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09/21/2023
Turaco: Complexity-Guided Data Sampling for Training Neural Surrogates of Programs
Programmers and researchers are increasingly developing surrogates of pr...
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02/14/2023
COMET: X86 Cost Model Explanation Framework
ML-based program cost models have been shown to yield fairly accurate pr...
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12/01/2022
The Effect of Data Dimensionality on Neural Network Prunability
Practitioners prune neural networks for efficiency gains and generalizat...
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04/11/2022
Cello: Efficient Computer Systems Optimization with Predictive Early Termination and Censored Regression
Sample-efficient machine learning (SEML) has been widely applied to find...
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12/12/2021
Programming with Neural Surrogates of Programs
Surrogates, models that mimic the behavior of programs, form the basis o...
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10/08/2020
DiffTune: Optimizing CPU Simulator Parameters with Learned Differentiable Surrogates
CPU simulators are useful tools for modeling CPU execution behavior. How...
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05/07/2020
TIRAMISU: A Polyhedral Compiler for Dense and Sparse Deep Learning
In this paper, we demonstrate a compiler that can optimize sparse and re...
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03/05/2020
Comparing Rewinding and Fine-tuning in Neural Network Pruning
Many neural network pruning algorithms proceed in three steps: train the...
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09/14/2017
