Correcting Intel's Deep Learning Benchmark Mistakes
blogs.nvidia.com
Correcting Intel's Deep Learning Benchmark Mistakes
1–10 of 40 posts
Re: Correcting Intel's Deep Learning Benchmark Mistakes
#2Well that was a pretty concise explanation of mistakes. Benchmarking is indeed difficult to get right.
Re: Correcting Intel's Deep Learning Benchmark Mistakes
#3Shots fired, wow Nvidia is pissed that Intel is trying to edge into the market with their Phi series.
Re: Correcting Intel's Deep Learning Benchmark Mistakes
#4`each with one or two sockets of less-capable processors, like Xeon Phi.`
Corporate smacktalk...
Re: Correcting Intel's Deep Learning Benchmark Mistakes
#5> Titan uses four-year-old GPUs
... as does nearly every public cloud provider. I agree with most of the article, but you can't fault Intel for benchmarking the hardware that cloud providers are actually offering.
I'm not sure what exactly NVIDIA is doing with their Tesla product line but whatever it is, it's really restricting the availability of recent GPU hardware. Even Azure's GPU instances released this month are using the Kepler architecture from 2012. It's fully two generations out of date now, and that's sad.
Re: Correcting Intel's Deep Learning Benchmark Mistakes
#6Ok, its officially the new new thing when corporate communications types are sniping at each other :-)
Once we start seeing press releases of products that are not available yet being shown to kill the existing competition we'll know that the hype train has officially gone super-product-sonic (that is a hype wave travelling faster than the product releases can support it).
Re: Correcting Intel's Deep Learning Benchmark Mistakes
#7Why don't they provide a link to their testing methodology? They need to back up their claims (on both sides) with the actual configuration, all versions, and sample datasets for people to independently verify.
A docker container that runs their performance suite would be ideal.
Re: Correcting Intel's Deep Learning Benchmark Mistakes
#8> Titan uses four-year-old GPUs ... as does nearly every public cloud provider. I agree with most of the article, but you can't fault Intel for benchmarking the hardware that cloud providers are actually offering. I'm not sure what exactly NVIDIA is doing with their Tesla product line but whatever it is, it's really restricting the availability of recent GPU hardware. Even Azure's GPU instances released this month ar…
I mean Intel is comparing their publicly unavailable product against NVIDIA's publicly available product. Now NVIDIA is replying with the benchmarks on their (as of yet) publicly unavailable product.
I think this blog post is fair game.
Re: Correcting Intel's Deep Learning Benchmark Mistakes
#9Ok, its officially the new new thing when corporate communications types are sniping at each other :-) Once we start seeing press releases of products that are not available yet being shown to kill the existing competition we'll know that the hype train has officially gone super-product-sonic (that is a hype wave travelling faster than the product releases can support it).
Did you see the Opera vs Edge sniping a month or two ago? I suppose Opera is probably lot less corporate than Intel & Nvidia, of course...
Re: Correcting Intel's Deep Learning Benchmark Mistakes
#10@imaleppert Agree getting the details on the testing would be helpful. I think NV was more pointing out that Intel were putting their latest against NV's oldest. It'd be like testing a RX480 against a GTX660. What's the use of that?
@modeless the new Azure instances have M60's or you can purchase a 1080 or new TitanX which are both available (although stock has been tight).
https://azure.microsoft.com/en-us/blog/azure-n-series-previe...