u6027\u3067\u30e9\u30a4\u30d6\u30e9\u30ea\u304c\u6b63\u5e38\u306b\u8d77\u52d5\u305b\u305a\u3001\u52d5\u4f5c\u691c\u8a3c\u306e\u305f\u3081\u306b\u6570\u65e5\u8981\u3059\u308b\u3053\u3068\u304c\u3042\u308a\u3048\u307e\u3059\u3002\u30d5\u30ec\u30fc\u30e0\u30ef\u30fc\u30af\u306f\u65e5\u3005\u3001\u9032\u5316\u3057\u3066\u304a\u308a\u3001\u65b0\u3057\u3044\u30d0\u30fc\u30b8\u30e7\u30f3\u304c\u30ea\u30ea\u30fc\u30b9\u3055\u308c\u308b\u983b\u5ea6\u3082\u9ad8\u304f\u3001\u5404\u30bd\u30d5\u30c8\u306e\u30d0\u30fc\u30b8\u30e7\u30f3\u306e\u7d44\u307f\u5408\u308f\u305b\u3067\u52d5\u4f5c\u3057\u306a\u3044\u3053\u3068\u3092\u7d4c\u9a13\u3055\u308c\u305f\u304b\u305f\u3082\u591a\u3044\u306e\u3067\u306f\u306a\u3044\u304b\u3068\u601d\u3044\u307e\u3059\u3002<\/p>\n\n\n\n

\u30fbGPU\u30b3\u30f3\u30c6\u30ca\u3092\u4f7f\u3046\u30e1\u30ea\u30c3\u30c8<\/h4>\n\n\n\n

\u672c\u6765\u3067\u3042\u308c\u3070\u3001\u81a8\u5927\u306a\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u3092\u4f7f\u3046\u5b66\u7fd2\u30e2\u30c7\u30eb\u69cb\u7bc9\u3084\u9ad8\u901f\u6f14\u7b97\u51e6\u7406\u306b\u3059\u3050\u306b\u7740\u624b\u3057\u305f\u3044\u308f\u3051\u3067\u3059\u304c\u3001\u524d\u8ff0\u306e\u3088\u3046\u306a\u30bb\u30c3\u30c8\u30a2\u30c3\u30d7\u4f5c\u696d\u306b\u6642\u9593\u3092\u8981\u3059\u308b\u30b1\u30fc\u30b9\u3092\u907f\u3051\u308b\u305f\u3081\u306e\u3072\u3068\u3064\u306e\u624b\u6bb5\u3068\u3057\u3066\u3001GPU\u306b\u5bfe\u5fdc\u3057\u305f\u30b3\u30f3\u30c6\u30ca\u3092\u4f7f\u3046\u3053\u3068\u304c\u8003\u3048\u3089\u308c\u307e\u3059\u3002
\u30d9\u30f3\u30c0\u30fc\u304c\u63d0\u4f9b\u3057\u3066\u3044\u308b\u30b3\u30f3\u30c6\u30ca\u3084Docker Hub\u306b\u516c\u958b\u3055\u308c\u3066\u3044\u308b\u30b3\u30f3\u30c6\u30ca\u3092\u52b9\u679c\u7684\u306b\u5229\u7528\u3059\u308c\u3070\u3001\u74b0\u5883\u69cb\u7bc9\u5de5\u6570\u3092\u5927\u5e45\u306b\u524a\u6e1b\u3067\u304d\u3001\u3059\u3050\u306b\u8ab2\u984c\u306b\u53d6\u308a\u7d44\u3080\u3053\u3068\u3082\u53ef\u80fd\u3067\u3059\u3002<\/mark>
\u307e\u305f\u3001\u3072\u3068\u3064\u306e\u30c6\u30fc\u30de\u306b\u5bfe\u3057\u3066\u3001\u69d8\u3005\u30d5\u30ec\u30fc\u30e0\u30ef\u30fc\u30af\u3092\u4f7f\u3044\u3001\u51e6\u7406\u7d50\u679c\u306e\u76f8\u9055\u3084\u51e6\u7406\u6642\u9593\u3092\u30d9\u30f3\u30c1\u30de\u30fc\u30af\u3057\u305f\u3044\u5834\u5408\u306b\u3082\u3001\u30b3\u30f3\u30c6\u30ca\u306e\u6709\u52b9\u6d3b\u7528\u304c\u671f\u5f85\u3067\u304d\u307e\u3059\u3002<\/p>\n\n\n\n

\u30fbGPU\u30b3\u30f3\u30c6\u30ca\u3092\u4f7f\u3046\u30c7\u30e1\u30ea\u30c3\u30c8<\/h4>\n\n\n\n

\u3053\u306e\u3088\u3046\u306bGPU\u30b3\u30f3\u30c6\u30ca\u3092\u4f7f\u3046\u30e1\u30ea\u30c3\u30c8\u306f\u3068\u3066\u3082\u5927\u304d\u3044\u3068\u8a00\u3048\u308b\u306e\u3067\u3059\u304c\u3001\u5229\u7528\u8005\u304c\u30b3\u30f3\u30c6\u30ca\u306e\u4e2d\u8eab\u3092\u7406\u89e3\u3057\u306a\u3044\u3068\u3001\u30d5\u30ec\u30fc\u30e0\u30ef\u30fc\u30af\u3084\u30e9\u30a4\u30d6\u30e9\u30ea\u306e\u30a2\u30c3\u30d7\u30c7\u30fc\u30c8\u6642\u306a\u3069\u306e\u74b0\u5883\u5909\u5316\u306b\u81ea\u529b\u3067\u5bfe\u5fdc\u3067\u304d\u306a\u3044<\/mark>\u3053\u3068\u304c\u3042\u308b\u305f\u3081\u3001\u5229\u4fbf\u6027\u3092\u4eab\u53d7\u3057\u306a\u304c\u3089\u3082\u540c\u6642\u306b\u30b3\u30f3\u30c6\u30ca\u5185\u3067\u4f55\u304c\u884c\u308f\u308c\u3066\u3044\u308b\u304b\u306b\u3064\u3044\u3066\u77e5\u3063\u3066\u304a\u304f\u5fc5\u8981\u304c\u3042\u308a\u307e\u3059\u3002
\u3067\u306f\u3001GPU\u30b3\u30f3\u30c6\u30ca\u3092\u5b9f\u969b\u306b\u4f7f\u3063\u3066\u307f\u307e\u3057\u3087\u3046\u3002<\/p>\n\n\n\n

GPU\u3092\u4f7f\u3046\u305f\u3081\u306e\u6e96\u5099<\/h2>\n\n\n\n

\u3053\u3053\u3067\u306f\u3001\u30ab\u30b4\u30e4\u306eNVIDIA Tesla GPU\u30b5\u30fc\u30d0\u30fc P100\u307e\u305f\u306fP40\u3092\u4f7f\u3063\u3066\u6a5f\u68b0\u5b66\u7fd2\u3092\u3059\u308b\u305f\u3081\u306e\u6e96\u5099\u3092\u884c\u3044\u307e\u3059\u3002\u5bfe\u8c61\u30d7\u30ed\u30bb\u30c3\u30b5\u7528\u306e\u30c7\u30d0\u30a4\u30b9\u30c9\u30e9\u30a4\u30d0\u30fc\u306e\u30c0\u30a6\u30f3\u30ed\u30fc\u30c9\u3001CUDA\uff08\u30af\u30fc\u30c0\uff1aNVIDIA\u793e\u304c\u63d0\u4f9b\u3059\u308bGPU\u30b3\u30f3\u30d4\u30e5\u30fc\u30c6\u30a3\u30f3\u30b0\u5411\u3051\u7d71\u5408\u958b\u767a\u74b0\u5883\uff09\u306e\u8a2d\u5b9a\u65b9\u6cd5\u306a\u3089\u3073\u306bcuDNN\uff08\u30c7\u30a3\u30fc\u30d7\u30e9\u30fc\u30cb\u30f3\u30b0\u7528\u30e9\u30a4\u30d6\u30e9\u30ea\uff09\u306e\u4f7f\u3044\u65b9\u306a\u3069\u3001GPU\u6d3b\u7528\u306b\u4e0d\u53ef\u6b20\u306a\u57fa\u790e\u77e5\u8b58\u306b\u3064\u3044\u3066\u3068\u308a\u3042\u3052\u307e\u3059\u3002<\/p>\n\n\n\n

GPU\u30ab\u30fc\u30c9 \u30c9\u30e9\u30a4\u30d0\u3068CUDA Toolkit\u306e\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb<\/h3>\n\n\n\n

\u307e\u305a\u59cb\u3081\u306b\u884c\u3046\u3053\u3068\u306fGPU\u3092\u642d\u8f09\u3057\u305f\u30b0\u30e9\u30d5\u30a3\u30c3\u30af\u30dc\u30fc\u30c9\uff08GPU\u30ab\u30fc\u30c9\uff09\u306e\u30c7\u30d0\u30a4\u30b9\u30c9\u30e9\u30a4\u30d0\u30fc\u3092\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb\u3059\u308b\u3053\u3068\u3067\u3059\u3002
\u304a\u304a\u307e\u304b\u306a\u624b\u9806\u306f\u4ee5\u4e0b\u306b\u306a\u308a\u307e\u3059\u304c\u3001\u8a73\u7d30\u306f\u30ab\u30b4\u30e4\u306eWEB\u30b5\u30a4\u30c8\u4e0a\u306b\u3042\u308b\u30aa\u30f3\u30e9\u30a4\u30f3\u30de\u30cb\u30e5\u30a2\u30eb\u306b\u8a18\u8f09\u3055\u308c\u3066\u3044\u307e\u3059\u306e\u3067\u3001\u3054\u53c2\u7167\u304f\u3060\u3055\u3044\u3002<\/p>\n\n\n\n

NVIDIA\u30c9\u30e9\u30a4\u30d0\u30fc\u306e\u30c0\u30a6\u30f3\u30ed\u30fc\u30c9<\/strong>
\u516c\u5f0f\u30c0\u30a6\u30f3\u30ed\u30fc\u30c9\u30da\u30fc\u30b8\u306f\u3053\u3061\u3089
https:\/\/www.nvidia.com\/Download\/index.aspx?lang=en-us<\/a><\/p>\n\n\n\n

Ubuntu\u3067\u306eGPU\u30ab\u30fc\u30c9\u30c9\u30e9\u30a4\u30d0\u30fc\u306e\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb<\/strong>
\u30ab\u30b4\u30e4\u30b5\u30fc\u30d0\u30fc\u3067\u306e\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb\u624b\u9806\u306f\u3053\u3061\u3089<\/a><\/p>\n\n\n\n

GPU \u306f\u672c\u6765\u3001\u753b\u50cf\u51e6\u7406\u7528\u30d7\u30ed\u30bb\u30c3\u30b5\u3067\u3042\u308b\u305f\u3081\u3001\u6c4e\u7528\u8a08\u7b97\u7528\u9014\u3067\u4f7f\u7528\u3059\u308b\u306b\u306f GPGPU\uff08General-purpose computing on graphics processing units\uff09\u958b\u767a\u74b0\u5883\u3067\u3042\u308b\u300cCUDA\u300d\u304c\u5fc5\u8981\u306b\u306a\u308a\u307e\u3059\u3002 \u300cCUDA\u300d\u3092\u4f7f\u7528\u3059\u308b\u306b\u306f\u3001CUDA Toolkit \u3092\u30b5\u30fc\u30d0\u30fc\u306b\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb\u3059\u308b\u5fc5\u8981\u304c\u3042\u308a\u307e\u3059\u3002<\/p>\n\n\n\n

CUDA Toolkit\uff0811.0 RC\uff09\u306e\u30c0\u30a6\u30f3\u30ed\u30fc\u30c9\u3068\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb<\/strong>
\u516c\u5f0f\u30c0\u30a6\u30f3\u30ed\u30fc\u30c9\u30da\u30fc\u30b8\u306f\u3053\u3061\u3089
https:\/\/developer.nvidia.com\/cuda-downloads<\/a><\/p>\n\n\n\n

GPU\u306b\u5bfe\u5fdc\u3057\u305f\u30b3\u30f3\u30c6\u30ca\u306e\u6e96\u5099<\/h3>\n\n\n\n

\u3053\u3053\u304b\u3089Docker\u3092\u4f7f\u3063\u3066GPU\u3092\u30b3\u30f3\u30c6\u30ca\u5316\u3059\u308b\u4f5c\u696d\u306b\u5165\u3063\u3066\u3044\u304d\u307e\u3059\u306e\u3067\u3001\u5148\u305a\u306f\u30b3\u30f3\u30c6\u30ca\u304c\u5229\u7528\u3067\u304d\u308b\u74b0\u5883\u3092\u69cb\u7bc9\u3057\u307e\u3059\u3002
\u3010\u74b0\u5883\u3011
OS\uff1aUbuntu 16.04 LTS
GPU\uff1aTesla P40<\/p>\n\n\n\n

\u30fbDocker\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb\u524d\u306e\u6e96\u5099<\/strong><\/p>\n\n\n\n

\u3053\u3053\u3067\u306f\u3001Community Edition (CE)\u3092\u30a4\u30f3\u30b9\u30fc\u30eb\u3057\u307e\u3059\u3002<\/p>\n\n\n\n

\u53e4\u3044\u30d0\u30fc\u30b8\u30e7\u30f3\u306eDocker\u304c\u5165\u3063\u3066\u3044\u308b\u5834\u5408\u306f\u30a2\u30f3\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb\u3057\u307e\u3059\u3002 \u306a\u3051\u308c\u3070\u3001\u30b9\u30ad\u30c3\u30d7\u3057\u3066\u6b21\u306e\u30b9\u30c6\u30c3\u30d7\u306b\u9032\u3093\u3067\u304f\u3060\u3055\u3044\u3002<\/p>\n\n\n

\n$ sudo apt-get -y remove docker docker-engine\n<\/pre><\/div>\n\n\n
apt\u3092\u30a2\u30c3\u30d7\u30c7\u30fc\u30c8\u3057\u307e\u3059\u3002<\/p>\n\n\n
\n$ sudo apt-get update\n<\/pre><\/div>\n\n\n
https\u3067\u30ea\u30dd\u30b8\u30c8\u30ea\u3092\u4f7f\u3048\u308b\u3088\u3046\u306b\u3059\u308b\u305f\u3081\u306b\u30d1\u30c3\u30b1\u30fc\u30b8\u3092\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb\u3057\u307e\u3059\u3002<\/p>\n\n\n
\n$ sudo apt-get -y install\napt-transport-https\nca-certificates\ncurl\nsoftware-properties-common\n<\/pre><\/div>\n\n\n
\u516c\u5f0fGPG\u30ad\u30fc\u3092\u8ffd\u52a0\u3057\u307e\u3059\u3002<\/p>\n\n\n
\n$ curl -fsSL https:\/\/download.docker.com\/linux\/ubuntu\/gpg | sudo apt-key add -\n<\/pre><\/div>\n\n\n
\u30b9\u30af\u30ea\u30d7\u30c8\u3092\u5b9f\u884c\u3057\u3001\u6b63\u3057\u304f\u767b\u9332\u3055\u308c\u305f\u3089 OK \u3068\u8868\u793a\u3055\u308c\u307e\u3059\u3002<\/p>\n\n\n\n
Docker\u30ea\u30dd\u30b8\u30c8\u30ea\u3092\u8ffd\u52a0\u3057\u3001\u767b\u9332\u304c\u7d42\u308f\u3063\u305f\u3089apt\u3092\u30a2\u30c3\u30d7\u30c7\u30fc\u30c8\u3057\u307e\u3059\u3002<\/p>\n\n\n
\n$ sudo add-apt-repository\n"deb [arch=amd64] https:\/\/download.docker.com\/linux\/ubuntu\n$(lsb_release -cs) \nstable"\n$ sudo apt-get update\n<\/pre><\/div>\n\n\n
\u30fbDocker\u306e\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb<\/strong><\/p>\n\n\n\n
\u6b21\u306e\u30b9\u30af\u30ea\u30d7\u30c8\u3092\u5b9f\u884c\u3057\u3001Docker\u3092\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb\u3057\u307e\u3059\u3002<\/p>\n\n\n
\n$ sudo apt-get -y install docker-ce\n<\/pre><\/div>\n\n\n
\u30fbDocker\u306e\u52d5\u4f5c\u78ba\u8a8d<\/strong><\/p>\n\n\n\n
ubuntu\u306e\u30a4\u30e1\u30fc\u30b8\u3092\u3082\u3068\u306bDocker\u30b3\u30f3\u30c6\u30ca\u3092\u4f5c\u6210\u3057\u3001\u5b9f\u884c\u3057\u307e\u3059\u3002\u4f5c\u6210\u3057\u305f\u30b3\u30f3\u30c6\u30ca\u306e\u4e2d\u3067hello-world\u3068\u3044\u3046\u6587\u5b57\u3092\u8868\u793a\u3055\u305b\u307e\u3059\u3002<\/p>\n\n\n
\n$ sudo docker container run ubuntu:latest \/bin\/echo "hello-world"\n<\/pre><\/div>\n\n\n
\u4e0b\u8a18\u306e\u3088\u3046\u306b\u8868\u793a\u3055\u308c\u308c\u3070Docker\u306f\u6b63\u5e38\u306b\u52d5\u4f5c\u3057\u3066\u3044\u307e\u3059\u3002<\/p>\n\n\n
\nUnable to find image 'ubuntu:latest' locally\nlatest: Pulling from library\/ubuntu\nd51af753c3d3: Pull complete\nfc878cd0a91c: Pull complete\n6154df8ff988: Pull complete\nfee5db0ff82f: Pull complete\nDigest: sha256:747d2dbbaaee995098c9792d99bd333c6783ce56150d1b11e333bbceed5c54d7\nStatus: Downloaded newer image for ubuntu:latest\nhello-world\n\n<\/pre><\/div>\n\n\n
Docker\u30b3\u30f3\u30c6\u30ca\u304b\u3089GPU\u3092\u5229\u7528\u3059\u308b<\/h2>\n\n\n\n
NVIDIA Container Toolkit\u306e\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb<\/h3>\n\n\n\n
NVIDIA Container Toolkit \u3092\u5229\u7528\u3057\u3001Docker\u30b3\u30f3\u30c6\u30ca\u304b\u3089\u30b5\u30fc\u30d0\u30fc\u4e0a\u306eGPU\u3092\u6307\u5b9a\u3057\u307e\u3059\u3002--gpus<\/code>\u3092\u4f7f\u3044\u3001GPU \u30b3\u30f3\u30c6\u30ca\u3092\u4f5c\u6210\u3057\u307e\u3059\u3002<\/p>\n\n\n\n
\u30ea\u30dd\u30b8\u30c8\u30ea\u3092apt\u306b\u767b\u9332\u3057\u3001\u30c4\u30fc\u30eb\u30ad\u30c3\u30c8\u3092\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb\u3057\u307e\u3059\u3002<\/p>\n\n\n
\n$ distribution=$(. \/etc\/os-release;echo $ID$VERSION_ID)\n$ curl -s -L https:\/\/nvidia.github.io\/nvidia-docker\/gpgkey | sudo apt-key add -\n$ curl -s -L https:\/\/nvidia.github.io\/nvidia-docker\/$distribution\/nvidia-docker.list | sudo tee \/etc\/apt\/sources.list.d\/nvidia-docker.list\n\n$ sudo apt update &amp;&amp; sudo apt install -y nvidia-container-toolkit\n$ sudo systemctl restart docker\n\n<\/pre><\/div>\n\n\n
nvidia-container-cli info\u30b3\u30de\u30f3\u30c9\u3067 GPU \u304c\u8a8d\u8b58\u3067\u304d\u3066\u3044\u308b\u3053\u3068\u3092\u78ba\u8a8d\u3057\u307e\u3059\u3002CUDA\u306e\u30d0\u30fc\u30b8\u30e7\u30f3\u3084GPU\u306e\u30e2\u30c7\u30eb\u60c5\u5831\u304c\u8868\u793a\u3055\u308c\u307e\u3059\u3002<\/p>\n\n\n
\n$ nvidia-container-cli info\nNVRM version: 440.64.00\nCUDA version: 10.2\n\nDevice Index: 0\nDevice Minor: 0\nModel: Tesla P40\nBrand: Tesla\nGPU UUID: GPU-ccffd358-4ab2-0dab-10cf-78df33604be1\nBus Location: 00000000:03:00.0\nArchitecture: 6.1\n\n<\/pre><\/div>\n\n\n
Docker\u30b3\u30f3\u30c6\u30ca\u3092\u8d77\u52d5\u3059\u308b<\/h3>\n\n\n\n
Docker \u30b3\u30f3\u30c6\u30ca\u5185\u3067nvidia-smi\u30b3\u30de\u30f3\u30c9\u3092\u5b9f\u884c\u3057\u3001GPU\u3092\u8a8d\u8b58\u3057\u3066\u3044\u308b\u304b\u78ba\u8a8d\u3057\u307e\u3059\u3002<\/p>\n\n\n
\n$ docker run --gpus all ubuntu nvidia-smi\nFri Jun 12 09:51:17 2020\n+-----------------------------------------------------------------------------+\n| NVIDIA-SMI 440.64.00 Driver Version: 440.64.00 CUDA Version: N\/A |\n|-------------------------------+----------------------+----------------------+\n| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |\n| Fan Temp Perf Pwr:Usage\/Cap| Memory-Usage | GPU-Util Compute M. |\n|===============================+======================+======================|\n| 0 Tesla P40 Off | 00000000:03:00.0 Off | 0 |\n| N\/A 27C P8 10W \/ 250W | 10MiB \/ 22919MiB | 0% Default |\n+-------------------------------+----------------------+----------------------+\n\n+-----------------------------------------------------------------------------+\n| Processes: GPU Memory |\n| GPU PID Type Process name Usage |\n|=============================================================================|\n| No running processes found |\n+-----------------------------------------------------------------------------+\n\n\n<\/pre><\/div>\n\n\n
Docker \u30b3\u30f3\u30c6\u30ca\u5185\u304b\u3089GPU\u3092\u8a8d\u8b58\u3067\u304d\u3066\u3044\u308b\u3053\u3068\u304c\u78ba\u8a8d\u3067\u304d\u307e\u3057\u305f\u3002<\/p>\n\n\n\n
\u9023\u8f09\u3092\u901a\u3057\u3066\u69cb\u7bc9\u3059\u308b\u6700\u7d42\u7684\u306a\u30a4\u30e1\u30fc\u30b8<\/h3>\n\n\n\n
\u4eca\u56de\u3001GPU\u30b3\u30f3\u30c6\u30ca\u304c\u52d5\u4f5c\u3059\u308b\u3068\u3053\u308d\u307e\u3067\u78ba\u8a8d\u3067\u304d\u307e\u3057\u305f\u3002\u6b21\u56de\u4ee5\u964d\u306f\u3044\u308d\u3044\u308d\u306a\u30d5\u30ec\u30fc\u30e0\u30ef\u30fc\u30af\u306b\u5bfe\u5fdc\u3057\u305fGPU\u30b3\u30f3\u30c6\u30ca\u306e\u4f5c\u6210\u3068\u5229\u7528\u65b9\u6cd5\u306b\u3064\u3044\u3066\u7d39\u4ecb\u3057\u307e\u3059\u3002\u4e0b\u56f3\u306e\u3088\u3046\u306a\u30a4\u30e1\u30fc\u30b8\u306e\u74b0\u5883\u304c\u51fa\u6765\u4e0a\u304c\u308a\u307e\u3059\u3002<\/p>\n\n\n
\n
\"\"<\/figure>\n<\/div>\n\n\n
\u6b21\u56de\u4e88\u544a \u7b2c2\u56de\uff1aTensorFlow\u3068Keras\u306b\u3088\u308b\u30c7\u30a3\u30fc\u30d7\u30e9\u30fc\u30cb\u30f3\u30b0<\/h2>\n\n\n\n
\u3044\u3088\u3044\u3088\u6b21\u56de\u304b\u3089\u5b9f\u969b\u306bGPU\u4e0a\u3067TensorFlow\u306a\u3069\u306e\u30e1\u30b8\u30e3\u30fc\u306a\u30d5\u30ec\u30fc\u30e0\u30ef\u30fc\u30af\u3092\u52d5\u304b\u3059\u305f\u3081\u306e\u30b3\u30f3\u30c6\u30ca\u306e\u6d3b\u7528\u3068\u8ab2\u984c\u306e\u89e3\u6c7a\u624b\u9806\u3092\u89e3\u8aac\u3057\u3066\u3044\u304d\u307e\u3059\u3002\u5148\u305a\u306fTensorFlow\u3068keras\u306b\u3088\u308b\u30c7\u30a3\u30fc\u30d7\u30e9\u30fc\u30cb\u30f3\u30b0\u30e2\u30c7\u30eb\u69cb\u7bc9\u4f5c\u696d\u306b\u53d6\u308a\u639b\u304b\u3063\u3066\u3044\u304d\u307e\u3059\u3002<\/mark>\u5b66\u7fd2\u6e08\u30e2\u30c7\u30eb\u306e\u4e00\u90e8\u3092\u5b66\u7fd2\u3057\u76f4\u3057\u3066\u5229\u7528\u3059\u308b\u8ee2\u79fb\u5b66\u7fd2\u3092\u52b9\u679c\u7684\u306b\u4f7f\u3048\u3070\u3001\u30bc\u30ed\u304b\u3089\u5b66\u7fd2\u3055\u305b\u308b\u5834\u5408\u3088\u308a\u3082\u3001\u5c11\u306a\u3044\u30c7\u30fc\u30bf\u3068\u77ed\u3044\u6642\u9593\u3067\u4e00\u5b9a\u306e\u7cbe\u5ea6\u3092\u51fa\u3059\u3053\u3068\u304c\u671f\u5f85\u3067\u304d\u307e\u3059\u3002<\/p>\n\n\n
\n
HPC\u30b5\u30fc\u30d3\u30b9 SX-Aurora TSUBASA \u30af\u30e9\u30a6\u30c9<\/div>
\n
NEC\u306e\u30b9\u30fc\u30d1\u30fc\u30b3\u30f3\u30d4\u30e5\u30fc\u30bf\u30fc\u300cSX-Aurora TSUBASA\u300d\u3092\u30af\u30e9\u30a6\u30c9\u74b0\u5883\u3067\u3054\u5229\u7528\u3067\u304d\u308b\u696d\u754c\u968f\u4e00\u306e\u30b5\u30fc\u30d3\u30b9\u3067\u3059\u3002<\/p>\n\n\n\n
\u4e16\u754c\u30c8\u30c3\u30d7\u30af\u30e9\u30b9\u306e\u30b9\u30da\u30c3\u30af\u3067\u5927\u898f\u6a21\u30c7\u30fc\u30bf\u306e\u9ad8\u901f\u51e6\u7406\u3092\u5b9f\u73fe\u3059\u308b\u30d9\u30af\u30c8\u30eb\u578b\u30b9\u30fc\u30d1\u30fc\u30b3\u30f3\u30d4\u30e5\u30fc\u30bf\u30fc\u3092\u3001\u6708\u984d\u5b9a\u984d\u6599\u91d1\u306e\u30af\u30e9\u30a6\u30c9\u30b5\u30fc\u30d3\u30b9\u3068\u3057\u3066\u5229\u7528\u3067\u304d\u307e\u3059\u3002<\/p>\n\n\n\n
\"\"<\/a><\/figure>\n<\/div><\/div>\n<\/div><\/div>
  
          
        \u3010\u9023\u8f09\u4f01\u753b\u3011GPU\u30b3\u30f3\u30c6\u30ca\u6d3b\u7528 \u3010\u51686\u56de\u3011<\/th>      <\/tr>    <\/thead>    
      
        GPU\u30b3\u30f3\u30c6\u30ca\u3068\u306f\u4f55\u304b\uff1f\u4f55\u304c\u4fbf\u5229\u306a\u306e\u304b\uff1f\u3010\u7b2c1\u56de\uff1aGPU\u30b3\u30f3\u30c6\u30ca\u3067\u901f\u653b\u74b0\u5883\u69cb\u7bc9\u3011        <\/td>      <\/tr>      
        TensorFlow\u3068Keras\u306b\u3088\u308b\u30c7\u30a3\u30fc\u30d7\u30e9\u30fc\u30cb\u30f3\u30b0\u2460\u3010\u7b2c2\u56de:GPU\u30b3\u30f3\u30c6\u30ca\u3067\u753b\u50cf\u89e3\u6790\u301c\u6e96\u5099\u7de8\u301c\u3011<\/a>        <\/td>      <\/tr>      
        TensorFlow\u3068Keras\u306b\u3088\u308b\u30c7\u30a3\u30fc\u30d7\u30e9\u30fc\u30cb\u30f3\u30b0\u2461\u3010\u7b2c3\u56de:GPU\u30b3\u30f3\u30c6\u30ca\u3067\u753b\u50cf\u89e3\u6790\u301c\u5b9f\u8df5\u7de8\u301c\u3011<\/a>        <\/td>      <\/tr>      
        Chainer\u3092\u4f7f\u3063\u305f\u30c7\u30a3\u30fc\u30d7\u30e9\u30fc\u30cb\u30f3\u30b0\u3010\u7b2c4\u56de:GPU\u30b3\u30f3\u30c6\u30ca\u3067\u6a5f\u68b0\u5b66\u7fd2\u3059\u308b\u3011<\/a>        <\/td>      <\/tr>      
        PyTorch\u3067\u6a5f\u68b0\u5b66\u7fd2\u3010\u7b2c5\u56de:GPU\u30b3\u30f3\u30c6\u30ca\u3067\u30c6\u30f3\u30bd\u30eb\u306e\u57fa\u672c\u3092\u7406\u89e3\u3059\u308b\u3011<\/a>        <\/td>      <\/tr>    <\/tbody>  <\/table><\/div>","protected":false},"excerpt":{"rendered":"\u3010\u9023\u8f09\u4f01\u753b\u3011GPU\u30b3\u30f3\u30c6\u30ca\u6d3b\u7528 \u3010\u51686\u56de\u3011 GPU\u30b3\u30f3\u30c6\u30ca\u3068\u306f\u4f55\u304b\uff1f\u4f55\u304c\u4fbf\u5229\u306a\u306e\u304b\uff1f\u3010\u7b2c1\u56de\uff1aGPU\u30b3\u30f3\u30c6\u30ca\u3067\u901f\u653b\u74b0\u5883\u69cb\u7bc9\u3011 TensorFlow\u3068Keras\u306b\u3088\u308b\u30c7\u30a3\u30fc\u30d7\u30e9\u30fc\u30cb\u30f3\u30b0\u2460\u3010\u7b2c2\u56de:GPU\u30b3\u30f3\u30c6\u30ca\u3067\u753b\u50cf\u89e3\u6790\u301c\u6e96\u5099\u7de8\u301c\u3011 TensorFlow\u3068Keras\u306b\u3088\u308b\u30c7\u30a3\u30fc\u30d7\u30e9\u30fc\u30cb\u30f3\u30b0\u2461\u3010\u7b2c3\u56de:GPU\u30b3\u30f3\u30c6\u30ca\u3067\u753b\u50cf […]","protected":false},"author":10,"featured_media":3319,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_coblocks_attr":"","_coblocks_dimensions":"","_coblocks_responsive_height":"","_coblocks_accordion_ie_support":"","footnotes":""},"categories":[145],"tags":[34,56,67,100],"pickup":[],"sitedisplay":[],"sitetarget":[],"class_list":["post-3316","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-hpc","tag-gpu","tag-56","tag-67","tag-hpc"],"yoast_head":"\nGPU\u30b3\u30f3\u30c6\u30ca\u3068\u306f\u4f55\u304b\uff1f\u4f55\u304c\u4fbf\u5229\u306a\u306e\u304b\uff1f\u3010\u7b2c1\u56de\uff1aGPU\u30b3\u30f3\u30c6\u30ca\u3067\u901f\u653b\u74b0\u5883\u69cb\u7bc9\u3011 - \u30ab\u30b4\u30e4\u306e\u30b5\u30fc\u30d0\u30fc\u7814\u7a76\u5ba4<\/title>\n<meta name=\"description\" content=\"\u9ad8\u901f\u63cf\u753b\u51e6\u7406\u304c\u5fc5\u8981\u3068\u3055\u308c\u308bCG\u3001VR\u30013DCAD\u7b49\u3067\u5229\u7528\u3055\u308c\u3066\u304d\u305fGPU\uff08Graphics Processing Unit\uff1a\u30b0\u30e9\u30d5\u30a3\u30c3\u30af\u30b9 \u30d7\u30ed\u30bb\u30c3\u30b7\u30f3\u30b0 \u672c\u9023\u8f09\u306f\u3001\u51685\u56de\u306e\u30b7\u30ea\u30fc\u30ba\u3092\u901a\u3057\u3066\u3067\u304d\u308b\u3060\u3051\u52b9\u7387\u7684\u306b\u3001GPU\u306e\u74b0\u5883\u69cb\u7bc9\u3092\u884c\u3046\u305f\u3081\u306b\u30b3\u30f3\u30c6\u30ca\u306e\u6d3b\u7528\u3092\u884c\u3063\u3066\u3044\u304d\u307e\u3059\u3002\u300c\u6a5f\u68b0\u5b66\u7fd2\u3084\u30c7\u30a3\u30fc\u30d7\u30e9\u30fc\u30cb\u30f3\u30b0\u3092GPU\u3067\u5b9f\u884c\u3057\u3066\u307f\u305f\u3044\u3051\u3069\u96e3\u3057\u305d\u3046\u2026\u300d\u306a\u3069\u5c0e\u5165\u306b\u30cf\u30fc\u30c9\u30eb\u3092\u611f\u3058\u3089\u308c\u3066\u3044\u308b\u65b9\u306b\u3001\u30b3\u30f3\u30c6\u30ca\u3092\u6d3b\u7528\u3059\u308b\u3053\u3068\u3067\u3001\u74b0\u5883\u69cb\u7bc9\u306b\u8981\u3059\u308b\u5de5\u6570\u3092\u5727\u5012\u7684\u306b\u524a\u6e1b\u3057\u3001\u5373\u5ea7\u306b\u8ab2\u984c\u306b\u53d6\u308a\u7d44\u3080\u3053\u3068\u304c\u3067\u304d\u308b\u30e1\u30ea\u30c3\u30c8\u3092\u611f\u3058\u3066\u3044\u305f\u3060\u304d\u307e\u3059\u3002\u305d\u306e\u305f\u3081\u306b\u5fc5\u8981\u306a\u77e5\u8b58\u3084\u64cd\u4f5c\u65b9\u6cd5\u3092\u3001\u5f53\u793e\u306eGPU\u30b5\u30fc\u30d0\u30fc\u3092\u4f7f\u3044\u89e3\u8aac\u3057\u3066\u3044\u304d\u307e\u3059\u3002\u9023\u8f09\u3092\u8aad\u307f\u7d42\u3048\u308b\u3053\u308d\u306b\u306f\u3001TensorFlow\u3084PyTorch\u306a\u3069\u306e\u30e1\u30b8\u30e3\u30fc\u306a\u30d5\u30ec\u30fc\u30e0\u30ef\u30fc\u30af\u3092\u4f7f\u3063\u305f\u6f14\u7fd2\u304c\u3067\u304d\u308b\u3088\u3046\u306b\u306a\u3063\u3066\u3044\u308b\u306f\u305a\u3067\u3059\u3002\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.kagoya.jp\/howto\/engineer\/hpc\/gpu-container1\/\" \/>\n<meta property=\"og:locale\" content=\"ja_JP\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"GPU\u30b3\u30f3\u30c6\u30ca\u3068\u306f\u4f55\u304b\uff1f\u4f55\u304c\u4fbf\u5229\u306a\u306e\u304b\uff1f\u3010\u7b2c1\u56de\uff1aGPU\u30b3\u30f3\u30c6\u30ca\u3067\u901f\u653b\u74b0\u5883\u69cb\u7bc9\u3011 - \u30ab\u30b4\u30e4\u306e\u30b5\u30fc\u30d0\u30fc\u7814\u7a76\u5ba4\" \/>\n<meta property=\"og:description\" content=\"\u9ad8\u901f\u63cf\u753b\u51e6\u7406\u304c\u5fc5\u8981\u3068\u3055\u308c\u308bCG\u3001VR\u30013DCAD\u7b49\u3067\u5229\u7528\u3055\u308c\u3066\u304d\u305fGPU\uff08Graphics Processing Unit\uff1a\u30b0\u30e9\u30d5\u30a3\u30c3\u30af\u30b9 \u30d7\u30ed\u30bb\u30c3\u30b7\u30f3\u30b0 \u672c\u9023\u8f09\u306f\u3001\u51685\u56de\u306e\u30b7\u30ea\u30fc\u30ba\u3092\u901a\u3057\u3066\u3067\u304d\u308b\u3060\u3051\u52b9\u7387\u7684\u306b\u3001GPU\u306e\u74b0\u5883\u69cb\u7bc9\u3092\u884c\u3046\u305f\u3081\u306b\u30b3\u30f3\u30c6\u30ca\u306e\u6d3b\u7528\u3092\u884c\u3063\u3066\u3044\u304d\u307e\u3059\u3002\u300c\u6a5f\u68b0\u5b66\u7fd2\u3084\u30c7\u30a3\u30fc\u30d7\u30e9\u30fc\u30cb\u30f3\u30b0\u3092GPU\u3067\u5b9f\u884c\u3057\u3066\u307f\u305f\u3044\u3051\u3069\u96e3\u3057\u305d\u3046\u2026\u300d\u306a\u3069\u5c0e\u5165\u306b\u30cf\u30fc\u30c9\u30eb\u3092\u611f\u3058\u3089\u308c\u3066\u3044\u308b\u65b9\u306b\u3001\u30b3\u30f3\u30c6\u30ca\u3092\u6d3b\u7528\u3059\u308b\u3053\u3068\u3067\u3001\u74b0\u5883\u69cb\u7bc9\u306b\u8981\u3059\u308b\u5de5\u6570\u3092\u5727\u5012\u7684\u306b\u524a\u6e1b\u3057\u3001\u5373\u5ea7\u306b\u8ab2\u984c\u306b\u53d6\u308a\u7d44\u3080\u3053\u3068\u304c\u3067\u304d\u308b\u30e1\u30ea\u30c3\u30c8\u3092\u611f\u3058\u3066\u3044\u305f\u3060\u304d\u307e\u3059\u3002\u305d\u306e\u305f\u3081\u306b\u5fc5\u8981\u306a\u77e5\u8b58\u3084\u64cd\u4f5c\u65b9\u6cd5\u3092\u3001\u5f53\u793e\u306eGPU\u30b5\u30fc\u30d0\u30fc\u3092\u4f7f\u3044\u89e3\u8aac\u3057\u3066\u3044\u304d\u307e\u3059\u3002\u9023\u8f09\u3092\u8aad\u307f\u7d42\u3048\u308b\u3053\u308d\u306b\u306f\u3001TensorFlow\u3084PyTorch\u306a\u3069\u306e\u30e1\u30b8\u30e3\u30fc\u306a\u30d5\u30ec\u30fc\u30e0\u30ef\u30fc\u30af\u3092\u4f7f\u3063\u305f\u6f14\u7fd2\u304c\u3067\u304d\u308b\u3088\u3046\u306b\u306a\u3063\u3066\u3044\u308b\u306f\u305a\u3067\u3059\u3002\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www.kagoya.jp\/howto\/engineer\/hpc\/gpu-container1\/\" \/>\n<meta property=\"og:site_name\" content=\"\u30ab\u30b4\u30e4\u306e\u30b5\u30fc\u30d0\u30fc\u7814\u7a76\u5ba4\" \/>\n<meta property=\"article:published_time\" content=\"2020-07-01T00:30:08+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2023-07-19T04:28:37+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/www.kagoya.jp\/howto\/wp-content\/uploads\/gpu202006b_cacth.png\" \/>\n\t<meta property=\"og:image:width\" content=\"1200\" \/>\n\t<meta property=\"og:image:height\" content=\"630\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/png\" \/>\n<meta name=\"author\" content=\"\u9db4\u5ca1 \u8b19\u543e\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"\u57f7\u7b46\u8005\" \/>\n\t<meta name=\"twitter:data1\" content=\"\u9db4\u5ca1 \u8b19\u543e\" \/>\n\t<meta name=\"twitter:label2\" content=\"\u63a8\u5b9a\u8aad\u307f\u53d6\u308a\u6642\u9593\" \/>\n\t<meta name=\"twitter:data2\" content=\"3\u5206\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\\\/\\\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\\\/\\\/www.kagoya.jp\\\/howto\\\/engineer\\\/hpc\\\/gpu-container1\\\/#article\",\"isPartOf\":{\"@id\":\"https:\\\/\\\/www.kagoya.jp\\\/howto\\\/engineer\\\/hpc\\\/gpu-container1\\\/\"},\"author\":{\"name\":\"\u9db4\u5ca1 \u8b19\u543e\",\"@id\":\"https:\\\/\\\/www.kagoya.jp\\\/howto\\\/#\\\/schema\\\/person\\\/df4e644df3b6b3d2d54b27fb8623fb9d\"},\"headline\":\"GPU\u30b3\u30f3\u30c6\u30ca\u3068\u306f\u4f55\u304b\uff1f\u4f55\u304c\u4fbf\u5229\u306a\u306e\u304b\uff1f\u3010\u7b2c1\u56de\uff1aGPU\u30b3\u30f3\u30c6\u30ca\u3067\u901f\u653b\u74b0\u5883\u69cb\u7bc9\u3011\",\"datePublished\":\"2020-07-01T00:30:08+00:00\",\"dateModified\":\"2023-07-19T04:28:37+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\\\/\\\/www.kagoya.jp\\\/howto\\\/engineer\\\/hpc\\\/gpu-container1\\\/\"},\"wordCount\":193,\"image\":{\"@id\":\"https:\\\/\\\/www.kagoya.jp\\\/howto\\\/engineer\\\/hpc\\\/gpu-container1\\\/#primaryimage\"},\"thumbnailUrl\":\"https:\\\/\\\/www.kagoya.jp\\\/howto\\\/wp-content\\\/uploads\\\/gpu202006b_cacth.png\",\"keywords\":[\"GPU\",\"\u30b3\u30f3\u30c6\u30ca\",\"\u5b66\u8853\",\"HPC\"],\"articleSection\":[\"AI\u30fbIoT\u30fbHPC\"],\"inLanguage\":\"ja\"},{\"@type\":\"WebPage\",\"@id\":\"https:\\\/\\\/www.kagoya.jp\\\/howto\\\/engineer\\\/hpc\\\/gpu-container1\\\/\",\"url\":\"https:\\\/\\\/www.kagoya.jp\\\/howto\\\/engineer\\\/hpc\\\/gpu-container1\\\/\",\"name\":\"GPU\u30b3\u30f3\u30c6\u30ca\u3068\u306f\u4f55\u304b\uff1f\u4f55\u304c\u4fbf\u5229\u306a\u306e\u304b\uff1f\u3010\u7b2c1\u56de\uff1aGPU\u30b3\u30f3\u30c6\u30ca\u3067\u901f\u653b\u74b0\u5883\u69cb\u7bc9\u3011 - \u30ab\u30b4\u30e4\u306e\u30b5\u30fc\u30d0\u30fc\u7814\u7a76\u5ba4\",\"isPartOf\":{\"@id\":\"https:\\\/\\\/www.kagoya.jp\\\/howto\\\/#website\"},\"primaryImageOfPage\":{\"@id\":\"https:\\\/\\\/www.kagoya.jp\\\/howto\\\/engineer\\\/hpc\\\/gpu-container1\\\/#primaryimage\"},\"image\":{\"@id\":\"https:\\\/\\\/www.kagoya.jp\\\/howto\\\/engineer\\\/hpc\\\/gpu-container1\\\/#primaryimage\"},\"thumbnailUrl\":\"https:\\\/\\\/www.kagoya.jp\\\/howto\\\/wp-content\\\/uploads\\\/gpu202006b_cacth.png\",\"datePublished\":\"2020-07-01T00:30:08+00:00\",\"dateModified\":\"2023-07-19T04:28:37+00:00\",\"author\":{\"@id\":\"https:\\\/\\\/www.kagoya.jp\\\/howto\\\/#\\\/schema\\\/person\\\/df4e644df3b6b3d2d54b27fb8623fb9d\"},\"description\":\"\u9ad8\u901f\u63cf\u753b\u51e6\u7406\u304c\u5fc5\u8981\u3068\u3055\u308c\u308bCG\u3001VR\u30013DCAD\u7b49\u3067\u5229\u7528\u3055\u308c\u3066\u304d\u305fGPU\uff08Graphics Processing Unit\uff1a\u30b0\u30e9\u30d5\u30a3\u30c3\u30af\u30b9 \u30d7\u30ed\u30bb\u30c3\u30b7\u30f3\u30b0 \u672c\u9023\u8f09\u306f\u3001\u51685\u56de\u306e\u30b7\u30ea\u30fc\u30ba\u3092\u901a\u3057\u3066\u3067\u304d\u308b\u3060\u3051\u52b9\u7387\u7684\u306b\u3001GPU\u306e\u74b0\u5883\u69cb\u7bc9\u3092\u884c\u3046\u305f\u3081\u306b\u30b3\u30f3\u30c6\u30ca\u306e\u6d3b\u7528\u3092\u884c\u3063\u3066\u3044\u304d\u307e\u3059\u3002\u300c\u6a5f\u68b0\u5b66\u7fd2\u3084\u30c7\u30a3\u30fc\u30d7\u30e9\u30fc\u30cb\u30f3\u30b0\u3092GPU\u3067\u5b9f\u884c\u3057\u3066\u307f\u305f\u3044\u3051\u3069\u96e3\u3057\u305d\u3046\u2026\u300d\u306a\u3069\u5c0e\u5165\u306b\u30cf\u30fc\u30c9\u30eb\u3092\u611f\u3058\u3089\u308c\u3066\u3044\u308b\u65b9\u306b\u3001\u30b3\u30f3\u30c6\u30ca\u3092\u6d3b\u7528\u3059\u308b\u3053\u3068\u3067\u3001\u74b0\u5883\u69cb\u7bc9\u306b\u8981\u3059\u308b\u5de5\u6570\u3092\u5727\u5012\u7684\u306b\u524a\u6e1b\u3057\u3001\u5373\u5ea7\u306b\u8ab2\u984c\u306b\u53d6\u308a\u7d44\u3080\u3053\u3068\u304c\u3067\u304d\u308b\u30e1\u30ea\u30c3\u30c8\u3092\u611f\u3058\u3066\u3044\u305f\u3060\u304d\u307e\u3059\u3002\u305d\u306e\u305f\u3081\u306b\u5fc5\u8981\u306a\u77e5\u8b58\u3084\u64cd\u4f5c\u65b9\u6cd5\u3092\u3001\u5f53\u793e\u306eGPU\u30b5\u30fc\u30d0\u30fc\u3092\u4f7f\u3044\u89e3\u8aac\u3057\u3066\u3044\u304d\u307e\u3059\u3002\u9023\u8f09\u3092\u8aad\u307f\u7d42\u3048\u308b\u3053\u308d\u306b\u306f\u3001TensorFlow\u3084PyTorch\u306a\u3069\u306e\u30e1\u30b8\u30e3\u30fc\u306a\u30d5\u30ec\u30fc\u30e0\u30ef\u30fc\u30af\u3092\u4f7f\u3063\u305f\u6f14\u7fd2\u304c\u3067\u304d\u308b\u3088\u3046\u306b\u306a\u3063\u3066\u3044\u308b\u306f\u305a\u3067\u3059\u3002\",\"breadcrumb\":{\"@id\":\"https:\\\/\\\/www.kagoya.jp\\\/howto\\\/engineer\\\/hpc\\\/gpu-container1\\\/#breadcrumb\"},\"inLanguage\":\"ja\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\\\/\\\/www.kagoya.jp\\\/howto\\\/engineer\\\/hpc\\\/gpu-container1\\\/\"]}]},{\"@type\":\"ImageObject\",\"inLanguage\":\"ja\",\"@id\":\"https:\\\/\\\/www.kagoya.jp\\\/howto\\\/engineer\\\/hpc\\\/gpu-container1\\\/#primaryimage\",\"url\":\"https:\\\/\\\/www.kagoya.jp\\\/howto\\\/wp-content\\\/uploads\\\/gpu202006b_cacth.png\",\"contentUrl\":\"https:\\\/\\\/www.kagoya.jp\\\/howto\\\/wp-content\\\/uploads\\\/gpu202006b_cacth.png\",\"width\":1200,\"height\":630},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\\\/\\\/www.kagoya.jp\\\/howto\\\/engineer\\\/hpc\\\/gpu-container1\\\/#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"\u30db\u30fc\u30e0\",\"item\":\"https:\\\/\\\/www.kagoya.jp\\\/howto\\\/\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"GPU\u30b3\u30f3\u30c6\u30ca\u3068\u306f\u4f55\u304b\uff1f\u4f55\u304c\u4fbf\u5229\u306a\u306e\u304b\uff1f\u3010\u7b2c1\u56de\uff1aGPU\u30b3\u30f3\u30c6\u30ca\u3067\u901f\u653b\u74b0\u5883\u69cb\u7bc9\u3011\"}]},{\"@type\":\"WebSite\",\"@id\":\"https:\\\/\\\/www.kagoya.jp\\\/howto\\\/#website\",\"url\":\"https:\\\/\\\/www.kagoya.jp\\\/howto\\\/\",\"name\":\"\u30ab\u30b4\u30e4\u306e\u30b5\u30fc\u30d0\u30fc\u7814\u7a76\u5ba4\",\"description\":\"\u30c7\u30fc\u30bf\u30bb\u30f3\u30bf\u30fc\u904b\u55b6\u4f1a\u793e\u304c\u304a\u5c4a\u3051\u3059\u308b\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u30e1\u30c7\u30a3\u30a2\",\"potentialAction\":[{\"@type\":\"SearchAction\",\"target\":{\"@type\":\"EntryPoint\",\"urlTemplate\":\"https:\\\/\\\/www.kagoya.jp\\\/howto\\\/?s={search_term_string}\"},\"query-input\":{\"@type\":\"PropertyValueSpecification\",\"valueRequired\":true,\"valueName\":\"search_term_string\"}}],\"inLanguage\":\"ja\"},{\"@type\":\"Person\",\"@id\":\"https:\\\/\\\/www.kagoya.jp\\\/howto\\\/#\\\/schema\\\/person\\\/df4e644df3b6b3d2d54b27fb8623fb9d\",\"name\":\"\u9db4\u5ca1 \u8b19\u543e\",\"image\":{\"@type\":\"ImageObject\",\"inLanguage\":\"ja\",\"@id\":\"https:\\\/\\\/secure.gravatar.com\\\/avatar\\\/3aa257cb88c81f1f1b20b69ff2c2449d9943b4413ede75b7abcb3d7e1cc78850?s=96&d=mm&r=g\",\"url\":\"https:\\\/\\\/secure.gravatar.com\\\/avatar\\\/3aa257cb88c81f1f1b20b69ff2c2449d9943b4413ede75b7abcb3d7e1cc78850?s=96&d=mm&r=g\",\"contentUrl\":\"https:\\\/\\\/secure.gravatar.com\\\/avatar\\\/3aa257cb88c81f1f1b20b69ff2c2449d9943b4413ede75b7abcb3d7e1cc78850?s=96&d=mm&r=g\",\"caption\":\"\u9db4\u5ca1 \u8b19\u543e\"},\"url\":\"https:\\\/\\\/www.kagoya.jp\\\/howto\\\/author\\\/tsuruoka\\\/\"}]}<\/script>\n<!-- \/ Yoast SEO plugin. -->","yoast_head_json":{"title":"GPU\u30b3\u30f3\u30c6\u30ca\u3068\u306f\u4f55\u304b\uff1f\u4f55\u304c\u4fbf\u5229\u306a\u306e\u304b\uff1f\u3010\u7b2c1\u56de\uff1aGPU\u30b3\u30f3\u30c6\u30ca\u3067\u901f\u653b\u74b0\u5883\u69cb\u7bc9\u3011 - \u30ab\u30b4\u30e4\u306e\u30b5\u30fc\u30d0\u30fc\u7814\u7a76\u5ba4","description":"\u9ad8\u901f\u63cf\u753b\u51e6\u7406\u304c\u5fc5\u8981\u3068\u3055\u308c\u308bCG\u3001VR\u30013DCAD\u7b49\u3067\u5229\u7528\u3055\u308c\u3066\u304d\u305fGPU\uff08Graphics Processing Unit\uff1a\u30b0\u30e9\u30d5\u30a3\u30c3\u30af\u30b9 \u30d7\u30ed\u30bb\u30c3\u30b7\u30f3\u30b0 \u672c\u9023\u8f09\u306f\u3001\u51685\u56de\u306e\u30b7\u30ea\u30fc\u30ba\u3092\u901a\u3057\u3066\u3067\u304d\u308b\u3060\u3051\u52b9\u7387\u7684\u306b\u3001GPU\u306e\u74b0\u5883\u69cb\u7bc9\u3092\u884c\u3046\u305f\u3081\u306b\u30b3\u30f3\u30c6\u30ca\u306e\u6d3b\u7528\u3092\u884c\u3063\u3066\u3044\u304d\u307e\u3059\u3002\u300c\u6a5f\u68b0\u5b66\u7fd2\u3084\u30c7\u30a3\u30fc\u30d7\u30e9\u30fc\u30cb\u30f3\u30b0\u3092GPU\u3067\u5b9f\u884c\u3057\u3066\u307f\u305f\u3044\u3051\u3069\u96e3\u3057\u305d\u3046\u2026\u300d\u306a\u3069\u5c0e\u5165\u306b\u30cf\u30fc\u30c9\u30eb\u3092\u611f\u3058\u3089\u308c\u3066\u3044\u308b\u65b9\u306b\u3001\u30b3\u30f3\u30c6\u30ca\u3092\u6d3b\u7528\u3059\u308b\u3053\u3068\u3067\u3001\u74b0\u5883\u69cb\u7bc9\u306b\u8981\u3059\u308b\u5de5\u6570\u3092\u5727\u5012\u7684\u306b\u524a\u6e1b\u3057\u3001\u5373\u5ea7\u306b\u8ab2\u984c\u306b\u53d6\u308a\u7d44\u3080\u3053\u3068\u304c\u3067\u304d\u308b\u30e1\u30ea\u30c3\u30c8\u3092\u611f\u3058\u3066\u3044\u305f\u3060\u304d\u307e\u3059\u3002\u305d\u306e\u305f\u3081\u306b\u5fc5\u8981\u306a\u77e5\u8b58\u3084\u64cd\u4f5c\u65b9\u6cd5\u3092\u3001\u5f53\u793e\u306eGPU\u30b5\u30fc\u30d0\u30fc\u3092\u4f7f\u3044\u89e3\u8aac\u3057\u3066\u3044\u304d\u307e\u3059\u3002\u9023\u8f09\u3092\u8aad\u307f\u7d42\u3048\u308b\u3053\u308d\u306b\u306f\u3001TensorFlow\u3084PyTorch\u306a\u3069\u306e\u30e1\u30b8\u30e3\u30fc\u306a\u30d5\u30ec\u30fc\u30e0\u30ef\u30fc\u30af\u3092\u4f7f\u3063\u305f\u6f14\u7fd2\u304c\u3067\u304d\u308b\u3088\u3046\u306b\u306a\u3063\u3066\u3044\u308b\u306f\u305a\u3067\u3059\u3002","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"https:\/\/www.kagoya.jp\/howto\/engineer\/hpc\/gpu-container1\/","og_locale":"ja_JP","og_type":"article","og_title":"GPU\u30b3\u30f3\u30c6\u30ca\u3068\u306f\u4f55\u304b\uff1f\u4f55\u304c\u4fbf\u5229\u306a\u306e\u304b\uff1f\u3010\u7b2c1\u56de\uff1aGPU\u30b3\u30f3\u30c6\u30ca\u3067\u901f\u653b\u74b0\u5883\u69cb\u7bc9\u3011 - \u30ab\u30b4\u30e4\u306e\u30b5\u30fc\u30d0\u30fc\u7814\u7a76\u5ba4","og_description":"\u9ad8\u901f\u63cf\u753b\u51e6\u7406\u304c\u5fc5\u8981\u3068\u3055\u308c\u308bCG\u3001VR\u30013DCAD\u7b49\u3067\u5229\u7528\u3055\u308c\u3066\u304d\u305fGPU\uff08Graphics Processing Unit\uff1a\u30b0\u30e9\u30d5\u30a3\u30c3\u30af\u30b9 \u30d7\u30ed\u30bb\u30c3\u30b7\u30f3\u30b0 \u672c\u9023\u8f09\u306f\u3001\u51685\u56de\u306e\u30b7\u30ea\u30fc\u30ba\u3092\u901a\u3057\u3066\u3067\u304d\u308b\u3060\u3051\u52b9\u7387\u7684\u306b\u3001GPU\u306e\u74b0\u5883\u69cb\u7bc9\u3092\u884c\u3046\u305f\u3081\u306b\u30b3\u30f3\u30c6\u30ca\u306e\u6d3b\u7528\u3092\u884c\u3063\u3066\u3044\u304d\u307e\u3059\u3002\u300c\u6a5f\u68b0\u5b66\u7fd2\u3084\u30c7\u30a3\u30fc\u30d7\u30e9\u30fc\u30cb\u30f3\u30b0\u3092GPU\u3067\u5b9f\u884c\u3057\u3066\u307f\u305f\u3044\u3051\u3069\u96e3\u3057\u305d\u3046\u2026\u300d\u306a\u3069\u5c0e\u5165\u306b\u30cf\u30fc\u30c9\u30eb\u3092\u611f\u3058\u3089\u308c\u3066\u3044\u308b\u65b9\u306b\u3001\u30b3\u30f3\u30c6\u30ca\u3092\u6d3b\u7528\u3059\u308b\u3053\u3068\u3067\u3001\u74b0\u5883\u69cb\u7bc9\u306b\u8981\u3059\u308b\u5de5\u6570\u3092\u5727\u5012\u7684\u306b\u524a\u6e1b\u3057\u3001\u5373\u5ea7\u306b\u8ab2\u984c\u306b\u53d6\u308a\u7d44\u3080\u3053\u3068\u304c\u3067\u304d\u308b\u30e1\u30ea\u30c3\u30c8\u3092\u611f\u3058\u3066\u3044\u305f\u3060\u304d\u307e\u3059\u3002\u305d\u306e\u305f\u3081\u306b\u5fc5\u8981\u306a\u77e5\u8b58\u3084\u64cd\u4f5c\u65b9\u6cd5\u3092\u3001\u5f53\u793e\u306eGPU\u30b5\u30fc\u30d0\u30fc\u3092\u4f7f\u3044\u89e3\u8aac\u3057\u3066\u3044\u304d\u307e\u3059\u3002\u9023\u8f09\u3092\u8aad\u307f\u7d42\u3048\u308b\u3053\u308d\u306b\u306f\u3001TensorFlow\u3084PyTorch\u306a\u3069\u306e\u30e1\u30b8\u30e3\u30fc\u306a\u30d5\u30ec\u30fc\u30e0\u30ef\u30fc\u30af\u3092\u4f7f\u3063\u305f\u6f14\u7fd2\u304c\u3067\u304d\u308b\u3088\u3046\u306b\u306a\u3063\u3066\u3044\u308b\u306f\u305a\u3067\u3059\u3002","og_url":"https:\/\/www.kagoya.jp\/howto\/engineer\/hpc\/gpu-container1\/","og_site_name":"\u30ab\u30b4\u30e4\u306e\u30b5\u30fc\u30d0\u30fc\u7814\u7a76\u5ba4","article_published_time":"2020-07-01T00:30:08+00:00","article_modified_time":"2023-07-19T04:28:37+00:00","og_image":[{"width":1200,"height":630,"url":"https:\/\/www.kagoya.jp\/howto\/wp-content\/uploads\/gpu202006b_cacth.png","type":"image\/png"}],"author":"\u9db4\u5ca1 \u8b19\u543e","twitter_card":"summary_large_image","twitter_misc":{"\u57f7\u7b46\u8005":"\u9db4\u5ca1 \u8b19\u543e","\u63a8\u5b9a\u8aad\u307f\u53d6\u308a\u6642\u9593":"3\u5206"},"schema":{"@context":"https:\/\/schema.org","@graph":[{"@type":"Article","@id":"https:\/\/www.kagoya.jp\/howto\/engineer\/hpc\/gpu-container1\/#article","isPartOf":{"@id":"https:\/\/www.kagoya.jp\/howto\/engineer\/hpc\/gpu-container1\/"},"author":{"name":"\u9db4\u5ca1 \u8b19\u543e","@id":"https:\/\/www.kagoya.jp\/howto\/#\/schema\/person\/df4e644df3b6b3d2d54b27fb8623fb9d"},"headline":"GPU\u30b3\u30f3\u30c6\u30ca\u3068\u306f\u4f55\u304b\uff1f\u4f55\u304c\u4fbf\u5229\u306a\u306e\u304b\uff1f\u3010\u7b2c1\u56de\uff1aGPU\u30b3\u30f3\u30c6\u30ca\u3067\u901f\u653b\u74b0\u5883\u69cb\u7bc9\u3011","datePublished":"2020-07-01T00:30:08+00:00","dateModified":"2023-07-19T04:28:37+00:00","mainEntityOfPage":{"@id":"https:\/\/www.kagoya.jp\/howto\/engineer\/hpc\/gpu-container1\/"},"wordCount":193,"image":{"@id":"https:\/\/www.kagoya.jp\/howto\/engineer\/hpc\/gpu-container1\/#primaryimage"},"thumbnailUrl":"https:\/\/www.kagoya.jp\/howto\/wp-content\/uploads\/gpu202006b_cacth.png","keywords":["GPU","\u30b3\u30f3\u30c6\u30ca","\u5b66\u8853","HPC"],"articleSection":["AI\u30fbIoT\u30fbHPC"],"inLanguage":"ja"},{"@type":"WebPage","@id":"https:\/\/www.kagoya.jp\/howto\/engineer\/hpc\/gpu-container1\/","url":"https:\/\/www.kagoya.jp\/howto\/engineer\/hpc\/gpu-container1\/","name":"GPU\u30b3\u30f3\u30c6\u30ca\u3068\u306f\u4f55\u304b\uff1f\u4f55\u304c\u4fbf\u5229\u306a\u306e\u304b\uff1f\u3010\u7b2c1\u56de\uff1aGPU\u30b3\u30f3\u30c6\u30ca\u3067\u901f\u653b\u74b0\u5883\u69cb\u7bc9\u3011 - \u30ab\u30b4\u30e4\u306e\u30b5\u30fc\u30d0\u30fc\u7814\u7a76\u5ba4","isPartOf":{"@id":"https:\/\/www.kagoya.jp\/howto\/#website"},"primaryImageOfPage":{"@id":"https:\/\/www.kagoya.jp\/howto\/engineer\/hpc\/gpu-container1\/#primaryimage"},"image":{"@id":"https:\/\/www.kagoya.jp\/howto\/engineer\/hpc\/gpu-container1\/#primaryimage"},"thumbnailUrl":"https:\/\/www.kagoya.jp\/howto\/wp-content\/uploads\/gpu202006b_cacth.png","datePublished":"2020-07-01T00:30:08+00:00","dateModified":"2023-07-19T04:28:37+00:00","author":{"@id":"https:\/\/www.kagoya.jp\/howto\/#\/schema\/person\/df4e644df3b6b3d2d54b27fb8623fb9d"},"description":"\u9ad8\u901f\u63cf\u753b\u51e6\u7406\u304c\u5fc5\u8981\u3068\u3055\u308c\u308bCG\u3001VR\u30013DCAD\u7b49\u3067\u5229\u7528\u3055\u308c\u3066\u304d\u305fGPU\uff08Graphics Processing Unit\uff1a\u30b0\u30e9\u30d5\u30a3\u30c3\u30af\u30b9 \u30d7\u30ed\u30bb\u30c3\u30b7\u30f3\u30b0 \u672c\u9023\u8f09\u306f\u3001\u51685\u56de\u306e\u30b7\u30ea\u30fc\u30ba\u3092\u901a\u3057\u3066\u3067\u304d\u308b\u3060\u3051\u52b9\u7387\u7684\u306b\u3001GPU\u306e\u74b0\u5883\u69cb\u7bc9\u3092\u884c\u3046\u305f\u3081\u306b\u30b3\u30f3\u30c6\u30ca\u306e\u6d3b\u7528\u3092\u884c\u3063\u3066\u3044\u304d\u307e\u3059\u3002\u300c\u6a5f\u68b0\u5b66\u7fd2\u3084\u30c7\u30a3\u30fc\u30d7\u30e9\u30fc\u30cb\u30f3\u30b0\u3092GPU\u3067\u5b9f\u884c\u3057\u3066\u307f\u305f\u3044\u3051\u3069\u96e3\u3057\u305d\u3046\u2026\u300d\u306a\u3069\u5c0e\u5165\u306b\u30cf\u30fc\u30c9\u30eb\u3092\u611f\u3058\u3089\u308c\u3066\u3044\u308b\u65b9\u306b\u3001\u30b3\u30f3\u30c6\u30ca\u3092\u6d3b\u7528\u3059\u308b\u3053\u3068\u3067\u3001\u74b0\u5883\u69cb\u7bc9\u306b\u8981\u3059\u308b\u5de5\u6570\u3092\u5727\u5012\u7684\u306b\u524a\u6e1b\u3057\u3001\u5373\u5ea7\u306b\u8ab2\u984c\u306b\u53d6\u308a\u7d44\u3080\u3053\u3068\u304c\u3067\u304d\u308b\u30e1\u30ea\u30c3\u30c8\u3092\u611f\u3058\u3066\u3044\u305f\u3060\u304d\u307e\u3059\u3002\u305d\u306e\u305f\u3081\u306b\u5fc5\u8981\u306a\u77e5\u8b58\u3084\u64cd\u4f5c\u65b9\u6cd5\u3092\u3001\u5f53\u793e\u306eGPU\u30b5\u30fc\u30d0\u30fc\u3092\u4f7f\u3044\u89e3\u8aac\u3057\u3066\u3044\u304d\u307e\u3059\u3002\u9023\u8f09\u3092\u8aad\u307f\u7d42\u3048\u308b\u3053\u308d\u306b\u306f\u3001TensorFlow\u3084PyTorch\u306a\u3069\u306e\u30e1\u30b8\u30e3\u30fc\u306a\u30d5\u30ec\u30fc\u30e0\u30ef\u30fc\u30af\u3092\u4f7f\u3063\u305f\u6f14\u7fd2\u304c\u3067\u304d\u308b\u3088\u3046\u306b\u306a\u3063\u3066\u3044\u308b\u306f\u305a\u3067\u3059\u3002","breadcrumb":{"@id":"https:\/\/www.kagoya.jp\/howto\/engineer\/hpc\/gpu-container1\/#breadcrumb"},"inLanguage":"ja","potentialAction":[{"@type":"ReadAction","target":["https:\/\/www.kagoya.jp\/howto\/engineer\/hpc\/gpu-container1\/"]}]},{"@type":"ImageObject","inLanguage":"ja","@id":"https:\/\/www.kagoya.jp\/howto\/engineer\/hpc\/gpu-container1\/#primaryimage","url":"https:\/\/www.kagoya.jp\/howto\/wp-content\/uploads\/gpu202006b_cacth.png","contentUrl":"https:\/\/www.kagoya.jp\/howto\/wp-content\/uploads\/gpu202006b_cacth.png","width":1200,"height":630},{"@type":"BreadcrumbList","@id":"https:\/\/www.kagoya.jp\/howto\/engineer\/hpc\/gpu-container1\/#breadcrumb","itemListElement":[{"@type":"ListItem","position":1,"name":"\u30db\u30fc\u30e0","item":"https:\/\/www.kagoya.jp\/howto\/"},{"@type":"ListItem","position":2,"name":"GPU\u30b3\u30f3\u30c6\u30ca\u3068\u306f\u4f55\u304b\uff1f\u4f55\u304c\u4fbf\u5229\u306a\u306e\u304b\uff1f\u3010\u7b2c1\u56de\uff1aGPU\u30b3\u30f3\u30c6\u30ca\u3067\u901f\u653b\u74b0\u5883\u69cb\u7bc9\u3011"}]},{"@type":"WebSite","@id":"https:\/\/www.kagoya.jp\/howto\/#website","url":"https:\/\/www.kagoya.jp\/howto\/","name":"\u30ab\u30b4\u30e4\u306e\u30b5\u30fc\u30d0\u30fc\u7814\u7a76\u5ba4","description":"\u30c7\u30fc\u30bf\u30bb\u30f3\u30bf\u30fc\u904b\u55b6\u4f1a\u793e\u304c\u304a\u5c4a\u3051\u3059\u308b\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u30e1\u30c7\u30a3\u30a2","potentialAction":[{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https:\/\/www.kagoya.jp\/howto\/?s={search_term_string}"},"query-input":{"@type":"PropertyValueSpecification","valueRequired":true,"valueName":"search_term_string"}}],"inLanguage":"ja"},{"@type":"Person","@id":"https:\/\/www.kagoya.jp\/howto\/#\/schema\/person\/df4e644df3b6b3d2d54b27fb8623fb9d","name":"\u9db4\u5ca1 \u8b19\u543e","image":{"@type":"ImageObject","inLanguage":"ja","@id":"https:\/\/secure.gravatar.com\/avatar\/3aa257cb88c81f1f1b20b69ff2c2449d9943b4413ede75b7abcb3d7e1cc78850?s=96&d=mm&r=g","url":"https:\/\/secure.gravatar.com\/avatar\/3aa257cb88c81f1f1b20b69ff2c2449d9943b4413ede75b7abcb3d7e1cc78850?s=96&d=mm&r=g","contentUrl":"https:\/\/secure.gravatar.com\/avatar\/3aa257cb88c81f1f1b20b69ff2c2449d9943b4413ede75b7abcb3d7e1cc78850?s=96&d=mm&r=g","caption":"\u9db4\u5ca1 \u8b19\u543e"},"url":"https:\/\/www.kagoya.jp\/howto\/author\/tsuruoka\/"}]}},"views":44482,"_links":{"self":[{"href":"https:\/\/www.kagoya.jp\/howto\/wp-json\/wp\/v2\/posts\/3316","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.kagoya.jp\/howto\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.kagoya.jp\/howto\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.kagoya.jp\/howto\/wp-json\/wp\/v2\/users\/10"}],"replies":[{"embeddable":true,"href":"https:\/\/www.kagoya.jp\/howto\/wp-json\/wp\/v2\/comments?post=3316"}],"version-history":[{"count":0,"href":"https:\/\/www.kagoya.jp\/howto\/wp-json\/wp\/v2\/posts\/3316\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.kagoya.jp\/howto\/wp-json\/wp\/v2\/media\/3319"}],"wp:attachment":[{"href":"https:\/\/www.kagoya.jp\/howto\/wp-json\/wp\/v2\/media?parent=3316"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.kagoya.jp\/howto\/wp-json\/wp\/v2\/categories?post=3316"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.kagoya.jp\/howto\/wp-json\/wp\/v2\/tags?post=3316"},{"taxonomy":"pickup","embeddable":true,"href":"https:\/\/www.kagoya.jp\/howto\/wp-json\/wp\/v2\/pickup?post=3316"},{"taxonomy":"sitedisplay","embeddable":true,"href":"https:\/\/www.kagoya.jp\/howto\/wp-json\/wp\/v2\/sitedisplay?post=3316"},{"taxonomy":"sitetarget","embeddable":true,"href":"https:\/\/www.kagoya.jp\/howto\/wp-json\/wp\/v2\/sitetarget?post=3316"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}