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Paper Citation Record · LEDGER

KPerfIR: Towards an Open and Compiler-centric Ecosystem for GPU Kernel Performance Tooling on Modern AI Workloads

As of 18 August 2026, this Paper Citation Record lists 54 of 54 outbound references and 1 inbound Pith citation observation for arXiv:2505.21661.

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

pith.paper-citation-record.v1
2505.21661 v1

Coverage vector

measured 54 of 54 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:30:25.024913Z

measured 55 of 55 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-01T04:49:45.955512Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

54 of 54 outbound references displayed

  • verified exact1
  • verified fuzzy36
  • unresolved17
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 2e344e02-b01f-4ccc-ba02-e4205fe72d85 · outbound

This paper cites AMD CDNA 3 Architec- ture, 2024.

KPerfIR: Towards an Open and Compiler-centric Ecosystem for GPU Kernel Performance Tooling on Modern AI Workloads AMD CDNA 3 Architec- ture, 2024

Reference 1

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raw_fallback, observed 2026-08-07T13:30:34.500256Z

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.

source=pdf_text observed=2026-08-07T13:30:19.545522Z digest=sha256:6387387600874a2a6a2e3427003b4664a94b0569086fff92fe60ecf73d387cce

Observation 2eb6d586-4189-48eb-b105-842caf372f90 · outbound

This paper cites AMD Instinct MI300.

KPerfIR: Towards an Open and Compiler-centric Ecosystem for GPU Kernel Performance Tooling on Modern AI Workloads AMD Instinct MI300

Reference 2

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raw_fallback, observed 2026-08-07T13:30:34.344389Z

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.

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Observation 73eeba50-5079-4895-9db1-e035931c4531 · outbound

This paper cites Composable kernel (CK) library, 2024.

KPerfIR: Towards an Open and Compiler-centric Ecosystem for GPU Kernel Performance Tooling on Modern AI Workloads Composable kernel (CK) library, 2024

Reference 3

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raw_fallback, observed 2026-08-07T13:30:34.049128Z

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.

source=pdf_text observed=2026-08-07T13:30:19.807153Z digest=sha256:668e716a0d2a91870b917dcdca411f310f10a876d2946860f493a34348c005b8

Observation e39d64f4-f18f-440c-9dfa-b1e9d0d2d5b1 · outbound

This paper cites ROCm ROCProfiler, 2024.

KPerfIR: Towards an Open and Compiler-centric Ecosystem for GPU Kernel Performance Tooling on Modern AI Workloads ROCm ROCProfiler, 2024

Reference 4

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raw_fallback, observed 2026-08-07T13:30:33.896032Z

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.

source=pdf_text observed=2026-08-07T13:30:19.964826Z digest=sha256:64568fc478b40b951c5faf8b118c88d0dea94339da344697bfcee1c1ae476fcd

Observation 27487e3b-0f90-4d32-8a29-b566a845e40f · outbound

This paper cites Version 6.2.4.

KPerfIR: Towards an Open and Compiler-centric Ecosystem for GPU Kernel Performance Tooling on Modern AI Workloads Version 6.2.4

Reference 5

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raw_fallback, observed 2026-08-07T13:30:33.736971Z

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.

source=pdf_text observed=2026-08-07T13:30:20.062588Z digest=sha256:41ce2619d8f15debdf419cfd9185f562f1e3499696db3c98e8427b379f8ad2a5

Observation 290f3855-9c35-42cf-9d0e-12e558601a81 · outbound

This paper cites rocBLAS Library, 2023.

KPerfIR: Towards an Open and Compiler-centric Ecosystem for GPU Kernel Performance Tooling on Modern AI Workloads rocBLAS Library, 2023

Reference 6

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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.

source=pdf_text observed=2026-08-07T13:30:20.161638Z digest=sha256:31b7a064dea48745d35f269c74f323cf644985909bd264d4cc7341f438ad369d

Observation 57e3bd36-2b97-4be7-a9c8-1f223975e3b9 · outbound

This paper cites Pytorch 2: Faster machine learning through dynamic python bytecode transformation and graph compilation.

KPerfIR: Towards an Open and Compiler-centric Ecosystem for GPU Kernel Performance Tooling on Modern AI Workloads Pytorch 2: Faster machine learning through dynamic python bytecode transformation and graph compilation

Reference 7

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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.

source=pdf_text observed=2026-08-07T13:30:20.365005Z digest=sha256:7276b935d1a67e9a47196fefbea526dc40eb26323f21ee705fe0a657fa15a8e3

Observation 7bfcd8d2-17c6-40eb-8dd6-42d58241f38d · outbound

This paper cites Cu- daDMA: optimizing GPU memory bandwidth via warp specialization.

KPerfIR: Towards an Open and Compiler-centric Ecosystem for GPU Kernel Performance Tooling on Modern AI Workloads Cu- daDMA: optimizing GPU memory bandwidth via warp specialization

Reference 8

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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.

source=pdf_text observed=2026-08-07T13:30:20.495238Z digest=sha256:3f8fd0fb588fc3a4854bd644a1f8237817ed6cee15747dd7e9e0dec6000fa15a

Observation 9d5e68d6-583b-4ea5-ac8b-3fed454b7474 · outbound

This paper cites Hatchet: Pruning the overgrowth in parallel profiles.

KPerfIR: Towards an Open and Compiler-centric Ecosystem for GPU Kernel Performance Tooling on Modern AI Workloads Hatchet: Pruning the overgrowth in parallel profiles

Reference 9

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raw_fallback, observed 2026-08-07T13:30:32.924612Z

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.

source=pdf_text observed=2026-08-07T13:30:20.624754Z digest=sha256:8ce900f8de5d7dfcd70b0ee3a7ec9ea371d6ad51504ccc4151190004b3dac524

Observation 56db27a6-5958-4258-9476-5d40c9cf77d1 · outbound

This paper cites JAX: com- posable transformations of Python+NumPy programs, 2018.

KPerfIR: Towards an Open and Compiler-centric Ecosystem for GPU Kernel Performance Tooling on Modern AI Workloads JAX: com- posable transformations of Python+NumPy programs, 2018

Reference 10

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:30:20.844831Z digest=sha256:a9015634bbd940aa76c31b4b72a4181e4dc8fb60fc688765457d80f557a5143d

Observation af6e44c1-3fa5-454f-84a2-9114f38f6aa6 · outbound

This paper cites Language Models are Few-Shot Learners.

KPerfIR: Towards an Open and Compiler-centric Ecosystem for GPU Kernel Performance Tooling on Modern AI Workloads Language Models are Few-Shot Learners

Reference 11

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source=pdf_text observed=2026-08-07T13:30:20.955014Z digest=sha256:cbffcec2f51238f23e5b3249c3bf5786e9b96b5e7257a20f8cc69bd9a0c482ef

Observation 12e87fc3-18af-4c55-805c-fde39d1251fd · outbound

This paper cites FLUX: Fast Software-based Communication Overlap On GPUs Through Kernel Fusion.

KPerfIR: Towards an Open and Compiler-centric Ecosystem for GPU Kernel Performance Tooling on Modern AI Workloads FLUX: Fast Software-based Communication Overlap On GPUs Through Kernel Fusion

Reference 12

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:30:21.095644Z digest=sha256:69bf970ac3affdcbf66fbec4825fd62674ff93a52a84222139e32b1ced161bc7

Observation e8ee2ef3-9316-4ea0-9c1e-03a139372fb6 · outbound

This paper cites {TVM}: An automated {End-to-End} optimizing compiler for deep learning.

KPerfIR: Towards an Open and Compiler-centric Ecosystem for GPU Kernel Performance Tooling on Modern AI Workloads {TVM}: An automated {End-to-End} optimizing compiler for deep learning

Reference 13

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no resolver link, observed 2026-08-07T13:30:21.169914Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:30:21.169914Z digest=sha256:b93a074a72a5b5bcf6423534800fb09f767510daf7256272e40e9a961d92ca3b

Observation da1d23e9-33a1-403a-a7c4-9197248d0658 · outbound

This paper cites Learning to optimize tensor programs.

KPerfIR: Towards an Open and Compiler-centric Ecosystem for GPU Kernel Performance Tooling on Modern AI Workloads Learning to optimize tensor programs

Reference 14

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raw_fallback, observed 2026-08-07T13:30:32.674148Z

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.

source=pdf_text observed=2026-08-07T13:30:21.285927Z digest=sha256:7efdf2815db677a6067ff02ef9c2b629640add12183c7841688eac645aaad45a

Observation 70948b4b-64fa-4f76-b913-09282b3312ca · outbound

This paper cites Nvidia hopper h100 gpu: Scaling per- formance.

KPerfIR: Towards an Open and Compiler-centric Ecosystem for GPU Kernel Performance Tooling on Modern AI Workloads Nvidia hopper h100 gpu: Scaling per- formance

Reference 15

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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.

source=pdf_text observed=2026-08-07T13:30:21.383216Z digest=sha256:dc4a6d5fbed3fb234970b9ef8ef5f55746da6b078b779903c68014542bebe141

Observation e515ed3f-c5ed-4351-bed5-824f17cb5415 · outbound

This paper cites V olta: Performance and programmability.

KPerfIR: Towards an Open and Compiler-centric Ecosystem for GPU Kernel Performance Tooling on Modern AI Workloads V olta: Performance and programmability

Reference 16

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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.

source=pdf_text observed=2026-08-07T13:30:21.491020Z digest=sha256:8553e8e0ad43623a1fcc74b60215386bef58cba89f3b46a59a8fafdc1b41f20b

Observation cd36a80a-8a84-469d-86a2-a8d1bd62fd9a · outbound

This paper cites Crago, Sana Damani, Karthikeyan Sankar- alingam, and Stephen W.

KPerfIR: Towards an Open and Compiler-centric Ecosystem for GPU Kernel Performance Tooling on Modern AI Workloads Crago, Sana Damani, Karthikeyan Sankar- alingam, and Stephen W

Reference 17

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source=pdf_text observed=2026-08-07T13:30:21.603517Z digest=sha256:ba956dbae032fa273d382f8cd5df477c75f669f3b382f067cc7e5cb5aa02013f

Observation 2d5df09b-e791-4c35-9034-b1f53d7aa60e · outbound

This paper cites Davidson and Christopher W.

KPerfIR: Towards an Open and Compiler-centric Ecosystem for GPU Kernel Performance Tooling on Modern AI Workloads Davidson and Christopher W

Reference 18

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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.

source=pdf_text observed=2026-08-07T13:30:21.691141Z digest=sha256:b48a630cae919bf7d1957866169a3b2eb74af48c5fb63e1b8c6bfaf4c361c658

Observation 8d485b2e-9f76-4a37-907d-48a7880ec5fd · outbound

This paper cites Chrome trace format, 2023.

KPerfIR: Towards an Open and Compiler-centric Ecosystem for GPU Kernel Performance Tooling on Modern AI Workloads Chrome trace format, 2023

Reference 19

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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.

source=pdf_text observed=2026-08-07T13:30:21.790575Z digest=sha256:3100344a1b9d15ea22d32fc1f1b33cbae970f9c32f5bed0eb9cfdebb682c5ccb

Observation e8743293-0cba-417c-822f-db090b7c51ba · outbound

This paper cites Amanda: Unified instrumentation 14 framework for deep neural networks.

KPerfIR: Towards an Open and Compiler-centric Ecosystem for GPU Kernel Performance Tooling on Modern AI Workloads Amanda: Unified instrumentation 14 framework for deep neural networks

Reference 20

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T13:30:21.937992Z digest=sha256:8f124752de133c3f820c450fca2cbd6393d0367d0633c4b58ac325f868313968

Observation 053317d4-7d5c-477a-9b90-252097da8bc3 · outbound

This paper cites Profile inference revisited.

KPerfIR: Towards an Open and Compiler-centric Ecosystem for GPU Kernel Performance Tooling on Modern AI Workloads Profile inference revisited

Reference 21

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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.

source=pdf_text observed=2026-08-07T13:30:22.055097Z digest=sha256:b1a26dbc9fec4f3e4d1c665d8d9816d9b562023e3763f4336d78c8afcacef13d

Observation 29bd1027-93f8-4c83-bb31-db15c772544e · outbound

This paper cites ALCOP: Automatic Load-Compute Pipelining in Deep Learning Compiler for AI-GPUs.

KPerfIR: Towards an Open and Compiler-centric Ecosystem for GPU Kernel Performance Tooling on Modern AI Workloads ALCOP: Automatic Load-Compute Pipelining in Deep Learning Compiler for AI-GPUs

Reference 22

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local_arxiv, observed 2026-08-07T13:30:26.245325Z

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.

source=pdf_text observed=2026-08-07T13:30:22.165005Z digest=sha256:5235729a96a1851f4d07355a71ef90bf0c8ad6358f76519baf24acca1525b2aa

Observation b05945cf-638c-494d-8c03-0b328d61116f · outbound

This paper cites Alcop: Automatic load- compute pipelining in deep learning compiler for ai- gpus.

KPerfIR: Towards an Open and Compiler-centric Ecosystem for GPU Kernel Performance Tooling on Modern AI Workloads Alcop: Automatic load- compute pipelining in deep learning compiler for ai- gpus

Reference 23

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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.

source=pdf_text observed=2026-08-07T13:30:22.247836Z digest=sha256:9a3a0e0f277e2b4212be3cda213700398334e0f813c46d888cd1969ade30c019

Observation 6b3fb28a-fef5-4fcb-b20c-20866a858629 · outbound

This paper cites Multi- physics simulations: Challenges and opportunities.

KPerfIR: Towards an Open and Compiler-centric Ecosystem for GPU Kernel Performance Tooling on Modern AI Workloads Multi- physics simulations: Challenges and opportunities

Reference 24

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raw_fallback, observed 2026-08-07T13:30:30.809330Z

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.

source=pdf_text observed=2026-08-07T13:30:22.335538Z digest=sha256:a556363e9231a2594d17efadca0263e4e56b002d84198dc1d0c5ab71d132b414

Observation a73110ad-2825-4370-bfb5-f1d1099a928e · outbound

This paper cites Llvm: A compilation framework for lifelong program analysis & transforma- tion.

KPerfIR: Towards an Open and Compiler-centric Ecosystem for GPU Kernel Performance Tooling on Modern AI Workloads Llvm: A compilation framework for lifelong program analysis & transforma- tion

Reference 25

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raw_fallback, observed 2026-08-07T13:30:30.653926Z

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.

source=pdf_text observed=2026-08-07T13:30:22.389283Z digest=sha256:fbf8a5b408a73e7bc9e75770230628ec1aa9137e36f435e3451347feddbe2561

Observation 54c58660-8eea-4202-b3ad-11c340ed26d5 · outbound

This paper cites Mlir: Scaling compiler infrastructure for do- main specific computation.

KPerfIR: Towards an Open and Compiler-centric Ecosystem for GPU Kernel Performance Tooling on Modern AI Workloads Mlir: Scaling compiler infrastructure for do- main specific computation

Reference 26

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:30:22.515748Z digest=sha256:c5c216212d0ae953402c9bf35994fcf14fcf013ee71fddd56ac656edb8a8f164

Observation 8c6437fb-9148-44fb-94f3-3bdf8c6f3095 · outbound

This paper cites Deep learning.

KPerfIR: Towards an Open and Compiler-centric Ecosystem for GPU Kernel Performance Tooling on Modern AI Workloads Deep learning

Reference 27

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:30:22.645303Z digest=sha256:bd6d2fc45418f0b19db67183cc50d5c113ee56b57cfbdadeb5c7c6c51b899e69

Observation 13dd4433-06a5-4ef0-abd3-021156b40d2d · outbound

This paper cites an unresolved cited work.

KPerfIR: Towards an Open and Compiler-centric Ecosystem for GPU Kernel Performance Tooling on Modern AI Workloads Unresolved cited work

Reference 28

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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.

source=pdf_text observed=2026-08-07T13:30:22.701028Z digest=sha256:35da4de70ea899e94b41e5d9b986a54f73c8f1d29267d6a01d2d6ea0ba69c56c

Observation e4235d67-0ff5-497d-82b3-0a5addda178c · outbound

This paper cites Experimental FlashAttention3 using Triton, 2024.

KPerfIR: Towards an Open and Compiler-centric Ecosystem for GPU Kernel Performance Tooling on Modern AI Workloads Experimental FlashAttention3 using Triton, 2024

Reference 29

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T13:30:22.794752Z digest=sha256:02935dd52c9c59227044ab5be5fe9aba4dfb67b69a64847a3fda47cc280600bf

Observation 6028930b-df31-4f74-bde3-fe4661c93150 · outbound

This paper cites NVIDIA Turing GPU Architec- ture Whitepaper, 2018.

KPerfIR: Towards an Open and Compiler-centric Ecosystem for GPU Kernel Performance Tooling on Modern AI Workloads NVIDIA Turing GPU Architec- ture Whitepaper, 2018

Reference 30

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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.

source=pdf_text observed=2026-08-07T13:30:22.857610Z digest=sha256:a69b334b61c5a71232fdabf9b2a2f96900cd60c019dc8bd1458098faec0aa649

Observation 1d72d265-bef9-4ede-a978-766f10be2cac · outbound

This paper cites cuBLAS Library, 2023.

KPerfIR: Towards an Open and Compiler-centric Ecosystem for GPU Kernel Performance Tooling on Modern AI Workloads cuBLAS Library, 2023

Reference 31

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raw_fallback, observed 2026-08-07T13:30:29.941830Z

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.

source=pdf_text observed=2026-08-07T13:30:22.984913Z digest=sha256:ab4864c0450f87693db7cea013d8f846e29214d1c7ae4a24750bef5672655053

Observation 7fa48589-8726-4e2d-b4ac-468851ed5b65 · outbound

This paper cites CUPTI: CUDA Profiling Tools Interface, 2023.

KPerfIR: Towards an Open and Compiler-centric Ecosystem for GPU Kernel Performance Tooling on Modern AI Workloads CUPTI: CUDA Profiling Tools Interface, 2023

Reference 32

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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.

source=pdf_text observed=2026-08-07T13:30:23.068207Z digest=sha256:bf5cdf5c0c421bfc100e156bea7628079d07f88ebd1c391423961c39c185de42

Observation 416fd099-5bf4-47c1-9099-65b41182c32b · outbound

This paper cites NVIDIA Nsight Compute, 2024.

KPerfIR: Towards an Open and Compiler-centric Ecosystem for GPU Kernel Performance Tooling on Modern AI Workloads NVIDIA Nsight Compute, 2024

Reference 33

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raw_fallback, observed 2026-08-07T13:30:29.630513Z

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.

source=pdf_text observed=2026-08-07T13:30:23.187664Z digest=sha256:48749717a2c9a3acf3c85675d16d12c54f14fdf3e71a41ca85479400eef3d6ee

Observation c2cfa9d0-71d2-477a-a996-c9d8ae0684f6 · outbound

This paper cites NVIDIA Nsight Systems, 2024.

KPerfIR: Towards an Open and Compiler-centric Ecosystem for GPU Kernel Performance Tooling on Modern AI Workloads NVIDIA Nsight Systems, 2024

Reference 34

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raw_fallback, observed 2026-08-07T13:30:29.448684Z

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.

source=pdf_text observed=2026-08-07T13:30:23.281676Z digest=sha256:dd478548fa2381a20633f218ca4da451d1591db0974a576a666bd2dfcb730a05

Observation 7cbfb932-243c-45f5-9250-329661b90689 · outbound

This paper cites NVIDIA PTX, 2024.

KPerfIR: Towards an Open and Compiler-centric Ecosystem for GPU Kernel Performance Tooling on Modern AI Workloads NVIDIA PTX, 2024

Reference 35

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raw_fallback, observed 2026-08-07T13:30:29.275704Z

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.

source=pdf_text observed=2026-08-07T13:30:23.329699Z digest=sha256:201553b736e7403a44161ae6d290d720cc9b8aac6024b57821193461d5555a27

Observation 58fa46a6-32fb-41a2-85af-35dc37be549e · outbound

This paper cites Group GEMM in Triton, 2024.

KPerfIR: Towards an Open and Compiler-centric Ecosystem for GPU Kernel Performance Tooling on Modern AI Workloads Group GEMM in Triton, 2024

Reference 36

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verified fuzzy
raw_fallback, observed 2026-08-07T13:30:29.065653Z

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.

source=pdf_text observed=2026-08-07T13:30:23.419679Z digest=sha256:0890bf84439d917987950675b82f3854b2ea5e07d3a9478efe4fa720bdf19ad8

Observation e41f3c2e-4d9e-486e-8919-ac13e92c36c3 · outbound

This paper cites Optimizing distributed ml communi- cation with fused computation-collective operations.

KPerfIR: Towards an Open and Compiler-centric Ecosystem for GPU Kernel Performance Tooling on Modern AI Workloads Optimizing distributed ml communi- cation with fused computation-collective operations

Reference 37

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raw_fallback, observed 2026-08-07T13:30:28.909368Z

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.

source=pdf_text observed=2026-08-07T13:30:23.515110Z digest=sha256:05cc3d507a69bc637f1531679cf4002d40900b6c6661c720bf6f1ad8618a39d2

Observation 8410f4dd-7f2c-4774-88fb-74a2d3637376 · outbound

This paper cites PyTorch Profiler.

KPerfIR: Towards an Open and Compiler-centric Ecosystem for GPU Kernel Performance Tooling on Modern AI Workloads PyTorch Profiler

Reference 38

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verified fuzzy
raw_fallback, observed 2026-08-07T13:30:28.804814Z

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.

source=pdf_text observed=2026-08-07T13:30:23.639842Z digest=sha256:32644037ebc7fe37b24e383ce8b4b4e7579a3542008b8f51c0889a774b944a7c

Observation 9e33af1c-37ca-4ab3-a77f-a84c89132027 · outbound

This paper cites Reinventing High Performance Computing: Challenges and Opportunities.

KPerfIR: Towards an Open and Compiler-centric Ecosystem for GPU Kernel Performance Tooling on Modern AI Workloads Reinventing High Performance Computing: Challenges and Opportunities

Reference 39

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unresolved
no resolver link, observed 2026-08-07T13:30:23.717161Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:30:23.717161Z digest=sha256:7b82a0f6c0a097d7cd255b4c7215c1ced0ad41103aeb756b11f23b073dd6d63e

Observation 01376597-3a37-4828-babc-6bb0cb7c485f · outbound

This paper cites Learning representations by back-propagating errors.

KPerfIR: Towards an Open and Compiler-centric Ecosystem for GPU Kernel Performance Tooling on Modern AI Workloads Learning representations by back-propagating errors

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-07T13:30:23.775785Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:30:23.775785Z digest=sha256:3a7dda8ddaf480f412ae32c06d83644a47d3728fd7a768987cadddff58e2e5f0

Observation 4fe7920d-610c-4afb-bda8-6fad7fb2be62 · outbound

This paper cites Flashattention- 3: Fast and accurate attention with asynchrony and low- precision.

KPerfIR: Towards an Open and Compiler-centric Ecosystem for GPU Kernel Performance Tooling on Modern AI Workloads Flashattention- 3: Fast and accurate attention with asynchrony and low- precision

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:30:28.685775Z

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.

source=pdf_text observed=2026-08-07T13:30:23.832865Z digest=sha256:c2bbc95c87bfcd46be898786de46c67e29bb101d00a37450fb219a699c513f89

Observation c01853a3-027a-4e52-85d3-a2a427ea60cd · outbound

This paper cites FlashAttention-3: Fast and Accurate Attention with Asynchrony and Low-precision.

KPerfIR: Towards an Open and Compiler-centric Ecosystem for GPU Kernel Performance Tooling on Modern AI Workloads FlashAttention-3: Fast and Accurate Attention with Asynchrony and Low-precision

Reference 42

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unresolved
no resolver link, observed 2026-08-07T13:30:23.937127Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:30:23.937127Z digest=sha256:c3c10f37c3cbb2e1d8a9c4f65e723e7a788b0314a5984630229169688d236aff

Observation 759b5c7d-5f43-4bac-8b38-274054b48cc6 · outbound

This paper cites Tensor program opti- mization with probabilistic programs.

KPerfIR: Towards an Open and Compiler-centric Ecosystem for GPU Kernel Performance Tooling on Modern AI Workloads Tensor program opti- mization with probabilistic programs

Reference 43

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no resolver link, observed 2026-08-07T13:30:23.995310Z

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source=pdf_text observed=2026-08-07T13:30:23.995310Z digest=sha256:7eb80778156f791f6915c2e26f0b698ba9e5ce9844b19360f7f7bb214c1316a1

Observation feb87269-0c5b-4cd8-ae0f-061a40d6246d · outbound

This paper cites ThunderKittens: Simple, Fast, and Adorable AI Kernels.

KPerfIR: Towards an Open and Compiler-centric Ecosystem for GPU Kernel Performance Tooling on Modern AI Workloads ThunderKittens: Simple, Fast, and Adorable AI Kernels

Reference 44

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no resolver link, observed 2026-08-07T13:30:24.085300Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-07T13:30:24.085300Z digest=sha256:2410ca3a7a9f6fd05616e01dece1f275ef1e532c616231584fcc15db113ca2ef

Observation 274c38bf-249b-455c-8760-e2c0a40f8074 · outbound

This paper cites CUTLASS, January 2023.

KPerfIR: Towards an Open and Compiler-centric Ecosystem for GPU Kernel Performance Tooling on Modern AI Workloads CUTLASS, January 2023

Reference 45

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raw_fallback, observed 2026-08-07T13:30:28.475954Z

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.

source=pdf_text observed=2026-08-07T13:30:24.159738Z digest=sha256:caa196e8a7960218415069023cbb635d3bb2018c9b082ea6a273818fbf200b67

Observation ec4c7c0b-4745-4260-b614-767e1e5ad6b5 · outbound

This paper cites Large language models in medicine.

KPerfIR: Towards an Open and Compiler-centric Ecosystem for GPU Kernel Performance Tooling on Modern AI Workloads Large language models in medicine

Reference 46

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:30:24.215990Z digest=sha256:b2655e87ffaa6c49cfcefbfac15f0fcfe8a14c93904736315f18169e9ab3c758

Observation 031bdfdc-2d9f-4c1e-b1d5-3976e281fe8a · outbound

This paper cites Triton: an intermediate language and compiler for tiled neural network computations.

KPerfIR: Towards an Open and Compiler-centric Ecosystem for GPU Kernel Performance Tooling on Modern AI Workloads Triton: an intermediate language and compiler for tiled neural network computations

Reference 47

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source=pdf_text observed=2026-08-07T13:30:24.270842Z digest=sha256:130b43bfe02d4ab9c7d50af7683e6cd836c8af6b7cd11861267f8f64222badc1

Observation eee372a2-8b78-4873-bf88-f62c4503f10b · outbound

This paper cites Nvbit: A dynamic binary instru- mentation framework for nvidia gpus.

KPerfIR: Towards an Open and Compiler-centric Ecosystem for GPU Kernel Performance Tooling on Modern AI Workloads Nvbit: A dynamic binary instru- mentation framework for nvidia gpus

Reference 48

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raw_fallback, observed 2026-08-07T13:30:27.955031Z

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.

source=pdf_text observed=2026-08-07T13:30:24.342065Z digest=sha256:e1e9a93b3f76ba117727294c0ca2bf7f40b9a35c6790067ff6fa9f87c07b293e

Observation 54438187-5bdc-4664-a4c7-a00147aabc7c · outbound

This paper cites WLB-LLM: Workload-Balanced 4D Parallelism for Large Language Model Training.

KPerfIR: Towards an Open and Compiler-centric Ecosystem for GPU Kernel Performance Tooling on Modern AI Workloads WLB-LLM: Workload-Balanced 4D Parallelism for Large Language Model Training

Reference 49

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no resolver link, observed 2026-08-07T13:30:24.514841Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:30:24.514841Z digest=sha256:df0f8d27000851e09e364d7945e6fff5139b4da0c03f180a88b460de49081c30

Observation f47efffa-1cd2-476b-bfb4-9dd2fcabe9bb · outbound

This paper cites Rap: Resource-aware automated gpu sharing for multi-gpu recommendation model training and input preprocessing.

KPerfIR: Towards an Open and Compiler-centric Ecosystem for GPU Kernel Performance Tooling on Modern AI Workloads Rap: Resource-aware automated gpu sharing for multi-gpu recommendation model training and input preprocessing

Reference 50

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verified fuzzy
raw_fallback, observed 2026-08-07T13:30:27.714838Z

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.

source=pdf_text observed=2026-08-07T13:30:24.634751Z digest=sha256:89696c7684946a947bc9eecf899d8f4ddfbdfb0a45eeabac2e5483ca3f6c542d

Observation fcee688e-b778-446a-aaef-556320014db0 · outbound

This paper cites BloombergGPT: A Large Language Model for Finance.

KPerfIR: Towards an Open and Compiler-centric Ecosystem for GPU Kernel Performance Tooling on Modern AI Workloads BloombergGPT: A Large Language Model for Finance

Reference 51

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no resolver link, observed 2026-08-07T13:30:24.734854Z

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source=pdf_text observed=2026-08-07T13:30:24.734854Z digest=sha256:1df51c12480094f9e1dd3c0f21d1e2ba365ef352055b1df6809d96d6d38aae1d

Observation 57ec749e-fe5d-4864-8b84-af6860c41538 · outbound

This paper cites Ansor: Generating {High-Performance} tensor programs for deep learn- ing.

KPerfIR: Towards an Open and Compiler-centric Ecosystem for GPU Kernel Performance Tooling on Modern AI Workloads Ansor: Generating {High-Performance} tensor programs for deep learn- ing

Reference 52

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no resolver link, observed 2026-08-07T13:30:24.804890Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:30:24.804890Z digest=sha256:48ecc760fda329ea45efe9fa8b52a036c1b7e2837cd4a2005752d3aadd59f209

Observation 9ab0e73d-bc02-4e5a-9de7-75afe7c1d6f3 · outbound

This paper cites Gvprof: A value profiler for gpu-based clusters.

KPerfIR: Towards an Open and Compiler-centric Ecosystem for GPU Kernel Performance Tooling on Modern AI Workloads Gvprof: A value profiler for gpu-based clusters

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:30:27.405478Z

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.

source=pdf_text observed=2026-08-07T13:30:24.934964Z digest=sha256:26d55756c13772e066b2c5ca81c348787fbaf66ac18355f12b6e2e582d3cd237

Observation 70b31a9c-f283-484e-baa0-b258163575ea · outbound

This paper cites Valueexpert: Exploring value patterns in gpu-accelerated applications.

KPerfIR: Towards an Open and Compiler-centric Ecosystem for GPU Kernel Performance Tooling on Modern AI Workloads Valueexpert: Exploring value patterns in gpu-accelerated applications

Reference 54

Resolution
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raw_fallback, observed 2026-08-07T13:30:26.974974Z

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.

source=pdf_text observed=2026-08-07T13:30:25.024913Z digest=sha256:4234470e9f87718fb55bb27d35ccd356236c3cceac4f218d2291c33c862e1a8f

Pith citing papers

Observation d12f834c-5d30-49cb-94e8-e4e59f0174e5 · inbound

TileSight: A First-Principles Tile-Centric Analytical GPU Performance Model from Cores to Clusters cites this paper.

TileSight: A First-Principles Tile-Centric Analytical GPU Performance Model from Cores to Clusters KPerfIR: Towards an Open and Compiler-centric Ecosystem for GPU Kernel Performance Tooling on Modern AI Workloads

Reference 18

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source=pdf_text observed=2026-08-01T04:49:45.955512Z digest=sha256:6acbad71db667b1952d29483fc7330fbee86af5ab02081e7da64be1a7fd52e0d