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Paper Citation Record · LEDGER

Pattern-Guided Design Space Exploration for FPGA Accelerator Design

As of 9 August 2026, this Paper Citation Record lists 36 of 36 outbound references and 0 inbound Pith citation observations for arXiv:2607.15068.

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

pith.paper-citation-record.v1
2607.15068 v1

Coverage vector

measured 36 of 36 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-02T00:17:24.756369Z

measured 36 of 36 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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

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Reference resolution

36 of 36 outbound references displayed

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External citation measurements

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Outbound references

Observation 378ffafd-f606-491b-9152-69f8ff9fb3bd · outbound

This paper cites Stiff circuit system modeling via transformer,.

Pattern-Guided Design Space Exploration for FPGA Accelerator Design Stiff circuit system modeling via transformer,

Reference 1

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Observation 6a1f8dce-96c4-4a08-8b77-9ce773d9c3c6 · outbound

This paper cites Labeling cost sensitive batch active learning for brain tumor segmentation,.

Pattern-Guided Design Space Exploration for FPGA Accelerator Design Labeling cost sensitive batch active learning for brain tumor segmentation,

Reference 2

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Observation a962b6c3-a879-48c5-a3d9-7e34f7c2cf94 · outbound

This paper cites Patternpaint: Practical layout pattern generation using diffusion-based inpainting,.

Pattern-Guided Design Space Exploration for FPGA Accelerator Design Patternpaint: Practical layout pattern generation using diffusion-based inpainting,

Reference 3

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Observation 4f917b3a-372b-4185-b296-1ac825b77bb3 · outbound

This paper cites Diffusion- model-enhanced layout pattern generation for sub-3nm dfm,.

Pattern-Guided Design Space Exploration for FPGA Accelerator Design Diffusion- model-enhanced layout pattern generation for sub-3nm dfm,

Reference 4

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Observation f028c881-6169-40cf-8cb0-92941eb52ae8 · outbound

This paper cites Dark silicon and the end of multicore scaling,.

Pattern-Guided Design Space Exploration for FPGA Accelerator Design Dark silicon and the end of multicore scaling,

Reference 5

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Observation 9c61af0a-1f87-48f3-924a-e4c306ced814 · outbound

This paper cites A reconfigurable fabric for accelerating large-scale datacenter services,.

Pattern-Guided Design Space Exploration for FPGA Accelerator Design A reconfigurable fabric for accelerating large-scale datacenter services,

Reference 6

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source=pdf_text observed=2026-08-02T00:17:24.638519Z digest=sha256:f56a44502fe09b45a7534616f3bbe8ad7127c236271576976d8e0cba95e79df8

Observation 198c0bc9-ac30-4cd7-9d60-9c1cd76e7863 · outbound

This paper cites A cloud-scale acceleration architecture,.

Pattern-Guided Design Space Exploration for FPGA Accelerator Design A cloud-scale acceleration architecture,

Reference 7

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source=pdf_text observed=2026-08-02T00:17:24.643148Z digest=sha256:232c3653a05e7639c88fa5d18be9688fbfc9cca8b17be2ce1608c5c34efacfad

Observation 0d8db604-7992-42cf-87ab-969635bb4d95 · outbound

This paper cites FPGA HLS today: Successes, challenges, and opportunities,.

Pattern-Guided Design Space Exploration for FPGA Accelerator Design FPGA HLS today: Successes, challenges, and opportunities,

Reference 8

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source=pdf_text observed=2026-08-02T00:17:24.647108Z digest=sha256:ab3285577b6f40c4dae9bce1f026b765e6f567e4fe417c3f97a6500ccccb6fb8

Observation cc300a7b-0064-4c30-9236-12db74c7eabb · outbound

This paper cites High-level synthesis design space explo- ration: Past, present, and future,.

Pattern-Guided Design Space Exploration for FPGA Accelerator Design High-level synthesis design space explo- ration: Past, present, and future,

Reference 9

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source=pdf_text observed=2026-08-02T00:17:24.651663Z digest=sha256:546f8fac43159be9935e686da0e0acd2f011cbb4e7833d3c453a9366a453cc70

Observation d22894bf-4280-43bd-814f-0bf2401e0285 · outbound

This paper cites Allo: A programming model for composable accelerator design,.

Pattern-Guided Design Space Exploration for FPGA Accelerator Design Allo: A programming model for composable accelerator design,

Reference 10

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Observation ca7a63a8-de96-4bdc-a64e-515179bf83bb · outbound

This paper cites The landscape of parallel computing research: A view from Berkeley,.

Pattern-Guided Design Space Exploration for FPGA Accelerator Design The landscape of parallel computing research: A view from Berkeley,

Reference 11

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source=pdf_text observed=2026-08-02T00:17:24.659883Z digest=sha256:874759fc8d5b81fe230f6ef385557ce79d7b27928fad3be5c96c43e8eee78bca

Observation ec6b33dd-5bde-49a7-a937-88bb6f6c3be6 · outbound

This paper cites MachSuite: Benchmarks for accelerator design and customized architectures,.

Pattern-Guided Design Space Exploration for FPGA Accelerator Design MachSuite: Benchmarks for accelerator design and customized architectures,

Reference 12

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source=pdf_text observed=2026-08-02T00:17:24.663798Z digest=sha256:fcc857615ee855f2fea5853fb9f3406295654ba77f027d49e0345ecb99923f60

Observation 17460494-0aa9-4f0a-bbfd-a5bcfd233868 · outbound

This paper cites Rodinia: A benchmark suite for heterogeneous computing,.

Pattern-Guided Design Space Exploration for FPGA Accelerator Design Rodinia: A benchmark suite for heterogeneous computing,

Reference 13

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source=pdf_text observed=2026-08-02T00:17:24.668133Z digest=sha256:7b24bbbb481ac2169877d6aa7b2c097f34390dda7b636bb535eedc76589e2cc6

Observation 1f609b53-e036-4c72-b597-a09a417ac139 · outbound

This paper cites CHStone: A benchmark program suite for practical C-based high-level synthesis,.

Pattern-Guided Design Space Exploration for FPGA Accelerator Design CHStone: A benchmark program suite for practical C-based high-level synthesis,

Reference 14

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source=pdf_text observed=2026-08-02T00:17:24.671685Z digest=sha256:1f0218fe6fd8b8497533b74038236b4345fb54129e58dd8ca56bca4f31e20c67

Observation 718b57ff-d4b4-4c6e-a00b-83f8d4addd0e · outbound

This paper cites Rosetta: A realistic high-level synthesis benchmark suite for software programmable FPGAs,.

Pattern-Guided Design Space Exploration for FPGA Accelerator Design Rosetta: A realistic high-level synthesis benchmark suite for software programmable FPGAs,

Reference 15

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source=pdf_text observed=2026-08-02T00:17:24.675682Z digest=sha256:354a52cad0d0434f499f0b13fe29652a8f66152de5326e9886b4e11dcd3671bc

Observation a85f4013-f31a-4eb6-a41c-3bcd1b77acb1 · outbound

This paper cites MLPerf inference benchmark,.

Pattern-Guided Design Space Exploration for FPGA Accelerator Design MLPerf inference benchmark,

Reference 16

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source=pdf_text observed=2026-08-02T00:17:24.679406Z digest=sha256:f3719dcad7fa1ce9c0f651067f2a5e0aa79c66a266a646563bf9574c69eacfaf

Observation 09740543-f3bb-45af-8e2d-60b5146bbdc0 · outbound

This paper cites ScaleHLS: A scalable high-level synthesis framework with multi-level transforma- tions and optimizations,.

Pattern-Guided Design Space Exploration for FPGA Accelerator Design ScaleHLS: A scalable high-level synthesis framework with multi-level transforma- tions and optimizations,

Reference 17

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source=pdf_text observed=2026-08-02T00:17:24.683062Z digest=sha256:b5520ec587ff782e6e6911507dc83b592f661c81cd6c37e7ce8557b7f522d9cc

Observation 191058f6-bdd5-4ffb-a1e0-1216521ae684 · outbound

This paper cites Decoupling algorithms from schedules for easy optimization of image processing pipelines,.

Pattern-Guided Design Space Exploration for FPGA Accelerator Design Decoupling algorithms from schedules for easy optimization of image processing pipelines,

Reference 18

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source=pdf_text observed=2026-08-02T00:17:24.686860Z digest=sha256:e3b9e09d764cf6b57ca7406b7ef9f34f1a11c38a79552426ee66dee6862f882b

Observation 25602d2a-73f3-4e92-8cf1-5c7a0ca62f6e · outbound

This paper cites TVM: An automated end-to-end optimizing compiler for deep learning,.

Pattern-Guided Design Space Exploration for FPGA Accelerator Design TVM: An automated end-to-end optimizing compiler for deep learning,

Reference 19

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source=pdf_text observed=2026-08-02T00:17:24.690537Z digest=sha256:1a7dd4bc338d1fe5e7306e7fc2389a29562cc9260793f987ac1bd80f1898569c

Observation 0b5850d9-3e51-48c6-b583-5b4d2de8a59d · outbound

This paper cites HeteroCL: A multi-paradigm programming infrastructure for software-defined reconfigurable computing,.

Pattern-Guided Design Space Exploration for FPGA Accelerator Design HeteroCL: A multi-paradigm programming infrastructure for software-defined reconfigurable computing,

Reference 20

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source=pdf_text observed=2026-08-02T00:17:24.694110Z digest=sha256:bfc1a55b64717ebd2dec9c39d75667bca48bbfa705982980e5fa4f62cd14abdc

Observation 9c80d0d9-ad0d-462a-b72e-56f4e0c8b7d3 · outbound

This paper cites fpgaConvNet: A framework for mapping convolutional neural networks on FPGAs,.

Pattern-Guided Design Space Exploration for FPGA Accelerator Design fpgaConvNet: A framework for mapping convolutional neural networks on FPGAs,

Reference 21

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source=pdf_text observed=2026-08-02T00:17:24.698711Z digest=sha256:86fa411f4f631ba8a486b630c72f2695b8d9734d1f609c355c56e651d3253778

Observation fb874a9a-35d3-4976-887a-a12f40051b41 · outbound

This paper cites DNNBuilder: An automated tool for building high-performance DNN hardware accelerators for FPGAs,.

Pattern-Guided Design Space Exploration for FPGA Accelerator Design DNNBuilder: An automated tool for building high-performance DNN hardware accelerators for FPGAs,

Reference 22

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Observation fa761949-cffc-4757-adc7-416213ccc13c · outbound

This paper cites In-datacenter performance analysis of a tensor processing unit,.

Pattern-Guided Design Space Exploration for FPGA Accelerator Design In-datacenter performance analysis of a tensor processing unit,

Reference 23

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source=pdf_text observed=2026-08-02T00:17:24.706434Z digest=sha256:3a44bbe28563e12961c827fe6bebc6c51768808deddce194cb0707cb9dd89a42

Observation d1c38035-6d82-4be7-9b27-f0fb37943058 · outbound

This paper cites Gemmini: Enabling systematic deep-learning archi- tecture evaluation via full-stack integration,.

Pattern-Guided Design Space Exploration for FPGA Accelerator Design Gemmini: Enabling systematic deep-learning archi- tecture evaluation via full-stack integration,

Reference 24

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Observation 684f6316-c0d1-4eb0-a77e-246ed03778c9 · outbound

This paper cites LegUp: High-level synthesis for FPGA-based processor/accelerator systems,.

Pattern-Guided Design Space Exploration for FPGA Accelerator Design LegUp: High-level synthesis for FPGA-based processor/accelerator systems,

Reference 25

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source=pdf_text observed=2026-08-02T00:17:24.713826Z digest=sha256:28a8d6443c83fea5dba0845f5f43eb546912c62f4a602f225880c90e1e83daa8

Observation 30668b16-dfad-42ab-807e-c86f460a439f · outbound

This paper cites MLIR: A Compiler Infrastructure for the End of Moore's Law.

Pattern-Guided Design Space Exploration for FPGA Accelerator Design MLIR: A Compiler Infrastructure for the End of Moore's Law

Reference 26

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source=pdf_text observed=2026-08-02T00:17:24.717495Z digest=sha256:5a82fc6395f188fdb7716dfe84ddf1c52e4268e5ed6f68890331d09a330f8afb

Observation 9161ff0c-ee36-468c-9fd3-9efaa229c068 · outbound

This paper cites VTR 7.0: Next generation architecture and CAD system for FPGAs,.

Pattern-Guided Design Space Exploration for FPGA Accelerator Design VTR 7.0: Next generation architecture and CAD system for FPGAs,

Reference 27

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Observation ac3d45c8-9819-425b-bba7-45e074e48eeb · outbound

This paper cites AutoBridge: Coupling coarse-grained floorplanning and pipelining for high-frequency HLS design on multi-die FPGAs,.

Pattern-Guided Design Space Exploration for FPGA Accelerator Design AutoBridge: Coupling coarse-grained floorplanning and pipelining for high-frequency HLS design on multi-die FPGAs,

Reference 28

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source=pdf_text observed=2026-08-02T00:17:24.725168Z digest=sha256:10d6c27c5dd00eba22cbe4dcfa60d7d8056ebe3cbeb458cb4c0b478dcd5cd541

Observation 1aff14d2-78fd-4a3a-b581-6af46fcee82c · outbound

This paper cites TAPA: A scalable task-parallel dataflow programming framework for modern FPGAs with co-optimization of HLS and physical design,.

Pattern-Guided Design Space Exploration for FPGA Accelerator Design TAPA: A scalable task-parallel dataflow programming framework for modern FPGAs with co-optimization of HLS and physical design,

Reference 29

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source=pdf_text observed=2026-08-02T00:17:24.729014Z digest=sha256:4b8bbc1f2afeb1a24acdb08b83a686ebff0f34ed045764919ee8e46c15c890d3

Observation 40d5d297-2483-4f1c-9fb9-6833534d845f · outbound

This paper cites Chisel: Constructing hardware in a Scala embedded language,.

Pattern-Guided Design Space Exploration for FPGA Accelerator Design Chisel: Constructing hardware in a Scala embedded language,

Reference 30

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source=pdf_text observed=2026-08-02T00:17:24.732720Z digest=sha256:121bfd01e5ac8e32f456147e5c3575a229d6e9538e815c3510da39bc1b0a37bc

Observation 7b91fdbf-250c-48ee-babb-99e60df2bef4 · outbound

This paper cites OpenROAD: Toward a self-driving, open-source digital layout implementation tool chain,.

Pattern-Guided Design Space Exploration for FPGA Accelerator Design OpenROAD: Toward a self-driving, open-source digital layout implementation tool chain,

Reference 31

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source=pdf_text observed=2026-08-02T00:17:24.736677Z digest=sha256:122a11f4c5e7fb4bc06a11c2152f07fc85cc2b03a20bc4b87c15efd4e9c232f3

Observation 61314dd7-229e-4dfc-af6a-95794cd5bfe5 · outbound

This paper cites On learning-based methods for design- space exploration with high-level synthesis,.

Pattern-Guided Design Space Exploration for FPGA Accelerator Design On learning-based methods for design- space exploration with high-level synthesis,

Reference 32

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Observation 0cbee2a1-e13c-4a78-8439-42d9a813cc79 · outbound

This paper cites AutoDSE: Enabling software programmers to design efficient FPGA accelerators,.

Pattern-Guided Design Space Exploration for FPGA Accelerator Design AutoDSE: Enabling software programmers to design efficient FPGA accelerators,

Reference 33

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source=pdf_text observed=2026-08-02T00:17:24.744196Z digest=sha256:d20a766c5117821a6115be6beedf1fadf7dd66346387233a981dd1dffd535da9

Observation 4245a5a1-9cab-4597-bf05-4f159bb1d820 · outbound

This paper cites From predict to generate: A cross-layer survey of generative ai for ic design and manufacturing,.

Pattern-Guided Design Space Exploration for FPGA Accelerator Design From predict to generate: A cross-layer survey of generative ai for ic design and manufacturing,

Reference 34

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Observation a5db22e7-d50b-4321-88ee-39af16fe3e46 · outbound

This paper cites Toward engineering agi: Benchmarking the engineering design capabilities of llms,.

Pattern-Guided Design Space Exploration for FPGA Accelerator Design Toward engineering agi: Benchmarking the engineering design capabilities of llms,

Reference 35

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Observation 202d4c09-bd87-4c62-b668-f24875144dc3 · outbound

This paper cites Available: https://proceedings.neurips.cc/paper files/ paper/2025/file/664f777548205fb6e0cbb0965e8d2e16-Paper-Datasets and Benchmarks Track.pdf.

Pattern-Guided Design Space Exploration for FPGA Accelerator Design Available: https://proceedings.neurips.cc/paper files/ paper/2025/file/664f777548205fb6e0cbb0965e8d2e16-Paper-Datasets and Benchmarks Track.pdf

Reference 2025

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Pith citing papers

No inbound Pith citation observations are available.