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2020 – today
- 2024
[j1]Newsha Ardalani
, Saptadeep Pal, Puneet Gupta:
DeepFlow: A Cross-Stack Pathfinding Framework for Distributed AI Systems. ACM Trans. Design Autom. Electr. Syst. 29(2): 30:1-30:20 (2024)- [c11]Anas Mahmoud, Mostafa Elhoushi, Amro Abbas, Yu Yang, Newsha Ardalani, Hugh Leather, Ari S. Morcos:
Sieve: Multimodal Dataset Pruning Using Image Captioning Models. CVPR 2024: 22423-22432 - [c10]Samuel Hsia, Alicia Golden, Bilge Acun, Newsha Ardalani, Zachary DeVito, Gu-Yeon Wei, David Brooks, Carole-Jean Wu:
MAD-Max Beyond Single-Node: Enabling Large Machine Learning Model Acceleration on Distributed Systems. ISCA 2024: 818-833 - [c9]Haiyang Huang, Newsha Ardalani, Anna Y. Sun, Liu Ke, Shruti Bhosale, Hsien-Hsin S. Lee, Carole-Jean Wu, Benjamin Lee:
Toward Efficient Inference for Mixture of Experts. NeurIPS 2024 - [i16]Vasu Sharma, Karthik Padthe, Newsha Ardalani, Kushal Tirumala, Russell Howes, Hu Xu, Po-Yao Huang, Shang-Wen Li, Armen Aghajanyan, Gargi Ghosh, Luke Zettlemoyer:
Text Quality-Based Pruning for Efficient Training of Language Models. CoRR abs/2405.01582 (2024) - 2023
- [c8]Samuel Hsia, Udit Gupta, Bilge Acun, Newsha Ardalani, Pan Zhong, Gu-Yeon Wei, David Brooks, Carole-Jean Wu:
MP-Rec: Hardware-Software Co-design to Enable Multi-path Recommendation. ASPLOS (3) 2023: 449-465 - [c7]Mark Mazumder, Colby R. Banbury, Xiaozhe Yao, Bojan Karlas, William Gaviria Rojas, Sudnya Frederick Diamos, Greg Diamos, Lynn He, Alicia Parrish, Hannah Rose Kirk, Jessica Quaye, Charvi Rastogi, Douwe Kiela, David Jurado, David Kanter, Rafael Mosquera, Will Cukierski, Juan Ciro, Lora Aroyo, Bilge Acun, Lingjiao Chen, Mehul Raje, Max Bartolo, Evan Sabri Eyuboglu, Amirata Ghorbani, Emmett D. Goodman, Addison Howard, Oana Inel, Tariq Kane, Christine R. Kirkpatrick, D. Sculley, Tzu-Sheng Kuo, Jonas W. Mueller, Tristan Thrush, Joaquin Vanschoren, Margaret Warren, Adina Williams, Serena Yeung, Newsha Ardalani, Praveen K. Paritosh, Ce Zhang, James Y. Zou, Carole-Jean Wu, Cody Coleman, Andrew Y. Ng, Peter Mattson, Vijay Janapa Reddi:
DataPerf: Benchmarks for Data-Centric AI Development. NeurIPS 2023 - [i15]Samuel Hsia, Udit Gupta, Bilge Acun, Newsha Ardalani, Pan Zhong, Gu-Yeon Wei, David Brooks, Carole-Jean Wu:
MP-Rec: Hardware-Software Co-Design to Enable Multi-Path Recommendation. CoRR abs/2302.10872 (2023) - [i14]Haiyang Huang, Newsha Ardalani, Anna Y. Sun, Liu Ke, Hsien-Hsin S. Lee, Anjali Sridhar, Shruti Bhosale, Carole-Jean Wu, Benjamin Lee:
Towards MoE Deployment: Mitigating Inefficiencies in Mixture-of-Expert (MoE) Inference. CoRR abs/2303.06182 (2023) - [i13]Anas Mahmoud, Mostafa Elhoushi, Amro Abbas, Yu Yang, Newsha Ardalani, Hugh Leather, Ari Morcos:
SIEVE: Multimodal Dataset Pruning Using Image Captioning Models. CoRR abs/2310.02110 (2023) - [i12]Samuel Hsia, Alicia Golden, Bilge Acun, Newsha Ardalani, Zachary DeVito, Gu-Yeon Wei, David Brooks, Carole-Jean Wu:
MAD Max Beyond Single-Node: Enabling Large Machine Learning Model Acceleration on Distributed Systems. CoRR abs/2310.02784 (2023) - [i11]Lingjiao Chen, Bilge Acun, Newsha Ardalani, Yifan Sun, Feiyang Kang, Hanrui Lyu, Yongchan Kwon, Ruoxi Jia, Carole-Jean Wu, Matei Zaharia, James Zou:
Data Acquisition: A New Frontier in Data-centric AI. CoRR abs/2311.13712 (2023) - [i10]Yu Yang, Aaditya K. Singh, Mostafa Elhoushi, Anas Mahmoud, Kushal Tirumala, Fabian Gloeckle, Baptiste Rozière, Carole-Jean Wu, Ari S. Morcos, Newsha Ardalani:
Decoding Data Quality via Synthetic Corruptions: Embedding-guided Pruning of Code Data. CoRR abs/2312.02418 (2023) - 2022
- [c6]Carole-Jean Wu, Ramya Raghavendra, Udit Gupta, Bilge Acun, Newsha Ardalani, Kiwan Maeng, Gloria Chang, Fiona Aga Behram, Jinshi Huang, Charles Bai, Michael Gschwind, Anurag Gupta, Myle Ott, Anastasia Melnikov, Salvatore Candido, David Brooks, Geeta Chauhan, Benjamin Lee, Hsien-Hsin S. Lee, Bugra Akyildiz, Maximilian Balandat, Joe Spisak, Ravi Jain, Mike Rabbat, Kim M. Hazelwood:
Sustainable AI: Environmental Implications, Challenges and Opportunities. MLSys 2022 - [i9]Ehsan Valavi, Joel Hestness, Newsha Ardalani, Marco Iansiti:
Time and the Value of Data. CoRR abs/2203.09118 (2022) - [i8]Ehsan Valavi, Joel Hestness, Marco Iansiti, Newsha Ardalani, Feng Zhu, Karim R. Lakhani:
Time Dependency, Data Flow, and Competitive Advantage. CoRR abs/2203.09128 (2022) - [i7]Mark Mazumder, Colby R. Banbury, Xiaozhe Yao, Bojan Karlas, William Gaviria Rojas, Sudnya Frederick Diamos, Greg Diamos, Lynn He, Douwe Kiela, David Jurado, David Kanter, Rafael Mosquera, Juan Ciro, Lora Aroyo, Bilge Acun, Sabri Eyuboglu, Amirata Ghorbani, Emmett D. Goodman, Tariq Kane, Christine R. Kirkpatrick, Tzu-Sheng Kuo, Jonas Mueller, Tristan Thrush, Joaquin Vanschoren, Margaret Warren, Adina Williams, Serena Yeung, Newsha Ardalani, Praveen K. Paritosh, Ce Zhang, James Zou, Carole-Jean Wu, Cody Coleman, Andrew Y. Ng, Peter Mattson, Vijay Janapa Reddi:
DataPerf: Benchmarks for Data-Centric AI Development. CoRR abs/2207.10062 (2022) - [i6]Newsha Ardalani, Carole-Jean Wu, Zeliang Chen, Bhargav Bhushanam, Adnan Aziz:
Understanding Scaling Laws for Recommendation Models. CoRR abs/2208.08489 (2022) - [i5]Newsha Ardalani, Saptadeep Pal, Puneet Gupta:
DeepFlow: A Cross-Stack Pathfinding Framework for Distributed AI Systems. CoRR abs/2211.03309 (2022) - 2021
- [i4]Carole-Jean Wu, Ramya Raghavendra, Udit Gupta, Bilge Acun, Newsha Ardalani, Kiwan Maeng, Gloria Chang, Fiona Aga Behram, James Huang, Charles Bai, Michael Gschwind, Anurag Gupta, Myle Ott, Anastasia Melnikov, Salvatore Candido, David Brooks, Geeta Chauhan, Benjamin Lee, Hsien-Hsin S. Lee, Bugra Akyildiz, Maximilian Balandat, Joe Spisak, Ravi Jain, Mike Rabbat, Kim M. Hazelwood:
Sustainable AI: Environmental Implications, Challenges and Opportunities. CoRR abs/2111.00364 (2021)
2010 – 2019
- 2019
- [c5]Joel Hestness, Newsha Ardalani, Gregory F. Diamos:
Beyond human-level accuracy: computational challenges in deep learning. PPoPP 2019: 1-14 - [i3]Newsha Ardalani, Urmish Thakker, Aws Albarghouthi, Karu Sankaralingam:
A Static Analysis-based Cross-Architecture Performance Prediction Using Machine Learning. CoRR abs/1906.07840 (2019) - [i2]Joel Hestness, Newsha Ardalani, Greg Diamos:
Beyond Human-Level Accuracy: Computational Challenges in Deep Learning. CoRR abs/1909.01736 (2019) - 2018
- [c4]Tony Nowatzki, Newsha Ardalani, Karthikeyan Sankaralingam, Jian Weng:
Hybrid optimization/heuristic instruction scheduling for programmable accelerator codesign. PACT 2018: 36:1-36:15 - 2017
- [c3]Tony Nowatzki, Vinay Gangadhar, Newsha Ardalani, Karthikeyan Sankaralingam:
Stream-Dataflow Acceleration. ISCA 2017: 416-429 - [i1]Joel Hestness, Sharan Narang, Newsha Ardalani, Gregory F. Diamos, Heewoo Jun, Hassan Kianinejad, Md. Mostofa Ali Patwary, Yang Yang, Yanqi Zhou:
Deep Learning Scaling is Predictable, Empirically. CoRR abs/1712.00409 (2017) - 2015
- [c2]Newsha Ardalani, Clint Lestourgeon, Karthikeyan Sankaralingam, Xiaojin Zhu:
Cross-architecture performance prediction (XAPP) using CPU code to predict GPU performance. MICRO 2015: 725-737
2000 – 2009
- 2009
- [c1]Newsha Ardalani, Amirali Baniasadi:
Write Invalidation Analysis in Chip Multiprocessors. PATMOS 2009: 196-205
Coauthor Index
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