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2020 – today
- 2024
[c7]Logan Weber, Jesse Michel, Alex Renda, Michael Carbin:
Learning to Compile Programs to Neural Networks. ICML 2024- [c6]Isha Chaudhary, Alex Renda, Charith Mendis, Gagandeep Singh:
COMET: Neural Cost Model Explanation Framework. MLSys 2024 - [i10]Logan Weber, Jesse Michel, Alex Renda, Michael Carbin:
Learning to Compile Programs to Neural Networks. CoRR abs/2407.15078 (2024) - 2023
- [j1]Alex Renda
, Yi Ding, Michael Carbin:
Turaco: Complexity-Guided Data Sampling for Training Neural Surrogates of Programs. Proc. ACM Program. Lang. 7(OOPSLA2): 1648-1676 (2023) - [i9]Isha Chaudhary, Alex Renda, Charith Mendis, Gagandeep Singh:
CoMEt: x86 Cost Model Explanation Framework. CoRR abs/2302.06836 (2023) - [i8]Alex Renda, Yi Ding, Michael Carbin:
Turaco: Complexity-Guided Data Sampling for Training Neural Surrogates of Programs. CoRR abs/2309.11726 (2023) - 2022
- [i7]Yi Ding, Alex Renda, Ahsan Pervaiz, Michael Carbin, Henry Hoffmann:
Cello: Efficient Computer Systems Optimization with Predictive Early Termination and Censored Regression. CoRR abs/2204.04831 (2022) - [i6]Zachary Ankner, Alex Renda, Gintare Karolina Dziugaite, Jonathan Frankle, Tian Jin:
The Effect of Data Dimensionality on Neural Network Prunability. CoRR abs/2212.00291 (2022) - 2021
- [c5]Alex Renda, Yi Ding, Michael Carbin:
Programming with neural surrogates of programs. Onward! 2021: 18-38 - [i5]Alex Renda, Yi Ding, Michael Carbin:
Programming with Neural Surrogates of Programs. CoRR abs/2112.06148 (2021) - 2020
- [c4]Alex Renda, Jonathan Frankle, Michael Carbin:
Comparing Rewinding and Fine-tuning in Neural Network Pruning. ICLR 2020 - [c3]Alex Renda, Yishen Chen, Charith Mendis, Michael Carbin:
DiffTune: Optimizing CPU Simulator Parameters with Learned Differentiable Surrogates. MICRO 2020: 442-455 - [i4]Alex Renda, Jonathan Frankle, Michael Carbin:
Comparing Rewinding and Fine-tuning in Neural Network Pruning. CoRR abs/2003.02389 (2020) - [i3]Riyadh Baghdadi, Abdelkader Nadir Debbagh, Kamel Abdous, Fatima-Zohra Benhamida, Alex Renda, Jonathan Elliott Frankle, Michael Carbin, Saman P. Amarasinghe:
TIRAMISU: A Polyhedral Compiler for Dense and Sparse Deep Learning. CoRR abs/2005.04091 (2020) - [i2]Alex Renda, Yishen Chen, Charith Mendis, Michael Carbin:
DiffTune: Optimizing CPU Simulator Parameters with Learned Differentiable Surrogates. CoRR abs/2010.04017 (2020)
2010 – 2019
- 2019
- [c2]Charith Mendis, Alex Renda, Saman P. Amarasinghe, Michael Carbin:
Ithemal: Accurate, Portable and Fast Basic Block Throughput Estimation using Deep Neural Networks. ICML 2019: 4505-4515 - [c1]Yishen Chen, Ajay Brahmakshatriya, Charith Mendis, Alex Renda, Eric Atkinson, Ondrej Sýkora, Saman P. Amarasinghe, Michael Carbin:
BHive: A Benchmark Suite and Measurement Framework for Validating x86-64 Basic Block Performance Models. IISWC 2019: 167-177 - 2017
- [i1]Alex Renda, Harrison Goldstein, Sarah Bird, Chris Quirk, Adrian Sampson:
Abstractions for AI-Based User Interfaces and Systems. CoRR abs/1709.04991 (2017)
Coauthor Index
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