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Anand Jayarajan
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Priority-based parameter propagation for distributed DNN training
A Jayarajan, J Wei, G Gibson, A Fedorova, G Pekhimenko
Proceedings of Machine Learning and Systems 19, 2019
2042019
Benchmarking and analyzing deep neural network training
H Zhu, M Akrout, B Zheng, A Pelegris, A Jayarajan, A Phanishayee, ...
2018 IEEE International Symposium on Workload Characterization (IISWC), 88-100, 2018
1542018
FPRaker: A processing element for accelerating neural network training
OM Awad, M Mahmoud, I Edo, AH Zadeh, C Bannon, A Jayarajan, ...
MICRO-54: 54th Annual IEEE/ACM International Symposium on Microarchitecture …, 2021
212021
How to validate machine learning models prior to deployment: silent trial protocol for evaluation of real-time models at ICU
S Tonekaboni, G Morgenshtern, A Assadi, A Pokhrel, X Huang, ...
Conference on Health, Inference, and Learning, 169-182, 2022
122022
LifeStream: A High-performance Stream Processing Engine for Periodic Streams
A Jayarajan, K Hau, A Goodwin, G Pekhimenko
26th ACM International Conference on Architectural Support for Programming …, 2021
9*2021
Tilt: A time-centric approach for stream query optimization and parallelization
A Jayarajan, W Zhao, Y Sun, G Pekhimenko
Proceedings of the 28th ACM International Conference on Architectural …, 2023
82023
Arbitor: A Numerically Accurate Hardware Emulation Tool for {DNN} Accelerators
C Jiang, A Jayarajan, H Lu, G Pekhimenko
2023 USENIX Annual Technical Conference (USENIX ATC 23), 519-536, 2023
12023
Needles in Needle Stacks: Meaningful Clinical Information Buried in Noisy Sensor Data
S Nagaraj, AJ Goodwin, D Lopushanskyy, SD Goodfellow, D Eytan, ...
Machine Learning for Healthcare Conference, 2024
2024
Tally: Non-Intrusive Performance Isolation for Concurrent Deep Learning Workloads
W Zhao, A Jayarajan, G Pekhimenko
arXiv preprint arXiv:2410.07381, 2024
2024
Needles in Needle Stacks: Meaningful Clinical Information Buried in Noisy Waveform Data
S Nagaraj, AJ Goodwin, D Lopushanskyy, D Eytan, RW Greer, ...
arXiv preprint arXiv:2409.00041, 2024
2024
Hardware Sensitivity Analysis for Deep Learning Models
A Jayarajan, G Pekhimenko, GA Gibson
2018
DNN Training Performance Analysis: A Divide and Conquer Approach
A Jayarajan
Training Larger Models on TensorFlow without Additional GPU
J Wei, A Qiao, A Jayarajan, G Gibson, V Vasudevan, E Xing
FOMG: Few-shOt Music Generation
A Jayarajan, HY Ling, M Suhail
TBD SUITE: BENCHMARKING AND PROFILING TOOLS FOR DNNS
XY Geoffrey, H Zhu, A Jayarajan, B Zheng, A Tiwari, G Pekhimenko
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