A Vulkan-Video-based game streaming tool for Linux

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I've been working for about 6 months on a new game streaming/remote desktop tool for linux. Gaming on linux is pretty exciting right now, given all the improvements in compatibility, but game streaming isn't really there yet, and the remote desktop space is fairly underdeveloped too. The server acts as a wayland compositor to get the streamed app or game to render completely off-screen (somewhat like Gamescope, if you're familiar), and it uses Vulkan Video to pass the app's rendered textures directly to the encoder ASIC on the same card. The result is very fast and very low-latency, without a lot of moving parts. Running on the same machine, I get about 15-20ms median latency round-trip (from user input to the frame responding to that input being displayed on the client), which is about one frame at 60fps. The client is the weakest link right now, but I'm working on a Swift UI macOS/tvOS client that should be a bit nicer to use. You'll also need a reasonably strong GPU to run the server. Thanks for reading and checking it out! And please leave a bug report if it doesn't work for you, it's quite new and I've basically only tested it on my setup. Running the server with `--bug-report` will dump a video capture and trace log to a folder in /tmp, which you can attach to the report.

Visit product View on Hacker NewsApr 27, 2024

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Product HuntOn track for Day 1 leaderboard · Strong signals: mac, macos, user · Missing: agents, agent, cursor

77%77% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

74%74% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: ide · Missing: https docs, excited, just released

70%70% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

TrustMRRFits verified-revenue profile · Strong signals: video, month, way · Missing: mobile apps, ios, personal

54%54% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

33%33% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

15%15% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

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