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Experience using QuickLogic IP to optimize AI/ML performance on FPGA?
Posted: Wed Sep 24, 2025 1:48 am
by lyly19
Hello everyone,
I am learning about how to utilize QuickLogic's core IP for AI/ML applications running on an FPGA. I see some documents discussing eFPGA and supporting tools, but I am unsure how people have implemented it in practice to optimize performance and reduce latency.
Pokerogue
Has anyone done AI/ML projects on an FPGA with QuickLogic and can share their experiences, challenges, and optimization tips?
Thank you very much!
Re: Experience using QuickLogic IP to optimize AI/ML performance on FPGA?
Posted: Mon Oct 13, 2025 2:47 am
by speedstars
Have you tried using the QuickAI or EOS S3 platform for your experiments yet? I’m curious how the performance compared to traditional FPGA setups.
Re: Experience using QuickLogic IP to optimize AI/ML performance on FPGA?
Posted: Thu Dec 11, 2025 9:38 am
by lasagnevolcanic
Run INT8/INT4 instead of float32 to save LUTs/DSPs/BRAM and increase throughput. This is best practice on most FPGAs/MCU-MLs. Have you tried it yet?
Re: Experience using QuickLogic IP to optimize AI/ML performance on FPGA?
Posted: Mon Dec 15, 2025 9:30 am
by wstagnat
The biggest challenges tend to be memory bandwidth and tool-flow iteration, but starting with a small kernel and scaling up works well.
Re: Experience using QuickLogic IP to optimize AI/ML performance on FPGA?
Posted: Wed Jan 21, 2026 2:23 am
by Owenburrows
My brain cells felt like they were in a gladiatorial arena. One project, we wrestled with a neural network model, struggling to port it efficiently. It was a true test of my Slice Master skills and patience to make those circuits hum.
Re: Experience using QuickLogic IP to optimize AI/ML performance on FPGA?
Posted: Thu Feb 12, 2026 4:29 am
by CharlesVikulte
Hey everyone, I'm diving into AI/ML on QuickLogic FPGAs and exploring eFPGA capabilities. The documentation is helpful, but real-world examples are scarce. Has anyone tackled similar AI/ML projects using QuickLogic? I'm particularly interested in your experiences, hurdles faced, and any optimization secrets you've discovered. Pokerogue is a fun game.
Re: Experience using QuickLogic IP to optimize AI/ML performance on FPGA?
Posted: Mon Feb 23, 2026 7:20 am
by ElizabethHorton
Okay, intriguing post! So, AI/ML on FPGAs, eh? Sounds complex. Optimizing for performance is always a tightrope walk, and latency, ugh, the bane of real-time processing. eFPGA, always seemed like a gamble. I faced a similar memory constraint challenge when trying to get a neural network to run on a resource-limited embedded platform for a robotics project. It felt like wrangling a digital serpent, a bit like trying to get a high score in Slither io.
Re: Experience using QuickLogic IP to optimize AI/ML performance on FPGA?
Posted: Thu Mar 05, 2026 8:52 am
by annakena
It’s great to see your interest in using QuickLogic's core IP for AI/ML on FPGAs. Learning from others' experiences can be invaluable, much like mastering the game through practice and strategy. Good luck, and I hope you find some helpful insights!
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