![\"\"](\"https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F372520%2Fbcc9b9ac24d17e5aca656743bbf6c5c7%2FTPUv3.png?generation=1581382407172014&alt=media\")
When I saw this competition, I browsed through to understand how is it different, included below are some info for you to understand. If there are other articlkes which I have missed, I request you to share it in the comments please.
\n\nTPU Hardware is a Domain specific Hardware built ground up with Machine Learning in view.\n
TPU in general is several times faster and a quick comparison speaks it all.\n![\"\"](\"https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F372520%2F09df232b6c4548356c253a44a3b441fd%2FTPUvsGPU.png?generation=1581382677694818&alt=media\")
A graphical representation of running MNIST in avilable in the link here and switching into Animation Mode, Please go throught the presentation too which gives a history about this Domain specific Hardware.
A really goos article comparing performance is this from Tim Dettmers himself.
Notes:\n1. Images and references are from link
", "messages": [ { "id": "741861", "postDate": "02/11/2020 01:15:54", "content": "When I saw this competition, I browsed through to understand how is it different, included below are some info for you to understand. If there are other articlkes which I have missed, I request you to share it in the comments please.
\n\nTPU Hardware is a Domain specific Hardware built ground up with Machine Learning in view.\n
TPU in general is several times faster and a quick comparison speaks it all.\n
A graphical representation of running MNIST in avilable in the link here and switching into Animation Mode, Please go throught the presentation too which gives a history about this Domain specific Hardware.
A really goos article comparing performance is this from Tim Dettmers himself.
Notes:\n1. Images and references are from link
", "rawMarkdown": "When I saw this competition, I browsed through to understand how is it different, included below are some info for you to understand. If there are other articlkes which I have missed, I request you to share it in the comments please.\n\nTPU Hardware is a Domain specific Hardware built ground up with Machine Learning in view.\n\n\nTPU in general is several times faster and a quick comparison speaks it all.\n\n\n- A graphical representation of running MNIST in avilable in the link [here](https://storage.googleapis.com/nexttpu/index.html) and switching into Animation Mode, Please go throught the presentation too which gives a history about this Domain specific Hardware.\n\n- A really goos article comparing performance is this from [Tim Dettmers](https://timdettmers.com/2018/10/17/tpus-vs-gpus-for-transformers-bert/) himself.\n\nNotes:\n1. Images and references are from [link](https://cloud.google.com/tpu)", "votes": null }, { "id": "741890", "postDate": "02/11/2020 01:48:35", "content": "I have a TPU tutorial with a lot of additional info here: Keras and modern convnets on TPUs.
\n\nBy the way, and spoiler alert, the TPU sample (Five flowers with Keras and Xception on TPU) you have in the Kaggle TPU docs is the final and best model from the tutorial.
", "rawMarkdown": "I have a TPU tutorial with a lot of additional info here: [Keras and modern convnets on TPUs](https://codelabs.developers.google.com/codelabs/keras-flowers-tpu/#0).\n\nBy the way, and spoiler alert, the TPU sample ([Five flowers with Keras and Xception on TPU](https://www.kaggle.com/mgornergoogle/five-flowers-with-keras-and-xception-on-tpu)) you have in the [Kaggle TPU docs](https://www.kaggle.com/docs/tpu) is the final and best model from the tutorial.", "votes": null } ], "comments": [ { "id": 741890, "author_name": "mgorner", "author_url": "", "post_date": "02/11/2020 01:48:35", "content": "I have a TPU tutorial with a lot of additional info here: Keras and modern convnets on TPUs.
\n\nBy the way, and spoiler alert, the TPU sample (Five flowers with Keras and Xception on TPU) you have in the Kaggle TPU docs is the final and best model from the tutorial.
", "votes": null, "replies": [] } ], "raw_markdown_by_id": { "741861": "When I saw this competition, I browsed through to understand how is it different, included below are some info for you to understand. If there are other articlkes which I have missed, I request you to share it in the comments please.\n\nTPU Hardware is a Domain specific Hardware built ground up with Machine Learning in view.\n\n\nTPU in general is several times faster and a quick comparison speaks it all.\n\n\n- A graphical representation of running MNIST in avilable in the link [here](https://storage.googleapis.com/nexttpu/index.html) and switching into Animation Mode, Please go throught the presentation too which gives a history about this Domain specific Hardware.\n\n- A really goos article comparing performance is this from [Tim Dettmers](https://timdettmers.com/2018/10/17/tpus-vs-gpus-for-transformers-bert/) himself.\n\nNotes:\n1. Images and references are from [link](https://cloud.google.com/tpu)", "741890": "I have a TPU tutorial with a lot of additional info here: [Keras and modern convnets on TPUs](https://codelabs.developers.google.com/codelabs/keras-flowers-tpu/#0).\n\nBy the way, and spoiler alert, the TPU sample ([Five flowers with Keras and Xception on TPU](https://www.kaggle.com/mgornergoogle/five-flowers-with-keras-and-xception-on-tpu)) you have in the [Kaggle TPU docs](https://www.kaggle.com/docs/tpu) is the final and best model from the tutorial." }, "source": "meta" }