I made a Web shooter in C++ with no engine. Fully deterministic netcode

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GitHub: https://github.com/TeamHypersomnia/Hypersomnia - The netcode relies on full simulation determinism - this includes Box2D physics. I'm using standard floating-point calculations and rely on IEEE754 compliance. I also use STREFLOP for portable math function implementations. This is commonly done for RTS games with a lot of synchronized units, however this technique is rarely if ever seen in games with complex physics, esp. shooters. - The atlas packer I wrote for the game was reused in Assassin's Creed, Skydio and received 2 scientific references: https://github.com/TeamHypersomnia/rectpack2D - You can play ranked matches in the browser after signing in with Discord. Your MMR is based on the OpenSkill library. - Browser clients and native clients (Windows, Linux, MacOS) can play on the same servers thanks to libdatachannel and datachannel-wasm. Host a server from your browser and connect from the Steam version, or vice versa. - I use LLVM to build it for all platforms: Windows, Linux, MacOS. I use Emscripten to compile it to WebAssembly. - There were significant challenges in making Box2D suitable for this, e.g. it comes without operator= so I had to implement complete cloning of the physical world for when I have to roll back the predicted world to reconcile it with the server state. Note it's not enough to just recreate the b2World from velocities and positions - you have to clone all contacts, generated trees, and all cached state so that the order of subsequent operations stays identical. Read more about the interesting tech aspects of the game here: https://github.com/TeamHypersomnia/Hypersomnia#tech-highligh...

Visit product View on Hacker NewsJun 9, 2024

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

66%66% 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, io · Missing: https docs, excited, just released

66%66% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

AppSumoStrong fit for a featured deal · Strong signals: platform, host · Missing: plus, intuitive, reviews

57%57% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

55%55% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

TrustMRRFits verified-revenue profile · Missing: mobile apps, ios, personal

50%50% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

13%13% 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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