In our recent analysis of Figure 35 from ALLEGRO , we explored the optimization landscape without ๐-constraints and the outcomes were remarkable.
๐ Key finding: Even in the absence of constraint tuning (indicated by “inf”), we identified a feasible solution that achieves energy and cost levels within 20% of their unconstrained optima. This highlights a surprising compatibility between energy efficiency and cost-effectiveness, an encouraging trait for practical applications that value both.
๐ Delay dynamics: We observed that as the ๐-constraint is relaxed, delay drops significantly. At ๐ = 100% (where energy and cost can double from their optima), delay approaches its optimal value a favorable trade-off in latency-sensitive scenarios.
๐ธ Cost vs. others: Interestingly, when optimizing only for cost, the system shows less responsiveness to ๐ changes. Even with substantial relaxations (up to 200% deviation for energy and delay), cost remains suboptimal. This points to a strong competitive tension between cost and the other objectives.
These findings are shaping how we think about multi-objective optimization in complex, real-world systemsโwhere achieving balance is often more powerful than absolute optimization.
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