GPU Acceleration
GPUs and integrated graphics unlock massive parallelism for vision, analytics, and UI rendering. This tag covers when GPU acceleration pays off on embedded boards, and how to size memory bandwidth and power delivery to avoid bottlenecks. We discuss compute APIs, zero-copy pipelines from cameras to shaders, and how to profile kernels to reach deterministic latencies. Examples show hybrid CPU/GPU/NPU pipelines and fallback behavior when thermals clamp frequencies. Useful for teams moving beyond CPU-only designs but who still need predictable real-time performance.
AMD Ryzen Embedded SBCs: Graphics & AI at the Edge
An in-depth look at how AMD Ryzen Embedded SBCs deliver powerful graphics and AI acceleration for edge computing applications, from industrial automation to …
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