tensor.to_sparse() Memory Allocation

This page summarizes the projects mentioned and recommended in the original post on /r/pytorch

InfluxDB - Power Real-Time Data Analytics at Scale
Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
www.influxdata.com
featured
SaaSHub - Software Alternatives and Reviews
SaaSHub helps you find the best software and product alternatives
www.saashub.com
featured

  • DOKSparse

    sparse DOK tensors on GPU, pytorch

    • If using sparse tensors is a must, you can look into DOK sparse format, which is supported for 2d matrices in scipy. it kinda allows you to access any element of the sparse tensor in constant time, which makes it possible to create your tensor directly in sparse format, skipping the need to create a dense numpy array first. In case you need a GPU version of this, I have a library that implements sparse dok tensor in pytorch and cuda. currently it's GPU only.

  • InfluxDB

    Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

    InfluxDB 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