Clocks, workload,
and the energy between requests.
Paired measurements are available; latency-qualified adaptive savings have not been established.
Exploratory paired resultObserved held-out comparison: Adaptive candidate had 0.77% lower GPU energy across 8 valid matched pairs relative to the paired fixed setting; the largest TTFT and mean-ITL ratios were 1.029 and 1.009. This aggregate is descriptive; latency and selection qualification are reported separately.
Observed held-out comparison: GPU-managed clocks had 11.50% higher GPU energy across 8 valid matched pairs relative to the paired fixed setting; the largest TTFT and mean-ITL ratios were 1.077 and 1.037. This aggregate is descriptive; latency and selection qualification are reported separately.
On one 64-request code rate_2x development block, requested 660 MHz had 26.37% lower GPU energy than 210 MHz, with p95 time to first token changing from 111.45 to 26.53 seconds. Mean board power rose from 33.40 to 40.53 W; completion time fell from 238.05 to 144.45 seconds. The 660 MHz request delivered a 350.26 MHz time-weighted mean. This single-block contrast is descriptive and does not establish adaptive savings or a common winner across sources.
On one 64-request conversation rate_4x development block, requested 660 MHz had 4.04% higher GPU energy than 210 MHz, with p95 time to first token changing from 7.63 to 3.36 seconds. Mean board power rose from 39.24 to 42.28 W; completion time fell from 168.50 to 162.66 seconds. The 660 MHz request delivered a 250.19 MHz time-weighted mean. This single-block contrast is descriptive and does not establish adaptive savings or a common winner across sources.
Prefill-heavy probes: at requested 660 versus 210 MHz, whole-workload GPU energy was 31.60% lower at concurrency 1 (2 matched repetitions); 29.95% lower at concurrency 4 (2 matched repetitions). These request-shape comparisons do not isolate exact GPU phase energy.
Decode-heavy probes: at requested 660 versus 210 MHz, whole-workload GPU energy was 0.30% lower at concurrency 1 (2 matched repetitions); 0.47% lower at concurrency 4 (2 matched repetitions). These request-shape comparisons do not isolate exact GPU phase energy. Singleton decode reported 54.8–55.4 W mean board power despite the configured 40 W limit; the discrepancy is unresolved and lacks physical-meter validation.
Long-context generation probes: at requested 660 versus 210 MHz, whole-workload GPU energy was 3.33% lower at concurrency 1 (2 matched repetitions); 10.41% lower at concurrency 4 (2 matched repetitions). These request-shape comparisons do not isolate exact GPU phase energy.
The retained inventory contains 80 independently valid completed trials, 3 invalid outcomes, and 13 unstarted outcomes.
The adaptive-candidates-v3-20260906T162440Z acquisition failed start-temperature admission before any request was dispatched. Its final window was 65 °C against the unchanged 62 °C ceiling after 180.03 seconds. No serving energy, latency, or adaptive-policy result was measured; the failed and unstarted outcomes remain in the inventory.
The invalid dev_conversation_fixed_2040 record reports a watchdog interruption with 55/64 requests completed and a sampled peak temperature of 77 °C. It contributes no energy or latency comparison point; subsequent unstarted trials remain missing.
The dev_conversation_demand_phase trial in adaptive-candidates-fresh-v3-20260906T164810Z failed conditioning before any request for that trial was dispatched. Its independently verified no-serving outcome supplies no energy, latency, or policy-performance measurement. Earlier completed trials in that acquisition remain separate evidence.
Thermal admission
Prefill and decode diagnostics
Probe clock realization and board power
Five-clock workload comparison
Requested versus observed clocks
Client-visible activity under fixed 660 MHz
| Source timing | Streaming-only time | Actual 210 during streaming | 1–3 streams duration | Actual 210 during 1–3 streams |
|---|---|---|---|---|
| Code rate_2x | 8.73% | 90.46% | 8.245 s | 99.88% |
| Conversation rate_4x | 64.30% | 88.82% | 9.182 s | 100.00% |
The GPU already delivered 210 MHz through nearly all recorded streaming-only intervals with one to three outstanding requests. These client-state exposures are not exact GPU phases, policy residency, an energy-savings bound, or an irreducible power floor. The policy also uses 0.2-second observations and 2-second holds; its effect requires measured commands, clocks, latency and energy. Held-out mixtures can differ.
Adaptive energy and latency
Clock changes during serving
What the measurements support
Energy is derived from NVIDIA GPU telemetry; it does not cover the whole server or provider bill and was not checked with a physical power meter. Short diagnostic requests do not isolate exact GPU prefill/decode energy. The bounded temperature rule establishes a start ceiling, not thermal equilibrium or matched starting temperatures. All comparison methods retain the configured 40 W power limit, 6,251 MHz memory setting, and 77/79 °C watchdogs. The configured limit is not an assertion that measured board power stayed below 40 W. New causal policies are separate from the existing governor/MPC, whose calibration requirements remain unmet. Repeated blocks share trace requests and acquisitions; a small exploratory study cannot establish a population-wide savings estimate.
Invalid, unstarted, and pending outcomes are retained in the downloadable summary. They supply no plotted energy or latency value. An unmeasured result is never displayed as zero.
Methods and interpretation
Primary replay timing: Code rate_2x; Conversation rate_4x. Each case retains its source request identities and complete token lengths.
Conversation gaps are multiplied by one half relative to the original rate_2x cases; code timing is unchanged. The original conversation rate_2x thermal failure remains secondary evidence and supplies no revised latency target.
The 73 °C post-trial gate checks completion and thermal margin after the first dense conversation trial. It is distinct from the unchanged 62 °C start admission and the 77/79 °C watchdogs. A completed valid trial above 73 °C remains descriptive evidence and cannot support selection.
5 predecessor code fixed-setting trials are marked for primary reuse; the independent import audit verifies exactly the five settings. Other predecessor trials remain diagnostic or secondary evidence.
The intended comparison has 8 global paired groups per comparator. Acquisitions separated by source do not reduce that total or add independent samples.
A 900-second allowance per conditioning attempt applies to adaptive-candidates-continuation-v3-20260906T174213Z, adaptive-heldout-code-rep1-v3-20260906T182420Z, adaptive-heldout-code-rep2-v3-20260906T210116Z, adaptive-heldout-conversation-rep1-v3-20260906T193105Z, adaptive-heldout-conversation-rep2-v3-20260906T201736Z. Earlier acquisitions retain their recorded 180-second allowances and outcomes. The extension gives more time to reach the same 62 °C, ten-second admission window; it does not establish thermal equilibrium. Allowances are recorded separately for each acquisition in the report data.
Trace attribution: Azure LLM Inference Dataset 2023, released under CC BY 4.0. Credit: Pratyush Patel, Esha Choukse, Chaojie Zhang, Aashaka Shah, Inigo Goiri, Saeed Maleki, and Ricardo Bianchini, Splitwise: Efficient generative LLM inference using phase splitting, ISCA 2024. Official release: https://github.com/Azure/AzurePublicDataset/blob/master/AzureLLMInferenceDataset2023.md. Our adaptations select 64-request blocks, rescale arrival timing, and replay recorded token lengths using synthetic repeated-token-ID prompts.
Azure traces supply request timing and input/output token counts, not original prompt text. The runner uses synthetic repeated token-ID prompts, temperature zero, ignored end-of-sequence tokens, and exact requested output lengths, with prefix caching disabled. These measurements do not validate semantic production workloads.
The fixed baseline is one common setting selected on development workloads. It is not an oracle that selects a different clock for each held-out block. The demand/phase versus idle-only policy comparison is a development ablation; only the selected policy enters held-out evaluation.
A null savings result when realized clocks collapse to the same values cannot distinguish an ineffective policy from inadequate clock-control authority. Requested-clock labels alone do not establish a distinct physical operating point.
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