mmap_ninja: Speedup your training dramatically by using memory-mapped files for your dataset

This page summarizes the projects mentioned and recommended in the original post on /r/Python
fast-data-pipeline image-augmentation data-augmentation Image processing Data processing

WorkOS
Our great sponsors
  • WorkOS - The modern identity platform for B2B SaaS
  • InfluxDB - Power Real-Time Data Analytics at Scale
  • SaaSHub - Software Alternatives and Reviews
Our great sponsors

  • mmap.ninja

    Memory mapped numpy arrays of varying shapes

  • DALI

    A GPU-accelerated library containing highly optimized building blocks and an execution engine for data processing to accelerate deep learning training and inference applications.

    • Small question if you are using GPU: How to this compare to GPUDirect Storage from Nvidia? can you have even more speedup by using both? I never toy with it, but the DALI project from Nvidia seem to tackle the same data loading problem.

  • WorkOS

    The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.

    WorkOS logo
NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a more popular project.

Suggest a related project

Related posts