Upgrade to Pro — share decks privately, control downloads, hide ads and more …

How we use GPUs in Cookpad

How we use GPUs in Cookpad

@Tokyo Machine Learning Kitchen
https://tokyo-ml.github.io/

Yuichiro Someya

November 06, 2017
Tweet

More Decks by Yuichiro Someya

Other Decks in Programming

Transcript

  1. 

  2.  All-in on AWS since 2011 Amazon S3 (Object Storage)

    Amazon RDS (Relational Data) Amazon Redshift (Data Warehouse)
  3.  All-in on AWS since 2011 Amazon S3 (Object Storage)

    Amazon RDS (Relational Data) Amazon Redshift (Data Warehouse) 7JSUVBM1SJWBUF$MPVE
  4. 7JSUVBM1SJWBUF$MPVE  All-in on AWS since 2011 Amazon S3 (Object

    Storage) Amazon RDS (Relational Data) Amazon Redshift (Data Warehouse) Amazon EC2 (Computation)
  5.  ‣ $6%" ‣ DV%// (Snapshot) ‣ $6%" ‣ DV%//

    CUDA9 cuDNN7 CUDA8 cuDNN7 CUDA8 cuDNN6
  6.  ‣ $6%" ‣ DV%// (Snapshot) ‣ $6%" ‣ DV%//

    CUDA9 cuDNN7 CUDA8 cuDNN7 CUDA8 cuDNN6
  7.  ‣ $6%" ‣ DV%// (Snapshot) ‣ $6%" ‣ DV%//

    CUDA9 cuDNN7 CUDA8 cuDNN7 CUDA8 cuDNN6
  8.  ‣ $6%" ‣ DV%// (Snapshot) ‣ $6%" ‣ DV%//

    IUUQTBXTBNB[PODPNBNB[POBJBNJT CUDA9 cuDNN7 CUDA8 cuDNN7 CUDA8 cuDNN6
  9.  CUDA9 cuDNN7 CUDA8 cuDNN7 CUDA8 cuDNN6 ... `ssh` ...

    AWS Lambda (Function) Stop! Idle? (Hourly)
  10.  CUDA9 cuDNN7 CUDA8 cuDNN7 CUDA8 cuDNN6 ... `ssh` ...

    AWS Lambda (Function) Stop! Idle? (Hourly)