BlazingDB Blog GPU-Accelerated Python on AWS

BlazingSQL + RAPIDS Stack now live on AWS MarketplaceData science on GPUs is one-click away with our latest offering. BlazingSQL + RAPIDS Stack is now available on the AWS Marketplace.With a few easy steps, you can launch your own GPU-powered data science workstation at the push of a button. All the power of high-performance data science with none of the complexity.Securely deploy an instance that’s preloaded with the latest GPU-accelerated data science packages in your AWS account; and, a few minutes later, access a high-performance JupyterLab environment — capable of querying terabyte-scale datasets — through a password protected URL.Get StartedYou can find BlazingSQL + RAPIDS Stack on the AWS Marketplace.From our product page, you simply need to click Continue to Subscribe.You can review our terms and conditions (we use the Standard Contract for AWS Marketplace) and click Continue to Configuration.To configure your instance by selecting your Fulfillment Option (we only support AMI presently), Software Version, and Region, then click Continue to Launch.In order to launch you will need to:Select the EC2 Instance TypeSelect the VPC and Subnet of your choiceSelect the Security Group (the seller settings expose all necessary ports publicly, choose unique IP addresses for increased security)Select the Key Pair of your choiceLaunchPlease wait for 2–3 minutes as the server is created and deployed.Then you simply go to the instance’s IP address to open JupyterLab.The password for your JupyterLab server is the marketplace instance’s Instance ID.And that’s it!You have now launched a BlazingSQL + RAPIDS data science workstation.Run through our demo notebooks and get started with GPU-accelerated Python now!GPU-Accelerated Python on AWS was originally published in BlazingSQL on Medium, where people are continuing the conversation by highlighting and responding to this story.