Case Studyaieimage processingamd ryzen aimemory optimization
AMD Ryzen AI Optimizes Color Image Negative Conversion
7.1
This session demonstrates how to use the Trace feature to implement and optimize color image negative conversion on AMD Ryzen AI Phoenix, using AIE dialects and AIE API. Engineers traced a 3-core design with 1,286,000 ns lock stalls and redesigned it to a 1-core approach with 320,000 ns per-component lock stalls, consolidating buffers and DMA channels to cut memory footprint and improve utilization.
Key Points
- 1Combine RGB channels into one AIE core, reducing lock stalls and core contention
- 2Lower lock stalls (1,286,000ns to 320,000ns) improves throughput and AIE utilization
- 3Reduce memory footprint by converting ping-pong buffers to single buffers, easing on-chip pressure
Scoring Rationale
Actionable, measurable optimization guidance for AMD NPU; limited scope and single-source session focused on Phoenix-specific implementation.
Sources
Public references used for this report.
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