Key improvements:
- Add timeout mechanism (2s) for result ordering to prevent slow devices from blocking pipeline
- Implement performance-biased load balancing with 2x penalty for low-GOPS devices (< 10 GOPS)
- Adjust KL520 GOPS from 3 to 2 for more accurate performance representation
- Remove KL540 references to focus on available hardware
- Add intelligent sequence skipping with timeout results for better throughput
This resolves the issue where multi-series mode had lower FPS than single KL720
due to KL520 devices creating bottlenecks in the result ordering queue.
Performance impact:
- Reduces KL520 task allocation from ~12.5% to ~5-8%
- Prevents pipeline stalls from slow inference results
- Maintains result ordering integrity with timeout fallback
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
- Fix mflow_converter to properly handle multi-series configuration creation
- Update InferencePipeline to correctly initialize MultiDongle with multi-series config
- Add comprehensive multi-series configuration validation in mflow_converter
- Enhance deployment dialog to display multi-series configuration details
- Improve analysis and configuration tabs to show proper multi-series info
This resolves the issue where multi-series mode was falling back to single-series
during inference initialization, ensuring proper multi-series dongle support.
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
