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Beating Microsoft's Garnet KV Store in less than 300 lines of code

Hacker News

Beating Microsoft's Garnet KV Store in less than 300 lines of code

I saw Microsoft's Garnet getting to the limits of (CPU) concurrent hashmap performance and thought it would be interesting to see if I could beat it with a GPU. Specifically, the GET throughput at 256M keys. Of course, a few lines of hacky code doesn't get one very much, but it's enough to connect a to remote hashmap and throw integers around. Redis got 1.5-1.7 Mop/s.

Visit productView on Hacker NewsMar 23, 2024
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Actual performance

3points
2comments
Did not reach leaderboard

Launch Intel predictions

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Hacker NewsStrong engagement from HN community · Missing: https docs, excited, just released
78%78% 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 · Missing: mobile apps, ios, personal
54%54% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
54%54% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Strong signals: code · Missing: mac, agents, macos
43%43% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
25%25% 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
9%9% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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