Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-08T14:14:35.448676Z
Paper Citation Record · LEDGER
Machine Learning Fleet Efficiency: Analyzing and Optimizing Large-Scale Google TPU Systems with ML Productivity Goodput
As of 19 August 2026, this Paper Citation Record lists 76 of 76 outbound references and 4 inbound Pith citation observations for arXiv:2502.06982.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T04:57:52.568195Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-01T21:36:15.542964Z
Reference resolution
76 of 76 outbound references displayed
- verified exact2
- verified fuzzy8
- unresolved61
- parse uncertain0
- malformed identifier1
- metadata mismatch4
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation cea38c78-cb23-4e32-891e-8cfc71194c40 · outbound
This paper cites an unresolved cited work.
Machine Learning Fleet Efficiency: Analyzing and Optimizing Large-Scale Google TPU Systems with ML Productivity Goodput Unresolved cited work
Reference 1
- Resolution
- unresolved
- raw_fallback, observed 2026-08-08T14:14:37.099828Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 0b4dea27-9028-45d8-a809-974e48dd30b7 · outbound
This paper cites an unresolved cited work.
Machine Learning Fleet Efficiency: Analyzing and Optimizing Large-Scale Google TPU Systems with ML Productivity Goodput Unresolved cited work
Reference 2
- Resolution
- unresolved
- raw_fallback, observed 2026-08-08T14:14:37.087597Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation ba93c145-4b2e-4506-89aa-11ff69ed5b23 · outbound
This paper cites TensorFlow: A system for large-scale machine learning.
Machine Learning Fleet Efficiency: Analyzing and Optimizing Large-Scale Google TPU Systems with ML Productivity Goodput TensorFlow: A system for large-scale machine learning
Reference 3
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T14:14:35.173870Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 25394408-4efc-4f53-b8ec-bde0f8a2f269 · outbound
This paper cites Banning, Sumeer Bhola, Rick Buskens, Ming Chen, Xi Chen, Yoo Chung, Qin Jia, Nick Sakharov, George T.
Machine Learning Fleet Efficiency: Analyzing and Optimizing Large-Scale Google TPU Systems with ML Productivity Goodput Banning, Sumeer Bhola, Rick Buskens, Ming Chen, Xi Chen, Yoo Chung, Qin Jia, Nick Sakharov, George T
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T14:14:37.074250Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 62504617-2bff-4208-b436-f941d37f44c7 · outbound
This paper cites an unresolved cited work.
Machine Learning Fleet Efficiency: Analyzing and Optimizing Large-Scale Google TPU Systems with ML Productivity Goodput Unresolved cited work
Reference 5
- Resolution
- unresolved
- raw_fallback, observed 2026-08-08T14:14:37.061577Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 31b47966-264d-4026-820a-a17fd17da18e · outbound
This paper cites an unresolved cited work.
Machine Learning Fleet Efficiency: Analyzing and Optimizing Large-Scale Google TPU Systems with ML Productivity Goodput Unresolved cited work
Reference 6
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T14:14:35.185891Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0bee877f-3334-4be6-b069-8149d26f08bf · outbound
This paper cites Pathways: Asynchronous Distributed Dataflow for ML.
Machine Learning Fleet Efficiency: Analyzing and Optimizing Large-Scale Google TPU Systems with ML Productivity Goodput Pathways: Asynchronous Distributed Dataflow for ML
Reference 7
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T14:14:35.190079Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6aa35d2a-d3ab-4c23-80fa-86e629d65c28 · outbound
This paper cites an unresolved cited work.
Machine Learning Fleet Efficiency: Analyzing and Optimizing Large-Scale Google TPU Systems with ML Productivity Goodput Unresolved cited work
Reference 8
- Resolution
- unresolved
- raw_fallback, observed 2026-08-08T14:14:37.049550Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation c6639a02-af13-4600-b624-732fa7140ab8 · outbound
This paper cites an unresolved cited work.
Machine Learning Fleet Efficiency: Analyzing and Optimizing Large-Scale Google TPU Systems with ML Productivity Goodput Unresolved cited work
Reference 9
- Resolution
- unresolved
- raw_fallback, observed 2026-08-08T14:14:37.033407Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 6a921add-11f4-4482-9a0c-3307790786b9 · outbound
This paper cites Cooper, and Linda Torczon.
Machine Learning Fleet Efficiency: Analyzing and Optimizing Large-Scale Google TPU Systems with ML Productivity Goodput Cooper, and Linda Torczon
Reference 10
- Resolution
- metadata mismatch
- raw_fallback, observed 2026-08-08T14:14:36.380989Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation b2da1d18-b349-4355-abe8-ac2c17255023 · outbound
This paper cites an unresolved cited work.
Machine Learning Fleet Efficiency: Analyzing and Optimizing Large-Scale Google TPU Systems with ML Productivity Goodput Unresolved cited work
Reference 11
- Resolution
- unresolved
- raw_fallback, observed 2026-08-08T14:14:37.018889Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 3d8a7939-5e56-4b69-8c42-c3783a43f834 · outbound
This paper cites Language Models are Few-Shot Learners.
Machine Learning Fleet Efficiency: Analyzing and Optimizing Large-Scale Google TPU Systems with ML Productivity Goodput Language Models are Few-Shot Learners
Reference 12
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T14:14:35.209953Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 06eea592-b20f-4e4b-8d92-9c1fd16bf40b · outbound
This paper cites an unresolved cited work.
Machine Learning Fleet Efficiency: Analyzing and Optimizing Large-Scale Google TPU Systems with ML Productivity Goodput Unresolved cited work
Reference 13
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T14:14:35.214069Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9f709f81-142b-4e48-b57a-23358e43ca57 · outbound
This paper cites an unresolved cited work.
Machine Learning Fleet Efficiency: Analyzing and Optimizing Large-Scale Google TPU Systems with ML Productivity Goodput Unresolved cited work
Reference 14
- Resolution
- unresolved
- raw_fallback, observed 2026-08-08T14:14:36.998340Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 3249a713-8368-4699-b59e-6da122993ffa · outbound
This paper cites an unresolved cited work.
Machine Learning Fleet Efficiency: Analyzing and Optimizing Large-Scale Google TPU Systems with ML Productivity Goodput Unresolved cited work
Reference 15
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T14:14:35.217913Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1cdcf7a7-8a22-45ad-bcc6-363b710d7867 · outbound
This paper cites an unresolved cited work.
Machine Learning Fleet Efficiency: Analyzing and Optimizing Large-Scale Google TPU Systems with ML Productivity Goodput Unresolved cited work
Reference 16
- Resolution
- unresolved
- raw_fallback, observed 2026-08-08T14:14:36.973987Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 3da094ce-d419-4776-90da-4cf7a41b2857 · outbound
This paper cites an unresolved cited work.
Machine Learning Fleet Efficiency: Analyzing and Optimizing Large-Scale Google TPU Systems with ML Productivity Goodput Unresolved cited work
Reference 17
- Resolution
- unresolved
- raw_fallback, observed 2026-08-08T14:14:36.986304Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 271ae118-3e51-49a6-8c22-5fca3a4c9e90 · outbound
This paper cites an unresolved cited work.
Machine Learning Fleet Efficiency: Analyzing and Optimizing Large-Scale Google TPU Systems with ML Productivity Goodput Unresolved cited work
Reference 18
- Resolution
- unresolved
- raw_fallback, observed 2026-08-08T14:14:36.963328Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 5d71858a-c111-4394-91c4-3007c6bd2bb5 · outbound
This paper cites Emer and Douglas W.
Machine Learning Fleet Efficiency: Analyzing and Optimizing Large-Scale Google TPU Systems with ML Productivity Goodput Emer and Douglas W
Reference 19
- Resolution
- metadata mismatch
- raw_fallback, observed 2026-08-08T14:14:36.283984Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 3ada0bbe-4023-4306-949b-5ad8a1d8acc4 · outbound
This paper cites an unresolved cited work.
Machine Learning Fleet Efficiency: Analyzing and Optimizing Large-Scale Google TPU Systems with ML Productivity Goodput Unresolved cited work
Reference 20
- Resolution
- unresolved
- raw_fallback, observed 2026-08-08T14:14:36.939914Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 44db8799-8f3c-4dc5-badf-05346876a859 · outbound
This paper cites an unresolved cited work.
Machine Learning Fleet Efficiency: Analyzing and Optimizing Large-Scale Google TPU Systems with ML Productivity Goodput Unresolved cited work
Reference 21
- Resolution
- unresolved
- raw_fallback, observed 2026-08-08T14:14:36.951919Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 87fb889a-4061-43d3-bf8e-740bf237af1d · outbound
This paper cites an unresolved cited work.
Machine Learning Fleet Efficiency: Analyzing and Optimizing Large-Scale Google TPU Systems with ML Productivity Goodput Unresolved cited work
Reference 22
- Resolution
- unresolved
- raw_fallback, observed 2026-08-08T14:14:36.916849Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation aeaf1fd6-7599-4aaf-8326-02135d738274 · outbound
This paper cites an unresolved cited work.
Machine Learning Fleet Efficiency: Analyzing and Optimizing Large-Scale Google TPU Systems with ML Productivity Goodput Unresolved cited work
Reference 23
- Resolution
- unresolved
- raw_fallback, observed 2026-08-08T14:14:36.928462Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 3fb2793b-0597-426b-835a-8a363aa6a5ab · outbound
This paper cites an unresolved cited work.
Machine Learning Fleet Efficiency: Analyzing and Optimizing Large-Scale Google TPU Systems with ML Productivity Goodput Unresolved cited work
Reference 24
- Resolution
- unresolved
- raw_fallback, observed 2026-08-08T14:14:36.890153Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 18c5a57b-994b-45ff-ae44-aeb52ba82a7c · outbound
This paper cites Hennessy and David A.
Machine Learning Fleet Efficiency: Analyzing and Optimizing Large-Scale Google TPU Systems with ML Productivity Goodput Hennessy and David A
Reference 25
- Resolution
- malformed identifier
- raw_fallback, observed 2026-08-08T14:14:36.903414Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation fa0088d6-7fc3-43aa-b781-393a2d03c52e · outbound
This paper cites an unresolved cited work.
Machine Learning Fleet Efficiency: Analyzing and Optimizing Large-Scale Google TPU Systems with ML Productivity Goodput Unresolved cited work
Reference 26
- Resolution
- unresolved
- raw_fallback, observed 2026-08-08T14:14:36.865391Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation fab075ab-53f4-40d7-8332-10a85963d716 · outbound
This paper cites an unresolved cited work.
Machine Learning Fleet Efficiency: Analyzing and Optimizing Large-Scale Google TPU Systems with ML Productivity Goodput Unresolved cited work
Reference 27
- Resolution
- unresolved
- raw_fallback, observed 2026-08-08T14:14:36.878769Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation a383b0ba-cb36-47ff-a4f3-5a3c501ef85f · outbound
This paper cites TPU v4: An Optically Reconfigurable Supercomputer for Machine Learning with Hardware Support for Embeddings.
Machine Learning Fleet Efficiency: Analyzing and Optimizing Large-Scale Google TPU Systems with ML Productivity Goodput TPU v4: An Optically Reconfigurable Supercomputer for Machine Learning with Hardware Support for Embeddings
Reference 28
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T14:14:35.272822Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a04529fe-3d6e-4562-a63d-1f61baacdcc2 · outbound
This paper cites Jouppi, Doe Hyun Yoon, Matthew Ashcraft, Mark Gottscho, Thomas B.
Machine Learning Fleet Efficiency: Analyzing and Optimizing Large-Scale Google TPU Systems with ML Productivity Goodput Jouppi, Doe Hyun Yoon, Matthew Ashcraft, Mark Gottscho, Thomas B
Reference 29
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T14:14:35.269272Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f9abe851-84b4-4daf-96cf-3ffaf96d86d2 · outbound
This paper cites an unresolved cited work.
Machine Learning Fleet Efficiency: Analyzing and Optimizing Large-Scale Google TPU Systems with ML Productivity Goodput Unresolved cited work
Reference 30
- Resolution
- metadata mismatch
- raw_fallback, observed 2026-08-08T14:14:36.116560Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 7e35396e-d937-4097-995a-bb982854c260 · outbound
This paper cites Jouppi, Cliff Young, Nishant Patil, David A.
Machine Learning Fleet Efficiency: Analyzing and Optimizing Large-Scale Google TPU Systems with ML Productivity Goodput Jouppi, Cliff Young, Nishant Patil, David A
Reference 31
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T14:14:36.852533Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 04723395-cbe5-4fd1-9ddc-be9bcb5f78dc · outbound
This paper cites an unresolved cited work.
Machine Learning Fleet Efficiency: Analyzing and Optimizing Large-Scale Google TPU Systems with ML Productivity Goodput Unresolved cited work
Reference 32
- Resolution
- unresolved
- raw_fallback, observed 2026-08-08T14:14:36.825662Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 40174fd1-2797-43c3-ae8e-0389fe5574ee · outbound
This paper cites an unresolved cited work.
Machine Learning Fleet Efficiency: Analyzing and Optimizing Large-Scale Google TPU Systems with ML Productivity Goodput Unresolved cited work
Reference 33
- Resolution
- unresolved
- raw_fallback, observed 2026-08-08T14:14:36.811728Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 8aa90ba5-3253-4e87-9805-7f31fa76a548 · outbound
This paper cites an unresolved cited work.
Machine Learning Fleet Efficiency: Analyzing and Optimizing Large-Scale Google TPU Systems with ML Productivity Goodput Unresolved cited work
Reference 34
- Resolution
- unresolved
- raw_fallback, observed 2026-08-08T14:14:36.838478Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 4ac63b1a-3cd3-4886-8bbc-eb203aa1bbfd · outbound
This paper cites an unresolved cited work.
Machine Learning Fleet Efficiency: Analyzing and Optimizing Large-Scale Google TPU Systems with ML Productivity Goodput Unresolved cited work
Reference 35
- Resolution
- unresolved
- raw_fallback, observed 2026-08-08T14:14:36.786613Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 68f558cb-ed27-41ae-bfcc-4886d4f215bd · outbound
This paper cites an unresolved cited work.
Machine Learning Fleet Efficiency: Analyzing and Optimizing Large-Scale Google TPU Systems with ML Productivity Goodput Unresolved cited work
Reference 36
- Resolution
- unresolved
- raw_fallback, observed 2026-08-08T14:14:36.762357Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation edde4ab9-8bd1-46dd-8c57-a6843fd05f34 · outbound
This paper cites an unresolved cited work.
Machine Learning Fleet Efficiency: Analyzing and Optimizing Large-Scale Google TPU Systems with ML Productivity Goodput Unresolved cited work
Reference 37
- Resolution
- unresolved
- raw_fallback, observed 2026-08-08T14:14:36.799045Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation cd04e0e4-912f-47fb-a144-b30e5033e5a5 · outbound
This paper cites an unresolved cited work.
Machine Learning Fleet Efficiency: Analyzing and Optimizing Large-Scale Google TPU Systems with ML Productivity Goodput Unresolved cited work
Reference 38
- Resolution
- unresolved
- raw_fallback, observed 2026-08-08T14:14:36.728319Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation ab82423b-1998-4c8e-bc28-340e0a3c3a3e · outbound
This paper cites Mustafa Rafique, Franck Cappello, and Bogdan Nicolae.
Machine Learning Fleet Efficiency: Analyzing and Optimizing Large-Scale Google TPU Systems with ML Productivity Goodput Mustafa Rafique, Franck Cappello, and Bogdan Nicolae
Reference 39
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T14:14:35.326881Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b89ee389-a29c-4bf0-adc7-c68a0b78d1f3 · outbound
This paper cites an unresolved cited work.
Machine Learning Fleet Efficiency: Analyzing and Optimizing Large-Scale Google TPU Systems with ML Productivity Goodput Unresolved cited work
Reference 40
- Resolution
- unresolved
- raw_fallback, observed 2026-08-08T14:14:36.716124Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 1fd3196a-60c5-4b1d-b348-6451670d219c · outbound
This paper cites an unresolved cited work.
Machine Learning Fleet Efficiency: Analyzing and Optimizing Large-Scale Google TPU Systems with ML Productivity Goodput Unresolved cited work
Reference 41
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T14:14:35.315520Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d8522ad1-6365-45dc-9a64-2d62889e1620 · outbound
This paper cites Deep Learning Recommendation Model for Personalization and Recommendation Systems.
Machine Learning Fleet Efficiency: Analyzing and Optimizing Large-Scale Google TPU Systems with ML Productivity Goodput Deep Learning Recommendation Model for Personalization and Recommendation Systems
Reference 42
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T14:14:35.337895Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 46a99af2-e73d-43ec-bd45-7fc432253e3d · outbound
This paper cites Wozniak, George Bosilca, Matthieu Dorier, and Franck Cappello.
Machine Learning Fleet Efficiency: Analyzing and Optimizing Large-Scale Google TPU Systems with ML Productivity Goodput Wozniak, George Bosilca, Matthieu Dorier, and Franck Cappello
Reference 43
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T14:14:35.341659Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d7582782-e7b2-40e7-aa22-f70f980fc257 · outbound
This paper cites Li, Ryan McElroy, Mike Paleczny, Daniel Peek, Paul Saab, David Stafford, Tony Tung, and Venkateshwaran Venkataramani.
Machine Learning Fleet Efficiency: Analyzing and Optimizing Large-Scale Google TPU Systems with ML Productivity Goodput Li, Ryan McElroy, Mike Paleczny, Daniel Peek, Paul Saab, David Stafford, Tony Tung, and Venkateshwaran Venkataramani
Reference 44
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T14:14:36.703233Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation e0bd02fb-8097-4562-94ec-647cb41c74ff · outbound
This paper cites an unresolved cited work.
Machine Learning Fleet Efficiency: Analyzing and Optimizing Large-Scale Google TPU Systems with ML Productivity Goodput Unresolved cited work
Reference 45
- Resolution
- verified exact
- raw_fallback, observed 2026-08-08T14:14:35.862508Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 0ecf53de-5d5d-4554-aa1e-9b436101f1bf · outbound
This paper cites tf.data: A Machine Learning Data Processing Framework.
Machine Learning Fleet Efficiency: Analyzing and Optimizing Large-Scale Google TPU Systems with ML Productivity Goodput tf.data: A Machine Learning Data Processing Framework
Reference 46
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T14:14:35.334066Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4364c9d7-070c-4f5b-9c59-84e7e8ba1517 · outbound
This paper cites PyTorch: An Imperative Style, High-Performance Deep Learning Library.
Machine Learning Fleet Efficiency: Analyzing and Optimizing Large-Scale Google TPU Systems with ML Productivity Goodput PyTorch: An Imperative Style, High-Performance Deep Learning Library
Reference 47
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T14:14:35.356616Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f925e958-84f0-4b51-ac10-d7dce73ce6dd · outbound
This paper cites an unresolved cited work.
Machine Learning Fleet Efficiency: Analyzing and Optimizing Large-Scale Google TPU Systems with ML Productivity Goodput Unresolved cited work
Reference 48
- Resolution
- unresolved
- raw_fallback, observed 2026-08-08T14:14:36.678965Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 47937785-8b0a-4ee3-ab3f-aeec2bed55c5 · outbound
This paper cites an unresolved cited work.
Machine Learning Fleet Efficiency: Analyzing and Optimizing Large-Scale Google TPU Systems with ML Productivity Goodput Unresolved cited work
Reference 49
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T14:14:35.364656Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f0baefb9-e41d-4293-a820-61eca9060050 · outbound
This paper cites an unresolved cited work.
Machine Learning Fleet Efficiency: Analyzing and Optimizing Large-Scale Google TPU Systems with ML Productivity Goodput Unresolved cited work
Reference 50
- Resolution
- metadata mismatch
- raw_fallback, observed 2026-08-08T14:14:35.763370Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation c3a6bd37-7003-4a44-a5c7-ce46522edf43 · outbound
This paper cites an unresolved cited work.
Machine Learning Fleet Efficiency: Analyzing and Optimizing Large-Scale Google TPU Systems with ML Productivity Goodput Unresolved cited work
Reference 51
- Resolution
- unresolved
- raw_fallback, observed 2026-08-08T14:14:36.691185Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation fe464644-1d9c-4018-b17d-0f4c6115eb9f · outbound
This paper cites an unresolved cited work.
Machine Learning Fleet Efficiency: Analyzing and Optimizing Large-Scale Google TPU Systems with ML Productivity Goodput Unresolved cited work
Reference 52
- Resolution
- unresolved
- raw_fallback, observed 2026-08-08T14:14:36.634749Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 890106eb-518b-4e56-ba70-5d9027342048 · outbound
This paper cites an unresolved cited work.
Machine Learning Fleet Efficiency: Analyzing and Optimizing Large-Scale Google TPU Systems with ML Productivity Goodput Unresolved cited work
Reference 53
- Resolution
- unresolved
- raw_fallback, observed 2026-08-08T14:14:36.622281Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation d26cc555-a91d-4763-94ad-c2d91c7904f3 · outbound
This paper cites Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer.
Machine Learning Fleet Efficiency: Analyzing and Optimizing Large-Scale Google TPU Systems with ML Productivity Goodput Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer
Reference 54
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7a8fa365-89e1-4dae-a7c3-a0c6220d91bb · outbound
This paper cites In Proceedings of Ma- chine Learning and Systems , D.
Machine Learning Fleet Efficiency: Analyzing and Optimizing Large-Scale Google TPU Systems with ML Productivity Goodput In Proceedings of Ma- chine Learning and Systems , D
Reference 55
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T14:14:36.659203Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 5906e66f-f389-487c-b4ce-db3b8e78b1b2 · outbound
This paper cites an unresolved cited work.
Machine Learning Fleet Efficiency: Analyzing and Optimizing Large-Scale Google TPU Systems with ML Productivity Goodput Unresolved cited work
Reference 56
- Resolution
- unresolved
- raw_fallback, observed 2026-08-08T14:14:36.596928Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation ec8ef137-7b5d-4351-ace9-ab1db94c451f · outbound
This paper cites an unresolved cited work.
Machine Learning Fleet Efficiency: Analyzing and Optimizing Large-Scale Google TPU Systems with ML Productivity Goodput Unresolved cited work
Reference 57
- Resolution
- unresolved
- raw_fallback, observed 2026-08-08T14:14:36.646435Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 08807a89-72ff-4ac9-bd5d-27972fda8f58 · outbound
This paper cites Gemini: A Family of Highly Capable Multimodal Models.
Machine Learning Fleet Efficiency: Analyzing and Optimizing Large-Scale Google TPU Systems with ML Productivity Goodput Gemini: A Family of Highly Capable Multimodal Models
Reference 58
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 853f7608-fb94-49a3-bd3f-3d51f898e901 · outbound
This paper cites an unresolved cited work.
Machine Learning Fleet Efficiency: Analyzing and Optimizing Large-Scale Google TPU Systems with ML Productivity Goodput Unresolved cited work
Reference 59
- Resolution
- unresolved
- raw_fallback, observed 2026-08-08T14:14:36.572563Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 904ed2ba-818e-456a-b955-e57284ea0b3a · outbound
This paper cites an unresolved cited work.
Machine Learning Fleet Efficiency: Analyzing and Optimizing Large-Scale Google TPU Systems with ML Productivity Goodput Unresolved cited work
Reference 60
- Resolution
- unresolved
- raw_fallback, observed 2026-08-08T14:14:36.559271Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation ac4921a7-110b-4bfb-85dc-a81c9c424164 · outbound
This paper cites an unresolved cited work.
Machine Learning Fleet Efficiency: Analyzing and Optimizing Large-Scale Google TPU Systems with ML Productivity Goodput Unresolved cited work
Reference 61
- Resolution
- unresolved
- raw_fallback, observed 2026-08-08T14:14:36.609749Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 1c7deb3f-fc0a-47f7-aeee-3d452d9d5be2 · outbound
This paper cites Korupolu, David Oppenheimer, Eric Tune, and John Wilkes.
Machine Learning Fleet Efficiency: Analyzing and Optimizing Large-Scale Google TPU Systems with ML Productivity Goodput Korupolu, David Oppenheimer, Eric Tune, and John Wilkes
Reference 62
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T14:14:36.539676Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 1bdd4758-21ba-4026-91b0-1158d0faa395 · outbound
This paper cites an unresolved cited work.
Machine Learning Fleet Efficiency: Analyzing and Optimizing Large-Scale Google TPU Systems with ML Productivity Goodput Unresolved cited work
Reference 63
- Resolution
- unresolved
- raw_fallback, observed 2026-08-08T14:14:36.527478Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 6118bd45-25b0-4fc1-914f-1ddd3305fad0 · outbound
This paper cites an unresolved cited work.
Machine Learning Fleet Efficiency: Analyzing and Optimizing Large-Scale Google TPU Systems with ML Productivity Goodput Unresolved cited work
Reference 64
- Resolution
- unresolved
- raw_fallback, observed 2026-08-08T14:14:36.585251Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation fdf12497-143c-417d-9602-cacddbb99a31 · outbound
This paper cites An Evaluation of Edge TPU Accelerators for Convolutional Neural Networks.
Machine Learning Fleet Efficiency: Analyzing and Optimizing Large-Scale Google TPU Systems with ML Productivity Goodput An Evaluation of Edge TPU Accelerators for Convolutional Neural Networks
Reference 65
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T14:14:35.432953Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 39d43346-6e2b-489e-b7cb-18c1aa711eda · outbound
This paper cites Yoo, Morris A.
Machine Learning Fleet Efficiency: Analyzing and Optimizing Large-Scale Google TPU Systems with ML Productivity Goodput Yoo, Morris A
Reference 66
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T14:14:36.515371Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 10ca42e5-1ffb-4ccd-ba5b-00e93d4f239b · outbound
This paper cites Understanding Data Storage and Ingestion for Large-Scale Deep Recommendation Model Training.
Machine Learning Fleet Efficiency: Analyzing and Optimizing Large-Scale Google TPU Systems with ML Productivity Goodput Understanding Data Storage and Ingestion for Large-Scale Deep Recommendation Model Training
Reference 67
- Resolution
- verified exact
- local_arxiv, observed 2026-08-08T14:14:35.568865Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 3c795c23-a7ed-4002-a3c5-1ffc392fa3d6 · outbound
This paper cites an unresolved cited work.
Machine Learning Fleet Efficiency: Analyzing and Optimizing Large-Scale Google TPU Systems with ML Productivity Goodput Unresolved cited work
Reference 68
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T14:14:35.417476Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation db9cc7a8-a2bb-4a3e-ab44-a1e8936db368 · outbound
This paper cites an unresolved cited work.
Machine Learning Fleet Efficiency: Analyzing and Optimizing Large-Scale Google TPU Systems with ML Productivity Goodput Unresolved cited work
Reference 69
- Resolution
- unresolved
- raw_fallback, observed 2026-08-08T14:14:36.502598Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 758981c4-9a02-457b-af2b-5a42ce20c145 · outbound
This paper cites an unresolved cited work.
Machine Learning Fleet Efficiency: Analyzing and Optimizing Large-Scale Google TPU Systems with ML Productivity Goodput Unresolved cited work
Reference 71
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T14:14:35.429521Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation fc3ae17a-213b-4917-98b6-7e871893365c · outbound
This paper cites an unresolved cited work.
Machine Learning Fleet Efficiency: Analyzing and Optimizing Large-Scale Google TPU Systems with ML Productivity Goodput Unresolved cited work
Reference 75
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T14:14:35.444334Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2dfe1f75-e9ed-41f0-a3d4-35e47168f5fb · outbound
This paper cites In Proceedings of the 44th annual IEEE/ACM International Symposium on Microarchitecture.
Machine Learning Fleet Efficiency: Analyzing and Optimizing Large-Scale Google TPU Systems with ML Productivity Goodput In Proceedings of the 44th annual IEEE/ACM International Symposium on Microarchitecture
Reference 2011
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T14:14:36.741531Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation a8f6a0e4-5c66-44ee-ab88-74857485dbf5 · outbound
This paper cites TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems.
Machine Learning Fleet Efficiency: Analyzing and Optimizing Large-Scale Google TPU Systems with ML Productivity Goodput TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems
Reference 2016
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T14:14:35.169430Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 82e0ff50-14c6-4299-ae00-bc1275b92bbc · outbound
This paper cites In-Datacenter Performance Analysis of a Tensor Processing Unit.
Machine Learning Fleet Efficiency: Analyzing and Optimizing Large-Scale Google TPU Systems with ML Productivity Goodput In-Datacenter Performance Analysis of a Tensor Processing Unit
Reference 2017
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T14:14:35.280728Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 39ad9462-27af-42f6-a0ae-b7ac694bcc37 · outbound
This paper cites Learned Hardware/Software Co-Design of Neural Accelerators.
Machine Learning Fleet Efficiency: Analyzing and Optimizing Large-Scale Google TPU Systems with ML Productivity Goodput Learned Hardware/Software Co-Design of Neural Accelerators
Reference 2020
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T14:14:35.395499Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2ba9a89e-3730-4418-9db9-519699aa3567 · outbound
This paper cites In International Conference on High Performance Computing.
Machine Learning Fleet Efficiency: Analyzing and Optimizing Large-Scale Google TPU Systems with ML Productivity Goodput In International Conference on High Performance Computing
Reference 2023
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T14:14:36.774606Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Pith citing papers
Observation 41d4bd1b-5ccd-4729-80ed-24c41b4d0ce2 · inbound
A Survey of End-to-End Modeling for Distributed DNN Training: Workloads, Simulators, and TCO cites this paper.
A Survey of End-to-End Modeling for Distributed DNN Training: Workloads, Simulators, and TCO Machine Learning Fleet Efficiency: Analyzing and Optimizing Large-Scale Google TPU Systems with ML Productivity Goodput
Reference 129
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T04:57:52.568195Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 56ade0ac-c6ae-4299-85e1-3e64c5c9d9e1 · inbound
AcOrch: Accelerating Sampling-based GNN Training under CPU-NPU Heterogeneous Environments cites this paper.
AcOrch: Accelerating Sampling-based GNN Training under CPU-NPU Heterogeneous Environments Machine Learning Fleet Efficiency: Analyzing and Optimizing Large-Scale Google TPU Systems with ML Productivity Goodput
Reference 43
- Resolution
- verified exact
- arxiv_id, observed 2026-07-01T21:36:15.545052Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 067f8b27-9930-4cb9-91ea-6a262abcfd68 · inbound
MLSYSIM: First-Principles Infrastructure Modeling for Machine Learning Systems cites this paper.
MLSYSIM: First-Principles Infrastructure Modeling for Machine Learning Systems Machine Learning Fleet Efficiency: Analyzing and Optimizing Large-Scale Google TPU Systems with ML Productivity Goodput
Reference 132
- Resolution
- unresolved
- no resolver link, observed 2026-07-12T11:05:56.233115Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e937d750-074a-4c97-998a-3aa2b7833d3f · inbound
A Taxonomy of Performance Metrics for the Distributed Computing Continuum cites this paper.
A Taxonomy of Performance Metrics for the Distributed Computing Continuum Machine Learning Fleet Efficiency: Analyzing and Optimizing Large-Scale Google TPU Systems with ML Productivity Goodput
Reference 82
- Resolution
- unresolved
- no resolver link, observed 2026-07-31T08:21:13.989830Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.