Icicle viability gate: AI inference benchmark on H100 decides go/no-go

Situation

Set a clear decision gate for the Icicle project: viability is determined by performance on a real-world AI inference workload, not synthetic benchmarks. Omer to run the RLC Pro AI benchmark on an H100 GPU. 2-3x synthetic CPU/memory degradation is acceptable IF power savings are significant for AI inference; otherwise project gets punted.

Reasoning

Synthetic CPU/memory benchmarks are not the workload that matters for the customer thesis. Bjorn wanted a customer-environment test (per Anis DM); the actual go/no-go signal comes from AI inference, not contrived stressors. Setting a single explicit gate (real AI inference on H100) prevents the project from drifting through ambiguous results — it forces a decision rather than letting incremental data accumulate without conclusion. This mirrors the strategy-first/tactics-second framework from the Brady coaching: define the strategic question (does this work for AI inference) before getting lost in tactical numbers (synthetic perf hits).

Additional Context

Initial synthetic results show 2-3x slower on CPU/memory bound tests at 100% utilization. Team of 5 across Nathan and Ryan orgs running tests; Ahmer doing testing, Jeff Uphoff working with him on AI benchmark setup. Targeting v4.3. A few more days required. Ani Fox confirmed Bjorn wanted a customer-environment test.

Observed Evidence

Fathom decision statement plus two same-day Slack messages: setting workload version (v4.3) and reporting initial 2-3x degradation. Three independent sources confirm the gate is real AI inference, not synthetic.

Matching Patterns

Confidence Breakdown

Reasoning Depth Analysis