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Pier – New VM Platform and Programming Language

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Pier – New VM Platform and Programming Language

Hey folks, This is a large hobby project I've been working on to create a new VM platform called Pier. The platform spec is currently private but the code for the compiler and VM is published on my GitHub. Most of my effort over the years has gone towards designing the Pier bytecode and working on the VM, so the language is rather limited right now. Many features that would typically require you to choose specific APIs like GL/Vulkan/D3D are defined as custom APIs provided natively by Pier bytecode - the platform effectively provides an abstraction layer that allows the VM to be implemented on top of various different APIs. I took this further by defining a custom shader bytecode IR format, which gets translated to a shading language (like GLSL) by the VM. Currently Pier is limited to Linux, but I intend to port the VM to Windows soon which should be a trivial task. Let me know what you think!

Visit productView on Hacker NewsNov 9, 2022
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Product HuntOn track for Day 1 leaderboard · Strong signals: new, code, apis · Missing: mac, agents, macos
81%81% predicted probability of success on Product Hunt, 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
80%80% predicted probability of success on Hacker News, 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
78%78% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: platform, soon · Missing: plus, intuitive, reviews
45%45% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
31%31% 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
17%17% 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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