Showing 1 open source project for "parallel computing datamaning"

View related business solutions
  • Deploy Apps in Seconds with Cloud Run Icon
    Deploy Apps in Seconds with Cloud Run

    Host and run your applications without the need to manage infrastructure. Scales up from and down to zero automatically.

    Cloud Run is the fastest way to deploy containerized apps. Push your code in Go, Python, Node.js, Java, or any language and Cloud Run builds and deploys it automatically. Get fast autoscaling, pay only when your code runs, and skip the infrastructure headaches. Two million requests free per month. And new customers get $300 in free credit.
    Try Cloud Run Free
  • Managed MySQL, PostgreSQL, and SQL Databases on Google Cloud Icon
    Managed MySQL, PostgreSQL, and SQL Databases on Google Cloud

    Get back to your application and leave the database to us. Cloud SQL automatically handles backups, replication, and scaling.

    Cloud SQL is a fully managed relational database for MySQL, PostgreSQL, and SQL Server. We handle patching, backups, replication, encryption, and failover—so you can focus on your app. Migrate from on-prem or other clouds with free Database Migration Service. IDC found customers achieved 246% ROI. New customers get $300 in credits plus a 30-day free trial.
    Try Cloud SQL Free
  • 1

    Ezys

    Ezys 3D medical image registration program

    Ezys is a non-linear 3D medical image registration program. Ezys fully exploits the parallel computing power of inexpensive commercial graphics processing units (GPU), resulting in a very fast and accurate program capable of running on desktop PCs and even some laptops. On these systems, non-linear image registrations take less than a minute to complete. Ezys implements a diffeomorphic inverse consistent image registration algorithm with a demons-style regularization based on a non-parametric free form deformation model. ...
    Downloads: 0 This Week
    Last Update:
    See Project
  • Previous
  • You're on page 1
  • Next
MongoDB Logo MongoDB