MLSYSIM: First-Principles Infrastructure Modeling for Machine Learning Systems | Paper Citation Record

Observation f200c9ca-de59-40da-a8cc-dfc4fa3a7d2d · outbound

This paper cites and Tumanov, Alexey and Ramjee, Ramachandran , year =.

MLSYSIM: First-Principles Infrastructure Modeling for Machine Learning Systems and Tumanov, Alexey and Ramjee, Ramachandran , year =

Reference 2

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Observation d8e821d4-1667-451d-bf7d-e6223cc6fc9d · outbound

This paper cites and Tumanov, Alexey and Ramjee, Ramachandran , year =.

MLSYSIM: First-Principles Infrastructure Modeling for Machine Learning Systems and Tumanov, Alexey and Ramjee, Ramachandran , year =

Reference 3

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Observation 46a4171f-798a-4956-81c7-4ab1a21b6a24 · outbound

This paper cites OpenAI Blog , publisher =.

MLSYSIM: First-Principles Infrastructure Modeling for Machine Learning Systems OpenAI Blog , publisher =

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Observation 07da43f6-9e81-4859-9718-97330ec51864 · outbound

This paper cites 2018 , publisher =.

MLSYSIM: First-Principles Infrastructure Modeling for Machine Learning Systems 2018 , publisher =

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Observation 16e6b657-6e57-4fb7-b893-e1275a3aa098 · outbound

This paper cites Journal of Machine Learning Research , volume =.

MLSYSIM: First-Principles Infrastructure Modeling for Machine Learning Systems Journal of Machine Learning Research , volume =

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Observation 867029bc-65d9-4e3f-b9dd-17834e7f482b · outbound

This paper cites Frans and Morris, Robert , year =.

MLSYSIM: First-Principles Infrastructure Modeling for Machine Learning Systems Frans and Morris, Robert , year =

Reference 12

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Observation 9886aafe-8cb1-48ae-9bb8-a358186e2962 · outbound

This paper cites and Ermon, Stefano and Rudra, Atri and R.

MLSYSIM: First-Principles Infrastructure Modeling for Machine Learning Systems and Ermon, Stefano and Rudra, Atri and R

Reference 14

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Observation 45e0bb0d-b358-478b-9fae-606d950044d4 · outbound

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MLSYSIM: First-Principles Infrastructure Modeling for Machine Learning Systems 2012 , journal =

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Observation 6613a586-f3db-4390-a0f8-36e78171ad72 · outbound

This paper cites 2022 , booktitle =.

MLSYSIM: First-Principles Infrastructure Modeling for Machine Learning Systems 2022 , booktitle =

Reference 18

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Observation 1224bd4d-92d2-43e6-927f-e0138caadfc9 · outbound

This paper cites Proceedings of the 12th International Conference on Learning Representations (ICLR) , publisher =.

MLSYSIM: First-Principles Infrastructure Modeling for Machine Learning Systems Proceedings of the 12th International Conference on Learning Representations (ICLR) , publisher =

Reference 19

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Observation 25beb876-9a25-452a-8ddc-b165ba8f1d04 · outbound

This paper cites Proceedings of the 11th International Conference on Learning Representations (ICLR) , publisher =.

MLSYSIM: First-Principles Infrastructure Modeling for Machine Learning Systems Proceedings of the 11th International Conference on Learning Representations (ICLR) , publisher =

Reference 20

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Observation e926c300-4ef7-4963-af16-df363ad0d145 · outbound

This paper cites 2021 , journal =.

MLSYSIM: First-Principles Infrastructure Modeling for Machine Learning Systems 2021 , journal =

Reference 21

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Observation 7d036c83-54b2-4c99-b280-58046baeb20c · outbound

This paper cites and Brooks, David and Wu, Carole-Jean , year =.

MLSYSIM: First-Principles Infrastructure Modeling for Machine Learning Systems and Brooks, David and Wu, Carole-Jean , year =

Reference 22

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Observation 861e67e5-c075-45b1-940e-65dba10798ee · outbound

This paper cites 2022 , booktitle =.

MLSYSIM: First-Principles Infrastructure Modeling for Machine Learning Systems 2022 , booktitle =

Reference 23

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Observation 12eaf00a-c296-4e58-9591-683220d1f632 · outbound

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MLSYSIM: First-Principles Infrastructure Modeling for Machine Learning Systems 2016 , booktitle =

Reference 24

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Observation f1d28c34-8e2f-48fc-b294-c3f9b104005a · outbound

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MLSYSIM: First-Principles Infrastructure Modeling for Machine Learning Systems 2024 , publisher =

Reference 25

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Observation 0ed6b0da-e52f-4155-9e76-3c52f034229c · outbound

This paper cites 2022 , booktitle =.

MLSYSIM: First-Principles Infrastructure Modeling for Machine Learning Systems 2022 , booktitle =

Reference 26

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Observation 07f7dd8c-6f56-4c5f-8ee9-246f8d9069ca · outbound

This paper cites 2019 , booktitle =.

MLSYSIM: First-Principles Infrastructure Modeling for Machine Learning Systems 2019 , booktitle =

Reference 27

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Observation 409c5646-189a-4218-b7ad-f9d12d064b5a · outbound

This paper cites 2017 , booktitle =.

MLSYSIM: First-Principles Infrastructure Modeling for Machine Learning Systems 2017 , booktitle =

Reference 28

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Observation bc7f51a7-4765-4e58-ae03-5e422c045dc4 · outbound

This paper cites 2020 , journal =.

MLSYSIM: First-Principles Infrastructure Modeling for Machine Learning Systems 2020 , journal =

Reference 29

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Observation a8c974df-3c72-4627-850f-a4320459e343 · outbound

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MLSYSIM: First-Principles Infrastructure Modeling for Machine Learning Systems 2023 , note =

Reference 30

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Observation ebfdd119-2b38-4689-8efa-05880384a9fe · outbound

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MLSYSIM: First-Principles Infrastructure Modeling for Machine Learning Systems 1985 , journal =

Reference 32

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Observation ef444520-2b33-404e-a57b-7217c0a513b1 · outbound

This paper cites 2023 , booktitle =.

MLSYSIM: First-Principles Infrastructure Modeling for Machine Learning Systems 2023 , booktitle =

Reference 33

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Observation 6bdd0854-4ddf-43d1-af2c-6b4958665eed · outbound

This paper cites Lumos: Efficient Performance Modeling and Estimation for Large-scale.

MLSYSIM: First-Principles Infrastructure Modeling for Machine Learning Systems Lumos: Efficient Performance Modeling and Estimation for Large-scale

Reference 34

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Observation b0ac2187-5237-418b-ac85-f73ae5079eb7 · outbound

This paper cites Cerebras Architecture Deep Dive: First Look Inside the.

MLSYSIM: First-Principles Infrastructure Modeling for Machine Learning Systems Cerebras Architecture Deep Dive: First Look Inside the

Reference 35

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Observation b56c9a82-1e56-4053-b78f-4d6eef7138dc · outbound

This paper cites Proceedings of Machine Learning and Systems (MLSys) , publisher =.

MLSYSIM: First-Principles Infrastructure Modeling for Machine Learning Systems Proceedings of Machine Learning and Systems (MLSys) , publisher =

Reference 36

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Observation a25a45ff-90a9-47ca-855c-5639a0cddacf · outbound

This paper cites 2024 , journal =.

MLSYSIM: First-Principles Infrastructure Modeling for Machine Learning Systems 2024 , journal =

Reference 38

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MLSYSIM: First-Principles Infrastructure Modeling for Machine Learning Systems 2019 , howpublished =

Reference 39

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MLSYSIM: First-Principles Infrastructure Modeling for Machine Learning Systems 2025 , publisher =

Reference 41

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Observation e1a9446d-ee77-40c6-bc70-ca2e6e258ed6 · outbound

This paper cites Analyzing and Mitigating Data Stalls in.

MLSYSIM: First-Principles Infrastructure Modeling for Machine Learning Systems Analyzing and Mitigating Data Stalls in

Reference 42

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Observation 33ebd170-63fe-4d2d-b575-6fe304265645 · outbound

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MLSYSIM: First-Principles Infrastructure Modeling for Machine Learning Systems 2021 , booktitle =

Reference 43

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Observation a737c0be-2544-4076-9360-e7332904fbdd · outbound

This paper cites 2021 , journal =.

MLSYSIM: First-Principles Infrastructure Modeling for Machine Learning Systems 2021 , journal =

Reference 44

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Observation 4dac24b4-67b9-4139-9d86-c573ed178366 · outbound

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MLSYSIM: First-Principles Infrastructure Modeling for Machine Learning Systems 2014 , publisher =

Reference 47

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MLSYSIM: First-Principles Infrastructure Modeling for Machine Learning Systems 2021 , journal =

Reference 48

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Observation 2ef04bed-e58b-42d9-b35a-0dfabd621ce5 · outbound

This paper cites 2023 , journal =.

MLSYSIM: First-Principles Infrastructure Modeling for Machine Learning Systems 2023 , journal =

Reference 49

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Observation f3f61af8-c870-400a-9688-1c6df84f99d3 · outbound

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MLSYSIM: First-Principles Infrastructure Modeling for Machine Learning Systems and Talwalkar, Ameet , year =

Reference 50

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Observation eb42df78-332f-4580-b69d-ec9f24f8e558 · outbound

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MLSYSIM: First-Principles Infrastructure Modeling for Machine Learning Systems ACM SIGKDD International Conference on Knowledge Discovery and Data Mining , publisher =

Reference 52

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MLSYSIM: First-Principles Infrastructure Modeling for Machine Learning Systems 2017 , booktitle =

Reference 53

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Observation dd730cee-f680-4407-bb6e-805ef2a72c90 · outbound

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MLSYSIM: First-Principles Infrastructure Modeling for Machine Learning Systems and LaPiana, Lia S

Reference 56

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MLSYSIM: First-Principles Infrastructure Modeling for Machine Learning Systems 2019 , note =

Reference 57

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MLSYSIM: First-Principles Infrastructure Modeling for Machine Learning Systems 2006 , publisher =

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MLSYSIM: First-Principles Infrastructure Modeling for Machine Learning Systems Proceedings of the 22nd USENIX Symposium on Networked Systems Design and Implementation (NSDI) , publisher =

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MLSYSIM: First-Principles Infrastructure Modeling for Machine Learning Systems Machine Learning Fleet Efficiency: Analyzing and Optimizing Large-Scale

Reference 63

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MLSYSIM: First-Principles Infrastructure Modeling for Machine Learning Systems 2021 , booktitle =

Reference 66

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MLSYSIM: First-Principles Infrastructure Modeling for Machine Learning Systems SGLang: Efficient Execution of Structured Language Model Programs

Reference 69

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MLSYSIM: First-Principles Infrastructure Modeling for Machine Learning Systems Proceedings of the 18th USENIX Symposium on Operating Systems Design and Implementation (OSDI) , publisher =

Reference 70

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MLSYSIM: First-Principles Infrastructure Modeling for Machine Learning Systems Deep learning with differential privacy

Reference 71

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MLSYSIM: First-Principles Infrastructure Modeling for Machine Learning Systems Taming Throughput-Latency tradeoff in LLM inference with Sarathi-Serve

Reference 72

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MLSYSIM: First-Principles Infrastructure Modeling for Machine Learning Systems Vidur: A Large-Scale Simulation Framework For LLM Inference

Reference 73

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MLSYSIM: First-Principles Infrastructure Modeling for Machine Learning Systems Demystifying AI Platform Design for Distributed Inference of Next-Generation LLM models

Reference 74

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MLSYSIM: First-Principles Infrastructure Modeling for Machine Learning Systems The case for energy-proportional computing

Reference 75

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Observation c4b36731-26f6-4fd0-a7ff-268c7df2f454 · outbound

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MLSYSIM: First-Principles Infrastructure Modeling for Machine Learning Systems The Datacenter as a Computer

Reference 76

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MLSYSIM: First-Principles Infrastructure Modeling for Machine Learning Systems The gem5 simulator

Reference 77

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MLSYSIM: First-Principles Infrastructure Modeling for Machine Learning Systems Unresolved cited work

Reference 78

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MLSYSIM: First-Principles Infrastructure Modeling for Machine Learning Systems PaLM : Scaling language modeling with pathways

Reference 79

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MLSYSIM: First-Principles Infrastructure Modeling for Machine Learning Systems Frans Kaashoek, and Robert Morris

Reference 80

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Reference 81

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MLSYSIM: First-Principles Infrastructure Modeling for Machine Learning Systems Fu, Stefano Ermon, Atri Rudra, and Christopher R \'e

Reference 82

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MLSYSIM: First-Principles Infrastructure Modeling for Machine Learning Systems The tail at scale

Reference 83

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MLSYSIM: First-Principles Infrastructure Modeling for Machine Learning Systems Corrado, Rajat Monga, et al

Reference 84

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MLSYSIM: First-Principles Infrastructure Modeling for Machine Learning Systems Insights into deepseek-v3: Scaling challenges and reflections on hardware for ai architectures

Reference 85

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MLSYSIM: First-Principles Infrastructure Modeling for Machine Learning Systems Check-n-run: a checkpointing system for training deep learning recommendation models

Reference 86

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MLSYSIM: First-Principles Infrastructure Modeling for Machine Learning Systems LLMCarbon : Modeling the end-to-end carbon footprint of large language models

Reference 87

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MLSYSIM: First-Principles Infrastructure Modeling for Machine Learning Systems Switch transformers: Scaling to trillion parameter models with simple and efficient sparsity

Reference 88

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MLSYSIM: First-Principles Infrastructure Modeling for Machine Learning Systems GPTQ : Accurate post-training quantization for generative pre-trained transformers

Reference 89

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Reference 90

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MLSYSIM: First-Principles Infrastructure Modeling for Machine Learning Systems Chasing carbon: The elusive environmental footprint of computing

Reference 91

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Reference 92

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MLSYSIM: First-Principles Infrastructure Modeling for Machine Learning Systems Hennessy, David A

Reference 93

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MLSYSIM: First-Principles Infrastructure Modeling for Machine Learning Systems Training compute-optimal large language models

Reference 94

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MLSYSIM: First-Principles Infrastructure Modeling for Machine Learning Systems Calculon: A methodology and tool for high-level co-design of systems and large language models

Reference 95

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MLSYSIM: First-Principles Infrastructure Modeling for Machine Learning Systems Beyond Data and Model Parallelism for Deep Neural Networks

Reference 96

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MLSYSIM: First-Principles Infrastructure Modeling for Machine Learning Systems Reducing activation recomputation in large transformer models

Reference 97

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MLSYSIM: First-Principles Infrastructure Modeling for Machine Learning Systems Efficient memory management for large language model serving with pagedattention

Reference 98

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MLSYSIM: First-Principles Infrastructure Modeling for Machine Learning Systems Leiserson

Reference 99

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MLSYSIM: First-Principles Infrastructure Modeling for Machine Learning Systems GShard: Scaling Giant Models with Conditional Computation and Automatic Sharding

Reference 100

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MLSYSIM: First-Principles Infrastructure Modeling for Machine Learning Systems Fast inference from transformers via speculative decoding

Reference 101

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MLSYSIM: First-Principles Infrastructure Modeling for Machine Learning Systems llm-analysis: Latency and memory analysis of transformer models

Reference 102

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MLSYSIM: First-Principles Infrastructure Modeling for Machine Learning Systems Lumos: Efficient performance modeling and estimation for large-scale LLM training

Reference 103

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MLSYSIM: First-Principles Infrastructure Modeling for Machine Learning Systems Cerebras architecture deep dive: First look inside the HW/SW co-design for deep learning

Reference 104

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MLSYSIM: First-Principles Infrastructure Modeling for Machine Learning Systems Awq: Activation-aware weight quantization for on-device llm compression and acceleration

Reference 105

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Reference 106

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MLSYSIM: First-Principles Infrastructure Modeling for Machine Learning Systems The Llama 3 Herd of Models

Reference 107

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MLSYSIM: First-Principles Infrastructure Modeling for Machine Learning Systems Energy Usage Reports: Environmental awareness as part of algorithmic accountability

Reference 108

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MLSYSIM: First-Principles Infrastructure Modeling for Machine Learning Systems Mlperf: An industry standard benchmark suite for machine learning performance

Reference 109

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MLSYSIM: First-Principles Infrastructure Modeling for Machine Learning Systems Analyzing and mitigating data stalls in dnn training

Reference 110

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MLSYSIM: First-Principles Infrastructure Modeling for Machine Learning Systems Murray, Jiri Simsa, Ana Klimovic, and Ihor Indyk

Reference 111

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MLSYSIM: First-Principles Infrastructure Modeling for Machine Learning Systems Efficient large-scale language model training on gpu clusters using megatron-lm

Reference 112

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MLSYSIM: First-Principles Infrastructure Modeling for Machine Learning Systems NVIDIA H100 Tensor Core GPU datasheet

Reference 113

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MLSYSIM: First-Principles Infrastructure Modeling for Machine Learning Systems Timeloop: A systematic approach to dnn accelerator evaluation

Reference 114

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MLSYSIM: First-Principles Infrastructure Modeling for Machine Learning Systems Splitwise: Efficient generative llm inference using phase splitting

Reference 115

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MLSYSIM: First-Principles Infrastructure Modeling for Machine Learning Systems Carbon Emissions and Large Neural Network Training

Reference 116

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MLSYSIM: First-Principles Infrastructure Modeling for Machine Learning Systems Patterson and John L

Reference 117

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MLSYSIM: First-Principles Infrastructure Modeling for Machine Learning Systems Efficiently scaling transformer inference

Reference 118

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MLSYSIM: First-Principles Infrastructure Modeling for Machine Learning Systems Sparks, and Ameet Talwalkar

Reference 119

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MLSYSIM: First-Principles Infrastructure Modeling for Machine Learning Systems Generalized Slow Roll for Tensors

Reference 120

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MLSYSIM: First-Principles Infrastructure Modeling for Machine Learning Systems Machine Learning Systems: Principles and Practices of Engineering Artificially Intelligent Systems

Reference 121

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MLSYSIM: First-Principles Infrastructure Modeling for Machine Learning Systems TinyTorch : A progressive educational framework for machine learning systems

Reference 122

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