Newsha Ardalani

According to our database, Newsha Ardalani authored at least 22 papers between 2009 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

DeepFlow: A Cross-Stack Pathfinding Framework for Distributed AI Systems.

Newsha Ardalani, Saptadeep Pal, Puneet Gupta

ACM Trans. Design Autom. Electr. Syst., March, 2024

Text Quality-Based Pruning for Efficient Training of Language Models.

Vasu Sharma, Karthik Padthe, Newsha Ardalani, Kushal Tirumala, Russell Howes, Hu Xu, Po-Yao Huang, Shang-Wen Li, Armen Aghajanyan, Gargi Ghosh, Luke Zettlemoyer

CoRR, 2024

MAD-Max Beyond Single-Node: Enabling Large Machine Learning Model Acceleration on Distributed Systems.

Samuel Hsia, Alicia Golden, Bilge Acun, Newsha Ardalani, Zachary DeVito, Gu-Yeon Wei, David Brooks, Carole-Jean Wu

Proceedings of the 51st ACM/IEEE Annual International Symposium on Computer Architecture, 2024

Sieve: Multimodal Dataset Pruning Using Image Captioning Models.

Anas Mahmoud, Mostafa Elhoushi, Amro Abbas, Yu Yang, Newsha Ardalani, Hugh Leather, Ari S. Morcos

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

2023

Decoding Data Quality via Synthetic Corruptions: Embedding-guided Pruning of Code Data.

Yu Yang, Aaditya K. Singh, Mostafa Elhoushi, Anas Mahmoud, Kushal Tirumala, Fabian Gloeckle, Baptiste Rozière, Carole-Jean Wu, Ari S. Morcos, Newsha Ardalani

CoRR, 2023

Data Acquisition: A New Frontier in Data-centric AI.

Lingjiao Chen, Bilge Acun, Newsha Ardalani, Yifan Sun, Feiyang Kang, Hanrui Lyu, Yongchan Kwon, Ruoxi Jia, Carole-Jean Wu, Matei Zaharia, James Zou

CoRR, 2023

Towards MoE Deployment: Mitigating Inefficiencies in Mixture-of-Expert (MoE) Inference.

Haiyang Huang, Newsha Ardalani, Anna Y. Sun, Liu Ke, Hsien-Hsin S. Lee, Anjali Sridhar, Shruti Bhosale, Carole-Jean Wu, Benjamin Lee

CoRR, 2023

DataPerf: Benchmarks for Data-Centric AI Development.

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

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

MP-Rec: Hardware-Software Co-design to Enable Multi-path Recommendation.

Samuel Hsia, Udit Gupta, Bilge Acun, Newsha Ardalani, Pan Zhong, Gu-Yeon Wei, David Brooks, Carole-Jean Wu

Proceedings of the 28th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, 2023

2022

Understanding Scaling Laws for Recommendation Models.

Newsha Ardalani, Carole-Jean Wu, Zeliang Chen, Bhargav Bhushanam, Adnan Aziz

CoRR, 2022

DataPerf: Benchmarks for Data-Centric AI Development.

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

CoRR, 2022

Time Dependency, Data Flow, and Competitive Advantage.

Ehsan Valavi, Joel Hestness, Marco Iansiti, Newsha Ardalani, Feng Zhu, Karim R. Lakhani

CoRR, 2022

Time and the Value of Data.

Ehsan Valavi, Joel Hestness, Newsha Ardalani, Marco Iansiti

CoRR, 2022

Sustainable AI: Environmental Implications, Challenges and Opportunities.

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

Proceedings of the Fifth Conference on Machine Learning and Systems, 2022

2021

Sustainable AI: Environmental Implications, Challenges and Opportunities.

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

CoRR, 2021

2019

A Static Analysis-based Cross-Architecture Performance Prediction Using Machine Learning.

Newsha Ardalani, Urmish Thakker, Aws Albarghouthi, Karu Sankaralingam

CoRR, 2019

Beyond human-level accuracy: computational challenges in deep learning.

Joel Hestness, Newsha Ardalani, Gregory F. Diamos

Proceedings of the 24th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, 2019

2018

Hybrid optimization/heuristic instruction scheduling for programmable accelerator codesign.

Tony Nowatzki, Newsha Ardalani, Karthikeyan Sankaralingam, Jian Weng

Proceedings of the 27th International Conference on Parallel Architectures and Compilation Techniques, 2018

2017

Deep Learning Scaling is Predictable, Empirically.

Joel Hestness, Sharan Narang, Newsha Ardalani, Gregory F. Diamos, Heewoo Jun, Hassan Kianinejad, Md. Mostofa Ali Patwary, Yang Yang, Yanqi Zhou

CoRR, 2017

Stream-Dataflow Acceleration.

Tony Nowatzki, Vinay Gangadhar, Newsha Ardalani, Karthikeyan Sankaralingam

Proceedings of the 44th Annual International Symposium on Computer Architecture, 2017

2015

Cross-architecture performance prediction (XAPP) using CPU code to predict GPU performance.

Newsha Ardalani, Clint Lestourgeon, Karthikeyan Sankaralingam, Xiaojin Zhu

Proceedings of the 48th International Symposium on Microarchitecture, 2015

2009

Write Invalidation Analysis in Chip Multiprocessors.

Newsha Ardalani, Amirali Baniasadi

Proceedings of the Integrated Circuit and System Design. Power and Timing Modeling, 2009