"To top it off the new Intel Knights Landing Processor for the data center has Omni-Path architecture embedded. Nightmare scenario for MLNX. INTC going for complete domination of the space."
(Really ?)
Can Intel's New Knights Landing Chip Compete With NVIDIA For Deep Learning?
POST WRITTEN BY Karl Freund; Jun 28, 2016
( Karl Freund is a Moor Insights & Strategy analyst for machine learning & HPC)
Intel INTC -1.16% finally launched the highly anticipated “Knights Landing” (KNL) version of their Many Integrated Core (MIC) Xeon Phi processor at this years’ international supercomputing event (now called ISC High Performance), targeting High Performance Computing (HPC) and the white-hot market for training Deep Neural Networks (DNNs). DNNs are used to power everything from the ads you see on Google GOOGL -0.65% to autonomous cars to natural language processing to image recognition. The announcement started a bit of a food fight: Intel claims that they can beat NVIDIA NVDA -0.31% in Deep Learning by over 2x, to which NVIDIA responded that, no, actually their new accelerators beat Intel by, you guessed it, by over 2x.
Practically every tech company has staked a claim in Deep Learning as The Next Big Thing, so Intel is now spending a great deal of energy trying to join the party, so I don’t expect this to be all the ammunition they can muster. AI applications have helped boost the market for NVIDIA’s Tesla products, helping NVIDIA grow their Datacenter business by 63% to $142M in their latest quarter. Intel is now offering an attractive approach to this market, providing GPU-class performance on a host CPU that is compatible with the massive base of Xeon applications, potentially simplifying programming and reducing costly data movement. However, given the momentum NVIDIA has built for their GPUs, buyers will need time to validate Intel’s performance claims on their own compute-intensive workloads, especially in Deep Learning applications where NVIDIA dominates. |
