算法艺术创作
algorithmic-art
通过代码和可调参数创作生成艺术与交互式视觉效果。
analysis【设计与创意】Tune generated hls4ml designs with profiling, automatic precision inference, bit-exact propagation, resource knobs, FIFO depth, BramFactor, and optimization API guardrails.
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Use this sub-skill after a model has already been converted, or after a frontend sub-skill has produced an hls_config that needs tuning. It helps future agents profile numerical ranges, choose or validate precisions, reason about bit-exact conversion, tune resource/latency knobs, and avoid overclaiming hardware results.
references/profiling.md.Precision: auto, granularity='name', quantizer-derived precision, or bit_exact: read references/precision-and-bit-exact.md.ReuseFactor, Strategy, FIFO depth optimization, BramFactor, or resource/latency tradeoffs: read references/resource-tuning.md.references/optimization-api.md before importing optimization APIs.references/troubleshooting.md.scripts/inspect_precision_config.py to print a tiny granularity='name' config and the paths where precision/reuse keys live.frontends sub-skill.backends.extensions.compile()/predict() parity as numerical evidence only. It is not synthesis evidence, resource utilization evidence, or FIFO-deadlock evidence.ortools dependency did not resolve for Python 3.11. See references/optimization-api.md for the safe runtime interpretation.