News for hackers. Stuff that matters.
Re:YOLOv5 on CPUs: Sparsifying to Achieve GPU-Level Performance by carbocation on Friday September 10, 2021 @04:26PM (#28486495)
Agreed - I priced this out for a specific distributed inference task a few months ago and the T4 was cheaper and faster than GPU.

On 26 million images using a pytorch model that had 41 million parameters, T4 instances were about 32% cheaper than CPU instances, and took about 45% of the time even after accounting for extra GPU startup time.

Re:YOLOv5 on CPUs: Sparsifying to Achieve GPU-Level Performance by ml_hardware on Friday September 10, 2021 @05:07PM (#28486900)
Re:YOLOv5 on CPUs: Sparsifying to Achieve GPU-Level Performance by carbocation on Saturday September 11, 2021 @08:58AM (#28491620)
Yes, I’m using “T4” as a shorthand for “instances otherwise matched to the CPU-based instances but which also have a T4 GPU.”
Re:YOLOv5 on CPUs: Sparsifying to Achieve GPU-Level Performance by mkaic on Friday September 10, 2021 @07:15PM (#28487926)
OP was most likely referring to the AWS EC2 instance type T4, which runs on Amazon Graviton processors IIRC.
Re:YOLOv5 on CPUs: Sparsifying to Achieve GPU-Level Performance by mkl on Friday September 10, 2021 @08:06PM (#28488238)
> GCP lists a T4

GCP not AWS, or are you talking about a different OP?

Re:YOLOv5 on CPUs: Sparsifying to Achieve GPU-Level Performance by 37ef_ced3 on Friday September 10, 2021 @07:04PM (#28487849)
Many businesses/services can't saturate the hardware you describe. It's just too much compute power. With CPUs you can scale down to fit your actual needs: all the way down to a single AVX-512 core doing maybe 24 inferences per second (costing a few dollars PER MONTH).

Also, your cost/inference results will change if you use a fast CPU inference engine, instead of something slow like PyTorch (which you appear to be using).

Re:YOLOv5 on CPUs: Sparsifying to Achieve GPU-Level Performance by carbocation on Saturday September 11, 2021 @09:01AM (#28491641)
Thanks - this is something I wasn’t familiar with. Do you have any pointers for CPU inference engines that you’ve had good experience with or that I can look into further?
Re:YOLOv5 on CPUs: Sparsifying to Achieve GPU-Level Performance by markurtz on Saturday September 11, 2021 @09:27AM (#28491805)
Disclosure: I work for Neural Magic.

Hi carbocation, we'd love to see what you think of the performance using the DeepSparse engine for CPU inference: https://github.com/neuralmagic/deepsparse

Take a look through our getting started pages that walk through performance benchmarking, training, and deployment for our featured models: https://sparsezoo.neuralmagic.com/getting-started