jcjohnson / jcjohnson/cnn-benchmarks
Forward timing benchmark meaning
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- Python
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Description
Hi this is not a issue I am just not sure where to ask questions. If there is another place to put questions, please let me know. Thanks.
Does the "forward" timing in the benchmark mean the time the network takes to inference a SINGLE image (image/sec) or the time to process a batch (e.g. 16 images)? Take the AlexNet on Maxwell Titan X as an example which is 7.09ms. How can I deduce the images/sec from it? Is it 1/7.09ms=141image/sec or 1/(7.09ms/16)=2256image/sec? According to what NVIDIA announced, the specs for AlexNet on Maxwell Titan X is 450images/sec. However, neither of these two values (141 and 2256) is close which is quite confused.
[http://cdn.wccftech.com/wp-content/uploads/2016/01/NVIDIA-Drive-PX-2-Specifications.jpg](url)
Thanks and look forward to reply.
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Research direction
The issue names no file, test, or entry point; begin by locating where the benchmark reports “forward” timing. Clarify whether the value is per image or per batch, and document the conversion using the AlexNet/Maxwell Titan X example.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- machine-learning, performance
- Issue type
- Documentation
- Difficulty
- 1/5
- Estimated time
- Under an hour
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 20/100