DFModel: Design Space Optimization of Large-Scale Systems Exploiting Dataflow Mappings | Paper Citation Record

Observation 7c33989c-aa80-42c1-a5cc-3b5255794db8 · outbound

This paper cites Performance characteristics of common transports and buses,.

DFModel: Design Space Optimization of Large-Scale Systems Exploiting Dataflow Mappings Performance characteristics of common transports and buses,

Reference 1

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This paper cites Nvidia dgx-1 with tesla v100 system architecture,.

DFModel: Design Space Optimization of Large-Scale Systems Exploiting Dataflow Mappings Nvidia dgx-1 with tesla v100 system architecture,

Reference 2

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Observation 25edffee-10d3-40cc-94f9-3625933ea0fb · outbound

This paper cites [Online].

DFModel: Design Space Optimization of Large-Scale Systems Exploiting Dataflow Mappings [Online]

Reference 3

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Observation 747aa6c2-1729-4ae8-b32c-3e6e85791391 · outbound

This paper cites Hpl - a portable implementation of the high-performance linpack benchmark for distributed-memory computers,.

DFModel: Design Space Optimization of Large-Scale Systems Exploiting Dataflow Mappings Hpl - a portable implementation of the high-performance linpack benchmark for distributed-memory computers,

Reference 4

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This paper cites [Online].

DFModel: Design Space Optimization of Large-Scale Systems Exploiting Dataflow Mappings [Online]

Reference 5

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DFModel: Design Space Optimization of Large-Scale Systems Exploiting Dataflow Mappings Unresolved cited work

Reference 6

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Observation ddd578da-0871-4e87-8bf7-2bc79f4790ee · outbound

This paper cites [Online].

DFModel: Design Space Optimization of Large-Scale Systems Exploiting Dataflow Mappings [Online]

Reference 7

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Observation b73cf3c3-da39-42cd-b6c4-a0df03fabda3 · outbound

This paper cites Multinode multi-gpu: Using nvidia cufftmp ffts at scale,.

DFModel: Design Space Optimization of Large-Scale Systems Exploiting Dataflow Mappings Multinode multi-gpu: Using nvidia cufftmp ffts at scale,

Reference 8

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This paper cites Gurobi optimizer reference manual, version 10.0,.

DFModel: Design Space Optimization of Large-Scale Systems Exploiting Dataflow Mappings Gurobi optimizer reference manual, version 10.0,

Reference 9

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This paper cites Nvidia h100 pcie 96 gb,.

DFModel: Design Space Optimization of Large-Scale Systems Exploiting Dataflow Mappings Nvidia h100 pcie 96 gb,

Reference 10

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Observation 1be82016-d1f4-48dd-b435-0532b93024a9 · outbound

This paper cites What is nvlink?.

DFModel: Design Space Optimization of Large-Scale Systems Exploiting Dataflow Mappings What is nvlink?

Reference 11

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This paper cites Nvlink and nvlink switch,.

DFModel: Design Space Optimization of Large-Scale Systems Exploiting Dataflow Mappings Nvlink and nvlink switch,

Reference 12

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Observation cefefe8f-b640-416c-90ed-893212370e98 · outbound

This paper cites Analysis of the communication and computation cost of fft libraries towards exascale,.

DFModel: Design Space Optimization of Large-Scale Systems Exploiting Dataflow Mappings Analysis of the communication and computation cost of fft libraries towards exascale,

Reference 13

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Observation 978c9921-f0ce-44b6-b3fd-d9316db88a07 · outbound

This paper cites Demystifying AI Platform Design for Distributed Inference of Next-Generation LLM models.

DFModel: Design Space Optimization of Large-Scale Systems Exploiting Dataflow Mappings Demystifying AI Platform Design for Distributed Inference of Next-Generation LLM models

Reference 14

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This paper cites vtrain: A simulation framework for evaluating cost-effective and compute-optimal large lan- guage model training,.

DFModel: Design Space Optimization of Large-Scale Systems Exploiting Dataflow Mappings vtrain: A simulation framework for evaluating cost-effective and compute-optimal large lan- guage model training,

Reference 15

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Observation 4abdc373-0dd5-4c75-8f0a-36da6476af68 · outbound

This paper cites Language models are few-shot learners,.

DFModel: Design Space Optimization of Large-Scale Systems Exploiting Dataflow Mappings Language models are few-shot learners,

Reference 16

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This paper cites Cross-data knowledge graph construction for llm-enabled educational question-answering system: A case study at hcmut,.

DFModel: Design Space Optimization of Large-Scale Systems Exploiting Dataflow Mappings Cross-data knowledge graph construction for llm-enabled educational question-answering system: A case study at hcmut,

Reference 17

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This paper cites Hiercgra: A novel framework for large-scale cgra with hierarchical modeling and automated design space exploration,.

DFModel: Design Space Optimization of Large-Scale Systems Exploiting Dataflow Mappings Hiercgra: A novel framework for large-scale cgra with hierarchical modeling and automated design space exploration,

Reference 18

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Observation b65a91b9-4e84-416d-b9e6-7a37113be785 · outbound

This paper cites Blueconnect: Decomposing all-reduce for deep learning on heterogeneous network hierarchy,.

DFModel: Design Space Optimization of Large-Scale Systems Exploiting Dataflow Mappings Blueconnect: Decomposing all-reduce for deep learning on heterogeneous network hierarchy,

Reference 19

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Observation c41cb023-2d6c-4109-876f-30950474081e · outbound

This paper cites Nvidia hopper gpu: Scaling performance,.

DFModel: Design Space Optimization of Large-Scale Systems Exploiting Dataflow Mappings Nvidia hopper gpu: Scaling performance,

Reference 20

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Observation 33ee0972-fdc4-433e-8d7d-f50b814f395e · outbound

This paper cites Nvidia a100 gpu: Performance & innovation for gpu computing,.

DFModel: Design Space Optimization of Large-Scale Systems Exploiting Dataflow Mappings Nvidia a100 gpu: Performance & innovation for gpu computing,

Reference 21

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Observation 81f94c4c-3c00-43a8-ad27-b83747615e69 · outbound

This paper cites Insights from nvidia research,.

DFModel: Design Space Optimization of Large-Scale Systems Exploiting Dataflow Mappings Insights from nvidia research,

Reference 22

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Observation 46cd57d9-59cf-49ed-8951-72f7a79f972a · outbound

This paper cites Flashattention-2: Faster attention with better parallelism and work partitioning,.

DFModel: Design Space Optimization of Large-Scale Systems Exploiting Dataflow Mappings Flashattention-2: Faster attention with better parallelism and work partitioning,

Reference 23

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Observation eb2bfad5-933f-48f7-bb0b-2042ca56f2fb · outbound

This paper cites Flashattention: fast and memory-efficient exact attention with io-awareness,.

DFModel: Design Space Optimization of Large-Scale Systems Exploiting Dataflow Mappings Flashattention: fast and memory-efficient exact attention with io-awareness,

Reference 24

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Observation d5ea42c9-bedf-4ebc-abf1-dfcf135e9fb2 · outbound

This paper cites Explainable-dse: An agile and explainable exploration of efficient hw/sw codesigns of deep learning accelerators using bottleneck analysis,.

DFModel: Design Space Optimization of Large-Scale Systems Exploiting Dataflow Mappings Explainable-dse: An agile and explainable exploration of efficient hw/sw codesigns of deep learning accelerators using bottleneck analysis,

Reference 25

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Observation 2f89df17-e651-4374-9966-eb9f16a1d1d1 · outbound

This paper cites Large scale distributed deep networks,.

DFModel: Design Space Optimization of Large-Scale Systems Exploiting Dataflow Mappings Large scale distributed deep networks,

Reference 26

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Observation d9ec04b6-c438-4882-b9a0-66b1cf54ccda · outbound

This paper cites ECOS: An SOCP solver for embedded systems,.

DFModel: Design Space Optimization of Large-Scale Systems Exploiting Dataflow Mappings ECOS: An SOCP solver for embedded systems,

Reference 27

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Observation 3b0464e9-8a89-4d69-b3be-9c2c0fca3bb4 · outbound

This paper cites The Llama 3 Herd of Models.

DFModel: Design Space Optimization of Large-Scale Systems Exploiting Dataflow Mappings The Llama 3 Herd of Models

Reference 28

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Observation b42e3df9-360a-433b-993a-c2ad5d74da76 · outbound

This paper cites A comprehensive performance study of large language models on novel ai accelerators,.

DFModel: Design Space Optimization of Large-Scale Systems Exploiting Dataflow Mappings A comprehensive performance study of large language models on novel ai accelerators,

Reference 29

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Observation dd572071-1bbc-4941-822c-59d5f7e717bb · outbound

This paper cites Parameter selection and preconditioning for a graph form solver,.

DFModel: Design Space Optimization of Large-Scale Systems Exploiting Dataflow Mappings Parameter selection and preconditioning for a graph form solver,

Reference 30

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Observation 4595894f-7f68-44e2-9611-64912da8ff2c · outbound

This paper cites Tetris: Scalable and efficient neural network acceleration with 3d memory,.

DFModel: Design Space Optimization of Large-Scale Systems Exploiting Dataflow Mappings Tetris: Scalable and efficient neural network acceleration with 3d memory,

Reference 31

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Observation 36438182-d3e9-40c1-9fcc-a503f82f2192 · outbound

This paper cites Habitat: A {Runtime-Based} computational performance predictor for deep neural network training,.

DFModel: Design Space Optimization of Large-Scale Systems Exploiting Dataflow Mappings Habitat: A {Runtime-Based} computational performance predictor for deep neural network training,

Reference 32

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Observation 38ed3e78-5386-40fe-bf85-3d1ce76bc9e8 · outbound

This paper cites Looptree: Exploring the fused-layer dataflow accelerator design space,.

DFModel: Design Space Optimization of Large-Scale Systems Exploiting Dataflow Mappings Looptree: Exploring the fused-layer dataflow accelerator design space,

Reference 33

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Observation 25fcaaeb-02a0-4b18-9f62-b8551ae93b77 · outbound

This paper cites The netflix recommender system: Algorithms, business value, and innovation,.

DFModel: Design Space Optimization of Large-Scale Systems Exploiting Dataflow Mappings The netflix recommender system: Algorithms, business value, and innovation,

Reference 34

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Observation 83a7877e-5601-42c8-bb8e-0bfcaf27c484 · outbound

This paper cites Demystifying the characteristics of 3d-stacked memories: A case study for hybrid memory cube,.

DFModel: Design Space Optimization of Large-Scale Systems Exploiting Dataflow Mappings Demystifying the characteristics of 3d-stacked memories: A case study for hybrid memory cube,

Reference 35

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Observation 404b426c-9e2c-4935-9081-fa8b2befcba6 · outbound

This paper cites Cosa: Scheduling by constrained optimization for spatial accelerators,.

DFModel: Design Space Optimization of Large-Scale Systems Exploiting Dataflow Mappings Cosa: Scheduling by constrained optimization for spatial accelerators,

Reference 36

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This paper cites Mind the gap: Attainable data movement and operational intensity bounds for tensor algorithms,.

DFModel: Design Space Optimization of Large-Scale Systems Exploiting Dataflow Mappings Mind the gap: Attainable data movement and operational intensity bounds for tensor algorithms,

Reference 37

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Observation 196e8470-4eba-46ed-896a-2b3d06a25a23 · outbound

This paper cites Huang, Y.

DFModel: Design Space Optimization of Large-Scale Systems Exploiting Dataflow Mappings Huang, Y

Reference 38

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Observation 610566af-9043-4052-95a7-14289ad4b1d7 · outbound

This paper cites Calculon: a methodology and tool for high-level co-design of systems and large language models,.

DFModel: Design Space Optimization of Large-Scale Systems Exploiting Dataflow Mappings Calculon: a methodology and tool for high-level co-design of systems and large language models,

Reference 39

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Observation c78afecc-b2db-4a96-99bf-e118dacd715f · outbound

This paper cites Large language models and simple, stupid bugs,.

DFModel: Design Space Optimization of Large-Scale Systems Exploiting Dataflow Mappings Large language models and simple, stupid bugs,

Reference 40

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Observation 80cd3b32-3326-4845-9e54-c34d6c83b614 · outbound

This paper cites Beyond data and model parallelism for deep neural networks.

DFModel: Design Space Optimization of Large-Scale Systems Exploiting Dataflow Mappings Beyond data and model parallelism for deep neural networks

Reference 41

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Observation b9bcbd0d-1585-4c4b-8562-608587a02784 · outbound

This paper cites Tpu v4: An optically reconfigurable supercomputer for machine learning with hardware support for embeddings,.

DFModel: Design Space Optimization of Large-Scale Systems Exploiting Dataflow Mappings Tpu v4: An optically reconfigurable supercomputer for machine learning with hardware support for embeddings,

Reference 42

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Observation bebff07b-a2a9-4616-945c-947ad27660e6 · outbound

This paper cites Available: https://doi.org/10.1145/3581784.3607102.

DFModel: Design Space Optimization of Large-Scale Systems Exploiting Dataflow Mappings Available: https://doi.org/10.1145/3581784.3607102

Reference 43

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Observation 6a3210c3-2b44-4645-b462-60e6cf54358b · outbound

This paper cites Parallel implementation of 3d fft with volumetric decomposition schemes for efficient molecular dynamics simulations,.

DFModel: Design Space Optimization of Large-Scale Systems Exploiting Dataflow Mappings Parallel implementation of 3d fft with volumetric decomposition schemes for efficient molecular dynamics simulations,

Reference 44

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Observation c5177e3e-0cf5-4692-8482-bddc0fe15aa2 · outbound

This paper cites Neurocube: A programmable digital neuromorphic architecture with high-density 3d memory,.

DFModel: Design Space Optimization of Large-Scale Systems Exploiting Dataflow Mappings Neurocube: A programmable digital neuromorphic architecture with high-density 3d memory,

Reference 45

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Observation 68084043-1cd1-4527-8764-7bd356e044a8 · outbound

This paper cites Snuhpl: high performance linpack for heterogeneous gpus,.

DFModel: Design Space Optimization of Large-Scale Systems Exploiting Dataflow Mappings Snuhpl: high performance linpack for heterogeneous gpus,

Reference 46

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Observation 7f5fd9d6-f6fe-42cc-8e2a-a8c6892ed031 · outbound

This paper cites Ten lessons from three generations shaped google’s tpuv4i : Industrial product,.

DFModel: Design Space Optimization of Large-Scale Systems Exploiting Dataflow Mappings Ten lessons from three generations shaped google’s tpuv4i : Industrial product,

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-11T10:39:45.894975Z

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Observation 166a169b-bf7f-4633-81b0-a187b603d845 · outbound

This paper cites Mapzero: Mapping for coarse-grained reconfigurable architectures with reinforcement learning and monte-carlo tree search,.

DFModel: Design Space Optimization of Large-Scale Systems Exploiting Dataflow Mappings Mapzero: Mapping for coarse-grained reconfigurable architectures with reinforcement learning and monte-carlo tree search,

Reference 48

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Observation 1018c61f-b2a8-4aea-a707-5725d346d482 · outbound

This paper cites Task parallelism-aware deep neural net- work scheduling on multiple hybrid memory cube-based processing-in- memory,.

DFModel: Design Space Optimization of Large-Scale Systems Exploiting Dataflow Mappings Task parallelism-aware deep neural net- work scheduling on multiple hybrid memory cube-based processing-in- memory,

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T10:39:48.291280Z

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Observation 187444b6-f218-4e9f-889a-9ec39527c103 · outbound

This paper cites Fast inference from transform- ers via speculative decoding,.

DFModel: Design Space Optimization of Large-Scale Systems Exploiting Dataflow Mappings Fast inference from transform- ers via speculative decoding,

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T10:39:48.274908Z

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Observation 4ca1d36e-8e3c-4cde-87a9-6c663d82e60c · outbound

This paper cites Technology-driven, highly- scalable dragonfly topology,.

DFModel: Design Space Optimization of Large-Scale Systems Exploiting Dataflow Mappings Technology-driven, highly- scalable dragonfly topology,

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T10:39:48.306514Z

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Observation 7ac2a696-4268-4122-88c8-a346fc3b21b1 · outbound

This paper cites Multi-million core, multi-wafer ai cluster,.

DFModel: Design Space Optimization of Large-Scale Systems Exploiting Dataflow Mappings Multi-million core, multi-wafer ai cluster,

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T10:39:48.244214Z

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Observation 60c6a0be-9700-463e-8684-ad27f367dd71 · outbound

This paper cites Cerebras architecture deep dive: First look inside the hw/sw co-design for deep learning : Cerebras systems,.

DFModel: Design Space Optimization of Large-Scale Systems Exploiting Dataflow Mappings Cerebras architecture deep dive: First look inside the hw/sw co-design for deep learning : Cerebras systems,

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T10:39:48.228198Z

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Observation 5ebec0b9-b552-48a3-bb0b-543db9d3d9cc · outbound

This paper cites Wafer-scale ai: Enabling unprecedented ai compute performance,.

DFModel: Design Space Optimization of Large-Scale Systems Exploiting Dataflow Mappings Wafer-scale ai: Enabling unprecedented ai compute performance,

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T10:39:48.213030Z

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Observation 75a1b6f3-95f3-487a-922c-0f53367c1623 · outbound

This paper cites Evaluating modern gpu interconnect: Pcie, nvlink, nv-sli, nvswitch and gpudirect,.

DFModel: Design Space Optimization of Large-Scale Systems Exploiting Dataflow Mappings Evaluating modern gpu interconnect: Pcie, nvlink, nv-sli, nvswitch and gpudirect,

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T10:39:48.259661Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 86628288-efa1-40c8-9a74-8ba95003b0a6 · outbound

This paper cites Ai-based language models powering drug discovery and development,.

DFModel: Design Space Optimization of Large-Scale Systems Exploiting Dataflow Mappings Ai-based language models powering drug discovery and development,

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T10:39:48.182140Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 778aad18-ee29-4a92-9c0d-e78bb06c18ae · outbound

This paper cites Apex: A framework for automated processing element design space exploration using frequent subgraph analysis,.

DFModel: Design Space Optimization of Large-Scale Systems Exploiting Dataflow Mappings Apex: A framework for automated processing element design space exploration using frequent subgraph analysis,

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-11T10:39:45.969411Z

Source-reported events for the cited work

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Observation 031a736c-5daf-40d5-85a4-9f0f79f79b6e · outbound

This paper cites Specinfer: Accelerating large language model serving with tree-based speculative inference and verification,.

DFModel: Design Space Optimization of Large-Scale Systems Exploiting Dataflow Mappings Specinfer: Accelerating large language model serving with tree-based speculative inference and verification,

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-11T10:39:45.974403Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3eb44d79-5159-4328-858d-b3559a5ac4fd · outbound

This paper cites Building a performance model for deep learning recommendation model training on gpus,.

DFModel: Design Space Optimization of Large-Scale Systems Exploiting Dataflow Mappings Building a performance model for deep learning recommendation model training on gpus,

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T10:39:48.198092Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 76fc7bfa-2bfc-4697-a3af-4ac92379793e · outbound

This paper cites Amped: An analytical model for performance in dis- tributed training of transformers,.

DFModel: Design Space Optimization of Large-Scale Systems Exploiting Dataflow Mappings Amped: An analytical model for performance in dis- tributed training of transformers,

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T10:39:48.131661Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 375c766e-4665-4ee1-aca2-6debb3e537c4 · outbound

This paper cites Software-hardware co-design for fast and scalable training of deep learning recommendation models,.

DFModel: Design Space Optimization of Large-Scale Systems Exploiting Dataflow Mappings Software-hardware co-design for fast and scalable training of deep learning recommendation models,

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-11T10:39:45.988856Z

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Unavailable: canonical work link unavailable.

Observation e64b6151-a9ee-43a7-938c-ba83c42136ae · outbound

This paper cites Efficient large-scale language model training on gpu clusters using megatron-lm,.

DFModel: Design Space Optimization of Large-Scale Systems Exploiting Dataflow Mappings Efficient large-scale language model training on gpu clusters using megatron-lm,

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-11T10:39:45.994817Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ed68f8fa-c5ff-40bd-a95a-0fa90f6958cd · outbound

This paper cites Hybrid optimization/heuristic instruction scheduling for programmable accelerator codesign,.

DFModel: Design Space Optimization of Large-Scale Systems Exploiting Dataflow Mappings Hybrid optimization/heuristic instruction scheduling for programmable accelerator codesign,

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T10:39:48.113434Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation b9e0b052-ce9b-4c65-bcec-9f8cd22d4fe1 · outbound

This paper cites New mlperf inference v4.1 benchmark results highlight rapid hardware and software innovations in generative ai systems,.

DFModel: Design Space Optimization of Large-Scale Systems Exploiting Dataflow Mappings New mlperf inference v4.1 benchmark results highlight rapid hardware and software innovations in generative ai systems,

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T10:39:48.147867Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation f3c691bf-354f-4899-951b-1969118a6546 · outbound

This paper cites Timeloop: A systematic approach to dnn accelerator evaluation,.

DFModel: Design Space Optimization of Large-Scale Systems Exploiting Dataflow Mappings Timeloop: A systematic approach to dnn accelerator evaluation,

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T10:39:48.094668Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation c060c718-ff7b-4d04-b5ca-146a27bde65b · outbound

This paper cites Tale of two cs: Computation vs. communication scaling for future transformers on future hardware,.

DFModel: Design Space Optimization of Large-Scale Systems Exploiting Dataflow Mappings Tale of two cs: Computation vs. communication scaling for future transformers on future hardware,

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T10:39:48.078125Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 4caa31ba-3021-48ea-8898-4ea349d39a8a · outbound

This paper cites Sambanova sn40l rdu: Breaking the barrier of trillion+ parameter scale gen ai computing,.

DFModel: Design Space Optimization of Large-Scale Systems Exploiting Dataflow Mappings Sambanova sn40l rdu: Breaking the barrier of trillion+ parameter scale gen ai computing,

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T10:39:48.061641Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation af5b78e3-9a7e-4ad0-807b-d1f28034a5b6 · outbound

This paper cites Sambanova sn10 rdu:accelerating software 2.0 with dataflow,.

DFModel: Design Space Optimization of Large-Scale Systems Exploiting Dataflow Mappings Sambanova sn10 rdu:accelerating software 2.0 with dataflow,

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T10:39:48.044203Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 4e458555-13e5-40c4-9d98-760b70d2a12e · outbound

This paper cites Sambanova sn10 rdu: A 7nm dataflow architecture to accelerate software 2.0,.

DFModel: Design Space Optimization of Large-Scale Systems Exploiting Dataflow Mappings Sambanova sn10 rdu: A 7nm dataflow architecture to accelerate software 2.0,

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T10:39:48.026864Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 60c50edf-530c-41ff-9d48-1382e1272898 · outbound

This paper cites A general constraint-centric scheduling framework for spatial architectures,.

DFModel: Design Space Optimization of Large-Scale Systems Exploiting Dataflow Mappings A general constraint-centric scheduling framework for spatial architectures,

Reference 70

Resolution: unresolved; no resolver link, observed 2026-08-11T10:39:46.009910Z

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Observation b061b25a-9f17-41cc-9875-149e2ac9a188 · outbound

This paper cites Astra-sim: En- abling sw/hw co-design exploration for distributed dl training platforms,.

DFModel: Design Space Optimization of Large-Scale Systems Exploiting Dataflow Mappings Astra-sim: En- abling sw/hw co-design exploration for distributed dl training platforms,

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T10:39:47.998952Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation c7f50dc6-472c-4d82-ab44-4c7569c85360 · outbound

This paper cites Smart memory: Deep learning acceleration in 3d-stacked memories,.

DFModel: Design Space Optimization of Large-Scale Systems Exploiting Dataflow Mappings Smart memory: Deep learning acceleration in 3d-stacked memories,

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T10:39:47.983419Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 67dca5de-d9a9-416a-ba5c-0031e5069a12 · outbound

This paper cites A systematic methodology for characterizing scalability of dnn accelerators using scale-sim,.

DFModel: Design Space Optimization of Large-Scale Systems Exploiting Dataflow Mappings A systematic methodology for characterizing scalability of dnn accelerators using scale-sim,

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T10:39:47.967291Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation d767928e-8982-4bc8-a37f-a512763f4110 · outbound

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

DFModel: Design Space Optimization of Large-Scale Systems Exploiting Dataflow Mappings FlashAttention-3: Fast and Accurate Attention with Asynchrony and Low-precision

Reference 74

Resolution: unresolved; no resolver link, observed 2026-08-11T10:39:46.061299Z

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Observation 7c385a8c-56a9-484a-af02-73a692d6755d · outbound

This paper cites Megatron-LM: Training Multi-Billion Parameter Language Models Using Model Parallelism.

DFModel: Design Space Optimization of Large-Scale Systems Exploiting Dataflow Mappings Megatron-LM: Training Multi-Billion Parameter Language Models Using Model Parallelism

Reference 75

Resolution: unresolved; no resolver link, observed 2026-08-11T10:39:46.066186Z

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Observation a072e38c-5909-45f5-9945-97967b8f0a08 · outbound

This paper cites Language models are unsupervised multitask learners,.

DFModel: Design Space Optimization of Large-Scale Systems Exploiting Dataflow Mappings Language models are unsupervised multitask learners,

Reference 76

Resolution: unresolved; no resolver link, observed 2026-08-11T10:39:46.040750Z

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Observation f9d6e914-9095-4070-a901-45b6290cc4b8 · outbound

This paper cites Optimization of collective communication operations in mpich,.

DFModel: Design Space Optimization of Large-Scale Systems Exploiting Dataflow Mappings Optimization of collective communication operations in mpich,

Reference 77

Resolution: unresolved; no resolver link, observed 2026-08-11T10:39:46.076992Z

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Observation 2105d006-7744-4978-97cf-bbdc68722da8 · outbound

This paper cites LLaMA: Open and Efficient Foundation Language Models.

DFModel: Design Space Optimization of Large-Scale Systems Exploiting Dataflow Mappings LLaMA: Open and Efficient Foundation Language Models

Reference 78

Resolution: unresolved; no resolver link, observed 2026-08-11T10:39:46.082195Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f4fb7a24-29d8-47d6-a5aa-23a9813838ae · outbound

This paper cites Rail-only: A Low-Cost High-Performance Network for Training LLMs with Trillion Parameters.

DFModel: Design Space Optimization of Large-Scale Systems Exploiting Dataflow Mappings Rail-only: A Low-Cost High-Performance Network for Training LLMs with Trillion Parameters

Reference 79

Resolution: unresolved; no resolver link, observed 2026-08-11T10:39:46.087199Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f662a66b-37bf-4634-9184-ad64aaff0b00 · outbound

This paper cites Roofline: an insightful visual performance model for multicore architectures,.

DFModel: Design Space Optimization of Large-Scale Systems Exploiting Dataflow Mappings Roofline: an insightful visual performance model for multicore architectures,

Reference 80

Resolution: unresolved; no resolver link, observed 2026-08-11T10:39:46.092212Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d8fbd18d-dab6-4b84-b832-9eb676fcada6 · outbound

This paper cites Tacos: Topology-aware collective algorithm synthesizer for distributed 21 machine learning,.

DFModel: Design Space Optimization of Large-Scale Systems Exploiting Dataflow Mappings Tacos: Topology-aware collective algorithm synthesizer for distributed 21 machine learning,

Reference 81

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T10:39:47.951761Z

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Observation c54bffc8-012f-435c-92dc-508d0e9dcf34 · outbound

This paper cites Cosmological perturbation theory using the fftlog: formalism and connection to qft loop integrals,.

DFModel: Design Space Optimization of Large-Scale Systems Exploiting Dataflow Mappings Cosmological perturbation theory using the fftlog: formalism and connection to qft loop integrals,

Reference 82

Resolution: unresolved; no resolver link, observed 2026-08-11T10:39:46.071713Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dedda84a-3337-4e65-ad58-c8ca9b9a8f59 · outbound

This paper cites Pipemare: Asynchronous pipeline parallel dnn training,.

DFModel: Design Space Optimization of Large-Scale Systems Exploiting Dataflow Mappings Pipemare: Asynchronous pipeline parallel dnn training,

Reference 83

Resolution: verified exact; raw_fallback, observed 2026-08-11T10:39:46.436545Z

Source-reported events for the cited work

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Observation ea0da805-b3c8-422f-8d9e-1b3c4fa659ef · outbound

This paper cites LLM Inference Unveiled: Survey and Roofline Model Insights.

DFModel: Design Space Optimization of Large-Scale Systems Exploiting Dataflow Mappings LLM Inference Unveiled: Survey and Roofline Model Insights

Reference 84

Resolution: unresolved; no resolver link, observed 2026-08-11T10:39:46.112740Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dc168291-6b54-490c-aa55-05f5b616c9ce · outbound

This paper cites A full-stack search technique for domain optimized deep learning accelerators,.

DFModel: Design Space Optimization of Large-Scale Systems Exploiting Dataflow Mappings A full-stack search technique for domain optimized deep learning accelerators,

Reference 85

Resolution: unresolved; no resolver link, observed 2026-08-11T10:39:46.118281Z

Source-reported events for the cited work

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Observation f7767479-6219-43b4-8601-fb5466f9beb9 · outbound

This paper cites Llmcompass: Enabling efficient hardware design for large language model inference,.

DFModel: Design Space Optimization of Large-Scale Systems Exploiting Dataflow Mappings Llmcompass: Enabling efficient hardware design for large language model inference,

Reference 86

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T10:39:47.935371Z

Source-reported events for the cited work

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Observation 56b3fdb8-ff8d-4004-b5cb-6a1fc97e4799 · outbound

This paper cites An efficient implementation of the back-propagation algorithm on the connection machine cm-2,.

DFModel: Design Space Optimization of Large-Scale Systems Exploiting Dataflow Mappings An efficient implementation of the back-propagation algorithm on the connection machine cm-2,

Reference 87

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T10:39:47.917463Z

Source-reported events for the cited work

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Observation 3e10a6f4-19ff-4017-96f0-177a41778be0 · outbound

This paper cites Libra: Enabling workload-aware multi-dimensional network topology optimization for distributed training of large ai models,.

DFModel: Design Space Optimization of Large-Scale Systems Exploiting Dataflow Mappings Libra: Enabling workload-aware multi-dimensional network topology optimization for distributed training of large ai models,

Reference 88

Resolution: unresolved; no resolver link, observed 2026-08-11T10:39:46.102818Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a424b682-2eee-4696-b16d-f53314b43231 · outbound

This paper cites Towards higher performance and robust compilation for cgra modulo scheduling,.

DFModel: Design Space Optimization of Large-Scale Systems Exploiting Dataflow Mappings Towards higher performance and robust compilation for cgra modulo scheduling,

Reference 89

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T10:39:47.883215Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 71ec727e-2b22-42ca-8e77-4258e78d08e6 · outbound

This paper cites Alpa: Automating inter- and Intra-Operator parallelism for distributed deep learning,.

DFModel: Design Space Optimization of Large-Scale Systems Exploiting Dataflow Mappings Alpa: Automating inter- and Intra-Operator parallelism for distributed deep learning,

Reference 90

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T10:39:47.866412Z

Source-reported events for the cited work

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Observation c52c511f-26b4-448a-824a-41f8b59aea50 · outbound

This paper cites {DistServe}: Disaggregating prefill and decoding for goodput-optimized large language model serving,.

DFModel: Design Space Optimization of Large-Scale Systems Exploiting Dataflow Mappings {DistServe}: Disaggregating prefill and decoding for goodput-optimized large language model serving,

Reference 91

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T10:39:47.850485Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation dfdd433c-1b59-4d61-a451-3a48e5a8d3aa · outbound

This paper cites Sara: Scaling a reconfigurable dataflow accelerator,.

DFModel: Design Space Optimization of Large-Scale Systems Exploiting Dataflow Mappings Sara: Scaling a reconfigurable dataflow accelerator,

Reference 94

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T10:39:47.899470Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation a3e0e52d-b100-46a3-8bc4-341404a31655 · outbound

This paper cites Available: https://proceedings.neurips.cc/paper files/ paper/2020/file/1457c0d6bfcb4967418bfb8ac142f64a-Paper.pdf.

DFModel: Design Space Optimization of Large-Scale Systems Exploiting Dataflow Mappings Available: https://proceedings.neurips.cc/paper files/ paper/2020/file/1457c0d6bfcb4967418bfb8ac142f64a-Paper.pdf

Reference 1901

Resolution: unresolved; no resolver link, observed 2026-08-11T10:39:45.743045Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c9335a36-c724-49d8-b860-d4e7e911be7c · outbound

This paper cites Available: https://www.microway.com/knowledge-center- articles/performance-characteristics-of-common-transports-buses/.

DFModel: Design Space Optimization of Large-Scale Systems Exploiting Dataflow Mappings Available: https://www.microway.com/knowledge-center- articles/performance-characteristics-of-common-transports-buses/

Reference 2013

Resolution: unresolved; no resolver link, observed 2026-08-11T10:39:45.654884Z

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Unavailable: canonical work link unavailable.

Observation 87352225-7c40-49c7-872f-23de94a7d500 · outbound

This paper cites Available: https://doi.org/10.1145/3243176.3243212.

DFModel: Design Space Optimization of Large-Scale Systems Exploiting Dataflow Mappings Available: https://doi.org/10.1145/3243176.3243212

Reference 2018

Resolution: metadata mismatch; raw_fallback, observed 2026-08-11T10:39:46.856234Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 025cfcae-f0c7-4429-9f9e-fd399d32a3b6 · outbound

This paper cites Available: https://www.sciencedirect.com/science/article/ pii/S1359644621002816.

DFModel: Design Space Optimization of Large-Scale Systems Exploiting Dataflow Mappings Available: https://www.sciencedirect.com/science/article/ pii/S1359644621002816

Reference 2021

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T10:39:48.164461Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 702d494f-3dfa-4c87-aaef-c07b89db59d6 · outbound

This paper cites A Comprehensive Performance Study of Large Language Models on Novel AI Accelerators.

DFModel: Design Space Optimization of Large-Scale Systems Exploiting Dataflow Mappings A Comprehensive Performance Study of Large Language Models on Novel AI Accelerators

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-11T10:39:45.814412Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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