Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Explicit broadcast in image normalization for better performance #6551

Merged
merged 1 commit into from
Apr 10, 2019

Conversation

haoyuz
Copy link
Member

@haoyuz haoyuz commented Apr 10, 2019

With trivial model, it improves the data input pipeline throughput from 12.5K to 15K on a DGX1 V100 machine.

With trivial model, it improves the data input pipeline throughput from 12.5K to 15K on a DGX1 V100 machine.
@haoyuz haoyuz requested a review from tfboyd April 10, 2019 01:36
@haoyuz haoyuz requested review from karmel and a team as code owners April 10, 2019 01:36
Copy link
Member

@tfboyd tfboyd left a comment

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

LTGM

@tfboyd tfboyd merged commit 6f068c7 into master Apr 10, 2019
@haoyuz haoyuz deleted the haoyuzhang-broadcast branch April 10, 2019 03:35
wlongxiang pushed a commit to wlongxiang/models that referenced this pull request Apr 24, 2019
…sorflow#6551)

With trivial model, it improves the data input pipeline throughput from 12.5K to 15K on a DGX1 V100 machine.
lgeiger added a commit to plumerai/rethinking-bnn-optimization that referenced this pull request Jun 27, 2019
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
Projects
None yet
Development

Successfully merging this pull request may close these issues.

3 participants