6 ms·
Disclosure: I work on Google Cloud. I want to highlight this paragraph from the post: > Here at Google Cloud, we want to provide customers with the best cloud
by boulos 9y ago
Disclosure: I work on Google Cloud.
I want to highlight this paragraph from the post:
> Here at Google Cloud, we want to provide customers with the best cloud for every ML workload and will offer a variety of high-performance CPUs (including Intel Skylake) and GPUs (including NVIDIA’s Tesla V100) alongside Cloud TPUs.
We fundamentally want Google Cloud to be the best place to do computing. That includes AI/ML and so you’ll see us both invest in our own hardware, as well as provide the latest CPUs, GPUs, and so on. Don’t take this announcement as “Google is going to start excluding GPUs”, but rather that we’re adding an option that we’ve found internally to be an excellent balance of time-to-trained-model and cost. We’re still happily buying GPUs to offer to our Cloud customers, and as I said elsewhere the V100 is a great chip. All of this competition in hardware is great for folks who want to see ML progress in the years to come.
- riku_iki 9y ago> high-performance CPUs (including Intel Skylake) Any plans for ryzen?
- boulos 9y agoWe’re always exploring the best hardware for the dollar. We’re a founding member of OpenPOWER and to your question about AMD parts, we’ve previously (publicly) run Opterons when they were the best choice. At this time, we don’t have any announcements to make :). But I’d like to note that even if we were to use parts internally at Google (or not!), that for Cloud what matters is market demand. If there really was enormous customer demand for say ARM64, then we would look into it, even if the rest of Google wasn’t interested.
- singularity2001 9y agohow much did NVIDIA pay your boss to make that statement?
- sabalaba 9y agoAny plans to support AMD GPUs and the Radeon Open Compute project? The AI/ML community really needs viable alternatives to NVIDIA, otherwise they will continue to flex pricing power. Google, via TensorFlow, is in a phenomenal position to promote open source alternatives to the proprietary Deep Learning software ecosystem that we see today with CUDA/CuDNN.
- londons_explore 9y agoGoogle would happily accept patches to enable support for it. AMD hopefully has a team writing such patches now. It makes business sense for them to do so. Google is getting even more price gouging from Nvidia than the general public, and has even more incentive to level the playing field.
- socceroos 9y agoOr the opposite - they're getting nice savings in return for not actively developing or encouraging CUDA/cuDNN alternatives.
- oneshot908 9y agoDid you guys ever reveal the internal math model of TPU 2? We know V100 is FP16/FP32 on their tensor cores, when will you follow suit? Edit: sort of, from https://www.theregister.co.uk/2017/12/14/google_tpu2_specs_ish/ https://www.theregister.co.uk/2017/12/14/google_tpu2_specs_i... "32-bit floating-point precision math units for scalars and vectors, and 32-bit floating-point-precision matrix multiplication units with reduced precision for multipliers." So what does "reduced" mean exactly?
- boulos 9y agoWe still don’t document it exactly, but [1] shows that bfloat16 is supported on lots of ops. [1] https://cloud.google.com/tpu/docs/tensorflow-ops https://cloud.google.com/tpu/docs/tensorflow-ops
- londons_explore 9y agoIt is documented here: https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/framework/bfloat16.h https://github.com/tensorflow/tensorflow/blob/master/tensorf...
- boulos 9y agoThat doesn’t prove that the chip operates at 16 bits. For example, we could do 18-bit multipliers (or anything >= 16) and still use 16-bit floats.
- oneshot908 9y agoATI demonstrated FP24 was frickin' awesome over a decade and a half ago. it wouldn't surprise me in the least if you went somewhere like that, but it perplexes me as to why you think that's secret sauce in any way long after ATI nearly destroyed NVIDIA with FP24 back in the early days of DirectX 9 and NV3x.
- londons_explore 9y ago
- trevyn 9y ago>We fundamentally want Google Cloud to be the best place to do computing. Lower. Network. Egress. Pricing. By. Two. Orders. Of. Magnitude. Market rate is close to $1 per TB outbound. Your rate is $80-$120 per TB. That's just embarrassing.