Anand Jayarajan

According to our database, Anand Jayarajan authored at least 8 papers between 2018 and 2023.

Collaborative distances:

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

2023

Arbitor: A Numerically Accurate Hardware Emulation Tool for DNN Accelerators.

Chenhao Jiang, Anand Jayarajan, Hao Lu, Gennady Pekhimenko

Proceedings of the 2023 USENIX Annual Technical Conference, 2023

TiLT: A Time-Centric Approach for Stream Query Optimization and Parallelization.

Anand Jayarajan, Wei Zhao, Yudi Sun, Gennady Pekhimenko

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

2022

How to validate Machine Learning Models Prior to Deployment: Silent trial protocol for evaluation of real-time models at ICU.

Sana Tonekaboni, Gabriela Morgenshtern, Azadeh Assadi, Aslesha Pokhrel, Xi Huang, Anand Jayarajan, Robert Greer, Gennady Pekhimenko, Melissa D. McCradden, Mjaye Mazwi, Anna Goldenberg

Proceedings of the Conference on Health, Inference, and Learning, 2022

2021

FPRaker: A Processing Element For Accelerating Neural Network Training.

Omar Mohamed Awad, Mostafa Mahmoud, Isak Edo, Ali Hadi Zadeh, Ciaran Bannon, Anand Jayarajan, Gennady Pekhimenko, Andreas Moshovos

Proceedings of the MICRO '21: 54th Annual IEEE/ACM International Symposium on Microarchitecture, 2021

LifeStream: a high-performance stream processing engine for periodic streams.

Anand Jayarajan, Kimberly Hau, Andrew Goodwin, Gennady Pekhimenko

Proceedings of the ASPLOS '21: 26th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, 2021

2020

LifeStream: A High-performance Stream Processing Engine for Waveform Data.

Anand Jayarajan, Kimberly Hau, Andrew Goodwin, Gennady Pekhimenko

CoRR, 2020

2019

Priority-based Parameter Propagation for Distributed DNN Training.

Anand Jayarajan, Jinliang Wei, Garth Gibson, Alexandra Fedorova, Gennady Pekhimenko

Proceedings of Machine Learning and Systems 2019, 2019

2018

Benchmarking and Analyzing Deep Neural Network Training.

Hongyu Zhu, Mohamed Akrout, Bojian Zheng, Andrew Pelegris, Anand Jayarajan, Amar Phanishayee, Bianca Schroeder, Gennady Pekhimenko

Proceedings of the 2018 IEEE International Symposium on Workload Characterization, 2018