Newsha Ardalani

Publication Activity (10 Years)

Years Active: 2009-2024
Publications (10 Years): 24

Top Topics

Machine Learning

Competitive Advantage

Top Venues

Publications

Newsha Ardalani, Saptadeep Pal, Puneet Gupta
DeepFlow: A Cross-Stack Pathfinding Framework for Distributed AI Systems. ACM Trans. Design Autom. Electr. Syst. 29 (2) (2024)
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)
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 (2024)
Anas Mahmoud, Mostafa Elhoushi, Amro Abbas, Yu Yang, Newsha Ardalani, Hugh Leather, Ari Morcos
SIEVE: Multimodal Dataset Pruning Using Image Captioning Models. CoRR (2023)
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 (2023)
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)
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 (2023)
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)
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 (2023)
Haiyang Huang, Newsha Ardalani, Anna 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 (2023)
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 (2023)
Newsha Ardalani, Carole-Jean Wu, Zeliang Chen, Bhargav Bhushanam, Adnan Aziz
Understanding Scaling Laws for Recommendation Models. CoRR (2022)
Ehsan Valavi, Joel Hestness, Newsha Ardalani, Marco Iansiti
Time and the Value of Data. CoRR (2022)
Newsha Ardalani, Saptadeep Pal, Puneet Gupta
DeepFlow: A Cross-Stack Pathfinding Framework for Distributed AI Systems. CoRR (2022)
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 (2022)
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)
Ehsan Valavi, Joel Hestness, Marco Iansiti, Newsha Ardalani, Feng Zhu, Karim R. Lakhani
Time Dependency, Data Flow, and Competitive Advantage. CoRR (2022)
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 Hazelwood
Sustainable AI: Environmental Implications, Challenges and Opportunities. CoRR (2021)
Newsha Ardalani, Urmish Thakker, Aws Albarghouthi, Karu Sankaralingam
A Static Analysis-based Cross-Architecture Performance Prediction Using Machine Learning. CoRR (2019)
Joel Hestness, Newsha Ardalani, Gregory F. Diamos
Beyond human-level accuracy: computational challenges in deep learning. PPoPP (2019)
Joel Hestness, Newsha Ardalani, Greg Diamos
Beyond Human-Level Accuracy: Computational Challenges in Deep Learning. CoRR (2019)
Tony Nowatzki, Newsha Ardalani, Karthikeyan Sankaralingam, Jian Weng
Hybrid optimization/heuristic instruction scheduling for programmable accelerator codesign. PACT (2018)
Tony Nowatzki, Vinay Gangadhar, Newsha Ardalani, Karthikeyan Sankaralingam
Stream-Dataflow Acceleration. ISCA (2017)
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 (2017)
Newsha Ardalani, Clint Lestourgeon, Karthikeyan Sankaralingam, Xiaojin Zhu
Cross-architecture performance prediction (XAPP) using CPU code to predict GPU performance. MICRO (2015)
Newsha Ardalani, Amirali Baniasadi
Write Invalidation Analysis in Chip Multiprocessors. PATMOS (2009)