Compiler Playground for energy-efficient embedded dataflow processor

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Hi HN! My team at Efficient Computer ( https://efficient.computer ) and I are working on a new computer architecture and I am leading the team that is building the compiler for our chip. Our hardware is focused on energy-constrained embedded applications and is super efficient, which lets devices run for years on a small (ie AA) battery. We built a playground for our compiler that has a cool visualizer and debugger that shows how your C code (more languages to come) maps to our Fabric architecture, and an energy model that shows you how much less energy your code uses on our architecture. Check it out: https://www.efficient.computer/resources/effcc-compiler-play...

Visit product View on Hacker NewsFeb 27, 2025

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

73%73% predicted probability of success on Hacker News, based on ML models trained on real launch data.

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Product HuntOn track for Day 1 leaderboard · Strong signals: model, computer, new · Missing: mac, agents, macos

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

64%64% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

51%51% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

37%37% 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

21%21% 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

3%3% predicted probability of success on BetaList, based on ML models trained on real launch data.

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