Intel's Xeon Cascade Lake vs. NVIDIA Turing: An Analysis in AI
by Johan De Gelas on July 29, 2019 8:30 AM ESTWho Will Win the Next Enterprise Market?
At their last investors day, one of NVIDIA’s slides made it clear what the next battle in the enterprise space will be all about: data analytics. Note how an expensive dual Xeon “Skylake” Scalable is considered as baseline. That is quite a statement; reducing one of the latest Intel powered systems to a completely outperformed humble baseline.
NVIDIA’s entire business model revolves around the theory that buying expensive hardware like DGXs and Teslas is good for your TCO (“the more you buy, the more you save”). Don’t buy 5000 servers, buy 50 DGXes. Despite the fact that a DGX consumes 5 times more power, and costs $120k instead of $9k, you will be much better off. Of course, this is marketing at its best – or at its worst, depending on how you look at it. But even if the numbers are slightly exaggerated, it is a strong message: “from our deep learning stronghold to the Intel’s current growth market (Inference, HPC and machine learning), we will beat Intel by a large margin”.
Not convinced? This is how NVIDIA and IDC see the market evolving.
Currently the compute intensive or high-performance sub-market is about $37 billion out of a total $100 billion market. NVIDIA believes that this sub-market will double by 2023 and that they will be able to address $50 billion. In other words, the data analytics market – in a broad sense – will be almost half of the complete server market.
Even if this is an overestimation, it is clear that times are changing, and the stakes are very high. Neural networks are much better suited to GPUs, but if Intel can make sure that most of data pipeline runs better on CPUs and you only need a GPU for the most intensive and scalable neural networks, it will push NVIDIA back to a more niche role. On the other hand, if NVIDIA can accelerate a much larger part of the data pipeline, it will conquer markets that mostly belong to Intel and expand rapidly. And in the midst of this heated battle, IBM and AMD must make sure they get their share of the market. IBM will be offering better NVIDIA GPU based servers, and AMD will try building the right software ecosystem.
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ballsystemlord - Saturday, August 3, 2019 - link
Spelling and grammar errors:"But it will have a impact on total energy consumption, which we will discuss."
"An" not "a":
"But it will have an impact on total energy consumption, which we will discuss."
"We our newest servers into virtual clusters to make better use of all those core."
Missing "s" and missing word. I guessed "combine".
"We combine our newest servers into virtual clusters to make better use of all those cores."
"For reasons unknown to us, we could get our 2.7 GHz 8280 to perform much better than the 2.1 GHz Xeon 8176."
The 8280 is only slightly faster in the table than the 8176. It is the 8180 that is missing from the table.
"However, since my group is mostly using TensorFlow as a deep learning framework, we tend to with stick with it."
Excess "with":
"However, since my group is mostly using TensorFlow as a deep learning framework, we tend to stick with it."
"It has been observed that using a larger batch can causes significant degradation in the quality of the model,..."
Remove plural form:
"It has been observed that using a larger batch can cause significant degradation in the quality of the model,..."
"...but in many applications a loss of even a few percent is a significant."
Excess "a":
"...but in many applications a loss of even a few percent is significant."
"LSTM however come with the disadvantage that they are a lot more bandwidth intensive."
Add an "s":
"LSTMs however come with the disadvantage that they are a lot more bandwidth intensive."
"LSTMs exhibit quite inefficient memory access pattern when executed on mobile GPUs due to the redundant data movements and limited off-chip bandwidth."
"pattern" should be plural because "LSTMs" is plural, I choose an "s":
"LSTMs exhibit quite inefficient memory access patterns when executed on mobile GPUs due to the redundant data movements and limited off-chip bandwidth."
"Of course, you have the make the most of the available AVX/AVX2/AVX512 SIMD power."
"to" not "the":
"Of course, you have to make the most of the available AVX/AVX2/AVX512 SIMD power."
"Also, this another data point that proves that CNNs might be one of the best use cases for GPUs."
Missing "is":
"Also, this is another data point that proves that CNNs might be one of the best use cases for GPUs."
"From a high-level workflow perfspective,..."
A joke, or a misspelling?
"... it's not enough if the new chips have to go head-to-head with a GPU in a task the latter doesn't completely suck at."
Traditionally, AT has had no language.
"... it's not enough if the new chips have to go head-to-head with a GPU in a task the latter is good at."
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"has" not "is":
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ballsystemlord - Saturday, August 3, 2019 - link
Thanks for the cool article!tmnvnbl - Tuesday, August 6, 2019 - link
Great read, especially liked the background and perspective next to the benchmark detailsdusk007 - Tuesday, August 6, 2019 - link
Great Article.I wouldn't call Apache Arrow a database though. It is a data format more akin to a file format like csv or parquet. It is not something that stores data for you and gives it to you. It is the how to store data in memory. Like CSV or Parquet are a "how to" store data in Files. More efficient less redundancy less overhead when access from different runtimes (Tensorflow, Spark, Pandas,..).
Love the article, I hope we get more of those. Also that huge performance optimizations are possible in this field just in software. Often renting compute in the cloud is cheaper than the man hours required to optimize though.
Emrickjack - Thursday, August 8, 2019 - link
Johan's new piece in 14 months! Looking forward to your Rome reviewEmrickjack - Thursday, August 8, 2019 - link
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