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Paper Citation Record · LEDGER

Evaluating MFU as a Proxy for GPU Power for Energy-Aware Simulation of LLM Training

As of 14 August 2026, this Paper Citation Record lists 32 of 32 outbound references and 0 inbound Pith citation observations for arXiv:2608.03880.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2608.03880 v1

Coverage vector

measured 32 of 32 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T10:31:32.063715Z

measured 32 of 32 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

32 of 32 outbound references displayed

  • verified exact1
  • verified fuzzy26
  • unresolved5
  • parse uncertain0
  • malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation e13f4b67-8eca-44be-a70e-01e37a14dda2 · outbound

This paper cites Double-Exponential Increases in Inference Energy: The Cost of the Race for Accuracy.

Evaluating MFU as a Proxy for GPU Power for Energy-Aware Simulation of LLM Training Double-Exponential Increases in Inference Energy: The Cost of the Race for Accuracy

Reference 1

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unresolved
no resolver link, observed 2026-08-05T10:31:31.955513Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation f7ca0bba-8b28-4ddd-85a7-9d53d957d28a · outbound

This paper cites GPU-NEST: Characterizing energy efficiency of multi-GPU inference servers,.

Evaluating MFU as a Proxy for GPU Power for Energy-Aware Simulation of LLM Training GPU-NEST: Characterizing energy efficiency of multi-GPU inference servers,

Reference 2

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verified fuzzy
raw_fallback, observed 2026-08-05T10:31:32.425694Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation b5bfea1b-064a-4d9f-a381-e91bbfbf48da · outbound

This paper cites Energy and AI,.

Evaluating MFU as a Proxy for GPU Power for Energy-Aware Simulation of LLM Training Energy and AI,

Reference 3

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raw_fallback, observed 2026-08-05T10:31:32.414562Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 207a01b4-4d4f-45f7-8027-4b64ac3c6d71 · outbound

This paper cites Comparative study of hardware and software power measurements in video compression,.

Evaluating MFU as a Proxy for GPU Power for Energy-Aware Simulation of LLM Training Comparative study of hardware and software power measurements in video compression,

Reference 4

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raw_fallback, observed 2026-08-05T10:31:32.404943Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 8485b926-5931-49b0-8ef5-5a0439b92830 · outbound

This paper cites Environmental report 2024,.

Evaluating MFU as a Proxy for GPU Power for Energy-Aware Simulation of LLM Training Environmental report 2024,

Reference 5

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raw_fallback, observed 2026-08-05T10:31:32.394403Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 85286c77-9a23-4b37-969e-972730eb61c2 · outbound

This paper cites Vidur: A large-scale simulation frame- work for llm inference,.

Evaluating MFU as a Proxy for GPU Power for Energy-Aware Simulation of LLM Training Vidur: A large-scale simulation frame- work for llm inference,

Reference 6

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raw_fallback, observed 2026-08-05T10:31:32.384325Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 6951e949-2728-4007-8e62-1e3b9863a58c · outbound

This paper cites SimuMax: A simulator for distributed LLM training,.

Evaluating MFU as a Proxy for GPU Power for Energy-Aware Simulation of LLM Training SimuMax: A simulator for distributed LLM training,

Reference 7

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raw_fallback, observed 2026-08-05T10:31:32.374011Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-05T10:31:31.978777Z digest=sha256:db3f2abb86d861f09c33cb7eb06a39c03231fc0126ab4de4f55cc683951729c8

Observation 829244c7-e3fd-413a-9bb7-ea91088a76d2 · outbound

This paper cites LLM Cluster Simulator: Interactive distributed training and inference planning,.

Evaluating MFU as a Proxy for GPU Power for Energy-Aware Simulation of LLM Training LLM Cluster Simulator: Interactive distributed training and inference planning,

Reference 8

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raw_fallback, observed 2026-08-05T10:31:32.363272Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 598096d7-591d-49cf-814b-133af5a5243e · outbound

This paper cites The one-token model,.

Evaluating MFU as a Proxy for GPU Power for Energy-Aware Simulation of LLM Training The one-token model,

Reference 9

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verified fuzzy
raw_fallback, observed 2026-08-05T10:31:32.353146Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 6291b193-882e-49ba-ab30-9ce69a1c4d70 · outbound

This paper cites Understanding gpu power: A survey of profiling, modeling, and simulation methods,.

Evaluating MFU as a Proxy for GPU Power for Energy-Aware Simulation of LLM Training Understanding gpu power: A survey of profiling, modeling, and simulation methods,

Reference 10

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verified fuzzy
raw_fallback, observed 2026-08-05T10:31:32.343185Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 8ed182d3-cdc3-47da-ac10-1bd1c72986e3 · outbound

This paper cites PaLM: scaling language modeling with pathways,.

Evaluating MFU as a Proxy for GPU Power for Energy-Aware Simulation of LLM Training PaLM: scaling language modeling with pathways,

Reference 11

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verified fuzzy
raw_fallback, observed 2026-08-05T10:31:32.332514Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 2ad2bd19-326f-4e76-8474-09653fa68bd4 · outbound

This paper cites Vidur: A large-scale simulation frame- work for LLM inference,.

Evaluating MFU as a Proxy for GPU Power for Energy-Aware Simulation of LLM Training Vidur: A large-scale simulation frame- work for LLM inference,

Reference 12

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verified fuzzy
raw_fallback, observed 2026-08-05T10:31:32.322610Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-05T10:31:31.994418Z digest=sha256:6d13f40cde03eaaf11d6f85232e8153641f70fab39f96159c2cee74272ac7bd4

Observation c6eeb4de-279b-4fb4-9b30-a610569a50a4 · outbound

This paper cites Quantifying the energy consumption and carbon emissions of LLM inference via simulations,.

Evaluating MFU as a Proxy for GPU Power for Energy-Aware Simulation of LLM Training Quantifying the energy consumption and carbon emissions of LLM inference via simulations,

Reference 13

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verified fuzzy
raw_fallback, observed 2026-08-05T10:31:32.312212Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 6fc9fb1d-c0e0-4db3-8eda-5721ee5e23c0 · outbound

This paper cites Extracting practical, actionable energy insights from supercomputer telemetry and logs,.

Evaluating MFU as a Proxy for GPU Power for Energy-Aware Simulation of LLM Training Extracting practical, actionable energy insights from supercomputer telemetry and logs,

Reference 14

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verified fuzzy
raw_fallback, observed 2026-08-05T10:31:32.301995Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation ea9b7f26-ea6c-4443-b121-91fa062e15a5 · outbound

This paper cites [Online].

Evaluating MFU as a Proxy for GPU Power for Energy-Aware Simulation of LLM Training [Online]

Reference 15

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verified fuzzy
raw_fallback, observed 2026-08-05T10:31:32.291821Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 5e0ad4ea-57be-4ed1-a69e-83f551d01f69 · outbound

This paper cites Using model FLOPs utilization (MFU),.

Evaluating MFU as a Proxy for GPU Power for Energy-Aware Simulation of LLM Training Using model FLOPs utilization (MFU),

Reference 16

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raw_fallback, observed 2026-08-05T10:31:32.281399Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 2f16ae59-f37b-4855-94a8-b554d198df4e · outbound

This paper cites an unresolved cited work.

Evaluating MFU as a Proxy for GPU Power for Energy-Aware Simulation of LLM Training Unresolved cited work

Reference 17

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unresolved
raw_fallback, observed 2026-08-05T10:31:32.269308Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 88822de5-34e2-4224-a826-aa6591081ebe · outbound

This paper cites Monitoring and characterizing GPU usage,.

Evaluating MFU as a Proxy for GPU Power for Energy-Aware Simulation of LLM Training Monitoring and characterizing GPU usage,

Reference 18

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verified fuzzy
raw_fallback, observed 2026-08-05T10:31:32.258921Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 99d9b14d-40d4-40c4-ad3b-6100ed08cc5b · outbound

This paper cites Accurate and convenient energy measurements for GPUs: A detailed study of NVIDIA GPU’s built-in power sensor,.

Evaluating MFU as a Proxy for GPU Power for Energy-Aware Simulation of LLM Training Accurate and convenient energy measurements for GPUs: A detailed study of NVIDIA GPU’s built-in power sensor,

Reference 19

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verified fuzzy
raw_fallback, observed 2026-08-05T10:31:32.248227Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation f585ab3d-8f9d-4a76-92c2-b5667f21bd5b · outbound

This paper cites An experimental comparison of software-based power me- ters: Focus on CPU and GPU,.

Evaluating MFU as a Proxy for GPU Power for Energy-Aware Simulation of LLM Training An experimental comparison of software-based power me- ters: Focus on CPU and GPU,

Reference 20

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verified fuzzy
raw_fallback, observed 2026-08-05T10:31:32.237554Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation e47867f8-e3b3-4142-89b2-37a0029842db · outbound

This paper cites High-resolution power profiling of GPU functions using low-resolution measurement,.

Evaluating MFU as a Proxy for GPU Power for Energy-Aware Simulation of LLM Training High-resolution power profiling of GPU functions using low-resolution measurement,

Reference 21

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raw_fallback, observed 2026-08-05T10:31:32.226728Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 24a699f8-5b6e-4c29-8f7d-24680b1dedfe · outbound

This paper cites Scaling Laws for Neural Language Models.

Evaluating MFU as a Proxy for GPU Power for Energy-Aware Simulation of LLM Training Scaling Laws for Neural Language Models

Reference 22

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no resolver link, observed 2026-08-05T10:31:32.027971Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T10:31:32.027971Z digest=sha256:ac0aed80b3fc0cdc9d0ba382cd1a1cf6f3a52943e0dbc8da8ff82d2b5dd142a8

Observation 20acc647-cad8-4d80-a3d6-9440a007e73d · outbound

This paper cites Pytorch: An imperative style, high-performance deep learning library,.

Evaluating MFU as a Proxy for GPU Power for Energy-Aware Simulation of LLM Training Pytorch: An imperative style, high-performance deep learning library,

Reference 23

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unresolved
no resolver link, observed 2026-08-05T10:31:32.032376Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T10:31:32.032376Z digest=sha256:c29db5bc2429254ae5a765148eaf892507f6943f4d60326c4a2500f3daab3e93

Observation b7a09e46-18b6-452a-ad77-f021596bd811 · outbound

This paper cites Transformers: State-of-the-art natural language processing,.

Evaluating MFU as a Proxy for GPU Power for Energy-Aware Simulation of LLM Training Transformers: State-of-the-art natural language processing,

Reference 24

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verified fuzzy
raw_fallback, observed 2026-08-05T10:31:32.210657Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 8f2c02c1-cefb-4d3f-ac32-0aaea77b4153 · outbound

This paper cites Hydra - a framework for elegantly configuring complex applications,.

Evaluating MFU as a Proxy for GPU Power for Energy-Aware Simulation of LLM Training Hydra - a framework for elegantly configuring complex applications,

Reference 25

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verified fuzzy
raw_fallback, observed 2026-08-05T10:31:32.200087Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 93a46424-4d30-46fa-9e19-b47043b6880f · outbound

This paper cites Hardware Scaling Trends and Diminishing Returns in Large-Scale Distributed Training.

Evaluating MFU as a Proxy for GPU Power for Energy-Aware Simulation of LLM Training Hardware Scaling Trends and Diminishing Returns in Large-Scale Distributed Training

Reference 26

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unresolved
no resolver link, observed 2026-08-05T10:31:32.042400Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T10:31:32.042400Z digest=sha256:495ab8d82b3159eabb62170157486319dc27697173137da3d467cf42c935162a

Observation 1336486d-7730-423b-b3aa-b2fa7f67f1da · outbound

This paper cites Understanding gpu resource interference one level deeper,.

Evaluating MFU as a Proxy for GPU Power for Energy-Aware Simulation of LLM Training Understanding gpu resource interference one level deeper,

Reference 27

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verified fuzzy
raw_fallback, observed 2026-08-05T10:31:32.188271Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 56317c4c-0073-4f41-8aa5-fb9d3540b540 · outbound

This paper cites Data-Driven Analysis to Understand GPU Hardware Resource Usage of Optimizations.

Evaluating MFU as a Proxy for GPU Power for Energy-Aware Simulation of LLM Training Data-Driven Analysis to Understand GPU Hardware Resource Usage of Optimizations

Reference 28

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verified exact
local_arxiv, observed 2026-08-05T10:31:32.099715Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-05T10:31:32.049456Z digest=sha256:8892852d385f9609a838989bac4d68664cb850c8c9462396959683104d60eefb

Observation f191c395-9656-41d7-b2af-f70719b0d04b · outbound

This paper cites Accelwattch: A power modeling framework for modern gpus,.

Evaluating MFU as a Proxy for GPU Power for Energy-Aware Simulation of LLM Training Accelwattch: A power modeling framework for modern gpus,

Reference 29

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verified fuzzy
raw_fallback, observed 2026-08-05T10:31:32.177266Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-05T10:31:32.053143Z digest=sha256:fcfcc917a0d1a4e98ce347ec72b60b7a23188bef3dee23c9e98358ec98aa690e

Observation 1a41813a-3689-4727-b000-bd1d3b025795 · outbound

This paper cites Trends in AI inference energy consumption: Beyond the performance-vs- parameter laws of deep learning,.

Evaluating MFU as a Proxy for GPU Power for Energy-Aware Simulation of LLM Training Trends in AI inference energy consumption: Beyond the performance-vs- parameter laws of deep learning,

Reference 30

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verified fuzzy
raw_fallback, observed 2026-08-05T10:31:32.165154Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-05T10:31:32.056510Z digest=sha256:a749a5f582553ce17557a82467ee6f138dc3573b8c6aa33d702b6d8a473800e9

Observation fc46df5b-d0e8-485f-af4b-f313ed3deb4a · outbound

This paper cites Lumos: Efficient performance modeling and estimation for large- scale LLM training,.

Evaluating MFU as a Proxy for GPU Power for Energy-Aware Simulation of LLM Training Lumos: Efficient performance modeling and estimation for large- scale LLM training,

Reference 31

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verified fuzzy
raw_fallback, observed 2026-08-05T10:31:32.154184Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-05T10:31:32.059820Z digest=sha256:f0fa767979a088f248c92452258ca13a0e1c6c3628ee467a7017f75db6d5062d

Observation eadfc6c0-9bf0-45b8-88f6-91c8126d1ef3 · outbound

This paper cites Vessim: A testbed for carbon-aware applications and systems,.

Evaluating MFU as a Proxy for GPU Power for Energy-Aware Simulation of LLM Training Vessim: A testbed for carbon-aware applications and systems,

Reference 32

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verified fuzzy
raw_fallback, observed 2026-08-05T10:31:32.143258Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-05T10:31:32.063715Z digest=sha256:5fafefb4150a7fa517f819c9277a48034d2a84a8c5a560b2bcd1d68043a4b424

Pith citing papers

No inbound Pith citation observations are available.