1 citations · 3 across the 4 of their papers we have counts for
4 papers
Regression Language Models for Code
Yash Akhauri, Xingyou Song, Arissa Wongpanich +2
We study code-to-metric regression: predicting numeric outcomes of code executions, a challenging task due to the open-ended nature of programming languages. While prior methods ha…
Performance Prediction for Large Systems via Text-to-Text Regression
Yash Akhauri, Bryan Lewandowski, Cheng-Hsi Lin +7
In many industries, predicting metric outcomes of large systems is a fundamental problem, driven largely by traditional tabular regression. However, such methods struggle on comple…
Machine Learning Fleet Efficiency: Analyzing and Optimizing Large-Scale Google TPU Systems with ML Productivity Goodput
Arissa Wongpanich, Tayo Oguntebi, Jose Baiocchi Paredes +6
Recent years have seen the emergence of machine learning (ML) workloads deployed in warehouse-scale computing (WSC) settings, also known as ML fleets. As the computational demands…
Training EfficientNets at Supercomputer Scale: 83% ImageNet Top-1 Accuracy in One Hour
Arissa Wongpanich, Hieu Pham, James Demmel +4
EfficientNets are a family of state-of-the-art image classification models based on efficiently scaled convolutional neural networks. Currently, EfficientNets can take on the order…