Setup a gpu optimized spark/hadoop cluster with docker compose
Hey folks, I figured this might be useful for a few people who want to play with hadoop and spark locally. Feedback hugely appreciated. I built this from the pain of wanting to setup a cluster for demos. I have gpu bits in there due to the use case but figured maybe some could draw inspiration from this. Happy to answer questions if there's any interest. Link here: https://github.com/deeplearning4j/docker
Setup a gpu optimized spark/hadoop cluster with docker compose launched on October 27, 2016 with 7 votes and more than 50% of that year's launches.
Does a similar job
all alternatives →- TCTensorDock Core GPU Cloud – GPU servers from $0.29/hr2022 · tensordock.com · ▲147
Hello HN! I’m Jonathan from TensorDock. After 7 months in beta, we’re finally launching Core Cloud, our platform to deploy GPU virtual machines in as little as 45 seconds! https://www.tensordock.com/product-core Why? Training machine learning workloads at large clouds can be extremely expensive. This left us wondering, “how did cloud ever become more expensive than on-prem?” I’ve seen too many ML startups buy their own hardware. Cheaper dedicated servers with NVIDIA GPUs are not too hard to find, but they lack the functionality and scalability of the big clouds. We thought to…
I've built a nice home server OSApr 2026 · lightwhale.asklandd.dk · ▲194ohai! I've released Lightwhale 3, which is possibly the easiest way to self-host Docker containers. It's a free, immutable Linux system purpose-built to live-boot straight into a working Docker Engine, thereby shortcutting the need for installation, configuration, and maintenance. Its simple design makes it easy to learn, and its low memory footprint should make it especially attractive during these times of RAMageddon. If this has piqued your interest, do check it out, along with its easy-to-follow Getting Started guide. In any event, have a nice day! =)
Dockerized GPU Deep Learning Solution (Code and Blog and TensorFlow Demo)2016 · github.com · ▲80An on-premises, bare-metal solution for deploying GPU-powered applications in containers - emergingstack/es-dev-stack
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Nextjournal – seamless data science for teams2019 · nextjournal.com · ▲170Runs anything you can put into a Docker container. Improve your workflow with polyglot notebooks, automatic versioning and real-time collaboration. Save time and money with on-demand provisioning, including GPU support. Use it for ML, data science, runnable tutorials, for your classroom or scientifi

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