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Home / Proceedings / Proceedings of the AAAI Conference on Artificial Intelligence

Inefficiency of K-FAC for Large Batch Size Training

February 1, 2023

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Authors

Linjian Ma

University of California at Berkeley


Gabe Montague

University of California at Berkeley


Jiayu Ye

University of California at Berkeley


Zhewei Yao

University of California at Berkeley


Amir Gholami

University of California at Berkeley


Kurt Keutzer

University of California at Berkeley


Michael Mahoney

University of California at Berkeley


DOI:

10.1609/aaai.v34i04.5946


Abstract:

There have been several recent work claiming record times for ImageNet training. This is achieved by using large batch sizes during training to leverage parallel resources to produce faster wall-clock training times per training epoch. However, often these solutions require massive hyper-parameter tuning, which is an important cost that is often ignored. In this work, we perform an extensive analysis of large batch size training for two popular methods that is Stochastic Gradient Descent (SGD) as well as Kronecker-Factored Approximate Curvature (K-FAC) method. We evaluate the performance of these methods in terms of both wall-clock time and aggregate computational cost, and study the hyper-parameter sensitivity by performing more than 512 experiments per batch size for each of these methods. We perform experiments on multiple different models on two datasets of CIFAR-10 and SVHN. The results show that beyond a critical batch size both K-FAC and SGD significantly deviate from ideal strong scaling behaviour, and that despite common belief K-FAC does not exhibit improved large-batch scalability behavior, as compared to SGD.

Topics: AAAI

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HOW TO CITE:

Linjian Ma||Gabe Montague||Jiayu Ye||Zhewei Yao||Amir Gholami||Kurt Keutzer||Michael Mahoney Inefficiency of K-FAC for Large Batch Size Training Proceedings of the AAAI Conference on Artificial Intelligence (2020) 5053-5060.

Linjian Ma||Gabe Montague||Jiayu Ye||Zhewei Yao||Amir Gholami||Kurt Keutzer||Michael Mahoney Inefficiency of K-FAC for Large Batch Size Training AAAI 2020, 5053-5060.

Linjian Ma||Gabe Montague||Jiayu Ye||Zhewei Yao||Amir Gholami||Kurt Keutzer||Michael Mahoney (2020). Inefficiency of K-FAC for Large Batch Size Training. Proceedings of the AAAI Conference on Artificial Intelligence, 5053-5060.

Linjian Ma||Gabe Montague||Jiayu Ye||Zhewei Yao||Amir Gholami||Kurt Keutzer||Michael Mahoney. Inefficiency of K-FAC for Large Batch Size Training. Proceedings of the AAAI Conference on Artificial Intelligence 2020 p.5053-5060.

Linjian Ma||Gabe Montague||Jiayu Ye||Zhewei Yao||Amir Gholami||Kurt Keutzer||Michael Mahoney. 2020. Inefficiency of K-FAC for Large Batch Size Training. "Proceedings of the AAAI Conference on Artificial Intelligence". 5053-5060.

Linjian Ma||Gabe Montague||Jiayu Ye||Zhewei Yao||Amir Gholami||Kurt Keutzer||Michael Mahoney. (2020) "Inefficiency of K-FAC for Large Batch Size Training", Proceedings of the AAAI Conference on Artificial Intelligence, p.5053-5060

Linjian Ma||Gabe Montague||Jiayu Ye||Zhewei Yao||Amir Gholami||Kurt Keutzer||Michael Mahoney, "Inefficiency of K-FAC for Large Batch Size Training", AAAI, p.5053-5060, 2020.

Linjian Ma||Gabe Montague||Jiayu Ye||Zhewei Yao||Amir Gholami||Kurt Keutzer||Michael Mahoney. "Inefficiency of K-FAC for Large Batch Size Training". Proceedings of the AAAI Conference on Artificial Intelligence, 2020, p.5053-5060.

Linjian Ma||Gabe Montague||Jiayu Ye||Zhewei Yao||Amir Gholami||Kurt Keutzer||Michael Mahoney. "Inefficiency of K-FAC for Large Batch Size Training". Proceedings of the AAAI Conference on Artificial Intelligence, (2020): 5053-5060.

Linjian Ma||Gabe Montague||Jiayu Ye||Zhewei Yao||Amir Gholami||Kurt Keutzer||Michael Mahoney. Inefficiency of K-FAC for Large Batch Size Training. AAAI[Internet]. 2020[cited 2023]; 5053-5060.


ISSN: 2374-3468


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