The Lambda
deep learning blog

Published on June 3, 2022 by Chuan Li

If you're interested in training the next large transformer like DALL-E, Imagen, or BERT, a single GPU (or even single 8x GPU instance!) might not be enough ...

Published on April 19, 2022 by Kathy Bui

After a period of closed beta, we're excited to announce that persistent storage for Lambda GPU Cloud is now available for all A6000 and V100 instances in an ...

Published on July 16, 2021 by Stephen Balaban

Deep learning engineers and researchers spend too much time managing their infrastructure. Fortune 500 companies, startups, and universities are forced to ...

Published on April 23, 2021 by Remy Guercio

Update: 1-GPU NVIDIA RTX A6000 instances, starting at $1.00 / hr, are now available

Published on October 29, 2020 by Remy Guercio

Starting today you can now spin up virtual machines with 1, 2, or 4 NVIDIA® Quadro RTX™ 6000 GPUs on Lambda's GPU cloud. We’ve built this new general purpose ...

Published on May 13, 2020 by Remy Guercio

With most (if not all) machine learning and deep learning researchers and engineers now working from home due to COVID-19, we’ve seen a massive increase in the ...

Published on May 3, 2020 by Remy Guercio

You can now use Lambda Cloud High Speed Filesystems to permanently store data on the Lambda Cloud. Click here to learn how to use Lambda Cloud Filesystems.

Published on May 3, 2020 by Remy Guercio

This guide will walk you through the process of launching a Lambda Cloud GPU instance and using SSH to log in. While we offer both a Web Terminal and Jupyter ...

Published on February 17, 2019 by Stephen Balaban

CPU, GPU, and I/O utilization monitoring using tmux, htop, iotop, and nvidia-smi. This stress test is running on a Lambda GPU Cloud 4x GPU instance. Often ...

Published on January 25, 2019 by Stephen Balaban

These slides are from my talk at Rework Deep Learning Summit 2019.