Here's how PYTORCH.ORG makes money* and how much!

*Please read our disclaimer before using our estimates.
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PYTORCH . ORG {}

Detected CMS Systems:

  1. Analyzed Page
  2. Matching Content Categories
  3. CMS
  4. Monthly Traffic Estimate
  5. How Does Pytorch.org Make Money
  6. How Much Does Pytorch.org Make
  7. Wordpress Themes And Plugins
  8. Keywords
  9. Topics
  10. Social Networks
  11. External Links
  12. Analytics And Tracking
  13. Libraries
  14. Hosting Providers

We are analyzing https://pytorch.org/blog/optimized-pytorch-w-graviton/.

Title:
Optimized PyTorch 2.0 Inference with AWS Graviton processors – PyTorch
Description:
No description found...
Website Age:
8 years and 10 months (reg. 2016-08-15).

Matching Content Categories {📚}

  • Education
  • Technology & Computing
  • Games

Content Management System {📝}

What CMS is pytorch.org built with?


Pytorch.org is built with WORDPRESS. But there are also traces of other content systems on the page (hubspot, 1woocommerce).

Traffic Estimate {📈}

What is the average monthly size of pytorch.org audience?

💥 Very Strong Traffic: 200k - 500k visitors per month


Based on our best estimate, this website will receive around 250,019 visitors per month in the current month.
However, some sources were not loaded, we suggest to reload the page to get complete results.

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How Does Pytorch.org Make Money? {💸}


E-COMMERCE {🛒}


Pytorch.org is an e-commerce website built with wordpress. Below, we provide further estimates of its revenues.

How Much Does Pytorch.org Make? {💰}

Wordpress Themes and Plugins {🎨}

What WordPress theme does this site use?

What WordPress plugins does this website use?

Keywords {🔍}

pytorch, inference, performance, aws, graviton, instances, install, instance, model, view, resnet, acl, profiler, optimized, cost, gravitonbased, models, image, onednn, python, pip, kernels, bfloat, diagram, operator, blog, compute, resources, arm, times, compared, graph, shows, latency, gemm, optimizations, primitive, objects, time, tutorials, speed, development, measured, amazon, results, optimization, library, backend, aarch, cpu,

Topics {✒️}

amazon-sagemaker-examples github repo torch hub resnet-50 previously called “mkl-dnn” general-purpose processors offer graviton3-based c7g instance main content join graviton3-based c7g instances making graviton-based instances set environment variables operator host duration aws ml blog real-time inference endpoint graviton3-based instances pytorch inference running /pytorch/benchmark amazon ec2 arm-based processors previous pytorch release started tutorials learn onednn resources update sudo apt events pytorch inference performance profiler supports ‘overview inference performance improvement existing hardware solutions latest news aws graviton processors automate performance benchmarking distilbert sentiment analysis roberta sentiment analysis linux foundation® linux foundation implemented primitive caching preceding trace view pytorch level optimizations simd hardware utilization automatic mixed precision roberta fill mask projects related announcements low operating cost achieve cost benefit inference recommender notebooks compute library tensor allocation overhead software development manager ideep operator level onednn primitive caching profiler operator view

External Links {🔗}(18)

Analytics and Tracking {📊}

  • Google Analytics
  • Google Analytics 4
  • Google Tag Manager
  • HubSpot

Libraries {📚}

  • Animate.css
  • Anime.js
  • Fancybox
  • FontAwesome
  • Foundation
  • jQuery
  • jQuery module (jquery)
  • jQuery module (jquery-migrate)
  • Lightbox
  • Masonry
  • Parallax.js
  • Prism.js
  • Select2
  • Swiper
  • Video.js
  • Waypoints
  • Zoom.js

Emails and Hosting {✉️}

Mail Servers:

  • aspmx.l.google.com
  • alt1.aspmx.l.google.com
  • alt2.aspmx.l.google.com
  • alt3.aspmx.l.google.com
  • alt4.aspmx.l.google.com

Name Servers:

  • ns1.dnsimple.com
  • ns2.dnsimple-edge.net
  • ns3.dnsimple.com
  • ns4.dnsimple-edge.org
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