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Morningstar | Nvidia Sends Shot Across Intel's Bow With $6.9 Billion Acquisition of Mellanox

On March 11, Nvidia announced it will acquire Israel-based Mellanox Technologies for $6.9 billion, or $125 per share in cash. Mellanox sells networking products that focus on efficient data transfer in data centers via its InfiniBand and Ethernet technologies for interconnects. Over the past year or so, Xilinx, Microsoft, and Intel have all been linked to acquiring Mellanox, particularly as data transfer is a growing bottleneck. Nvidia’s DGX integrated system for artificial intelligence uses InfiniBand technology, while Nvidia and Mellanox collectively power over half of the world’s TOP500 supercomputers with their graphics processing units and interconnects, respectively. The deal price represents a 14% premium to Mellanox's March 8 share price. However, Intel’s reported bid of $5.5 billion-$6.0 billion implied a 30% premium to the midpoint of where shares were previously trading, which implies Nvidia is paying a 56% premium. We are maintaining our $120 fair value estimate for narrow-moat Nvidia and continue to see a better margin of safety in wide-moat Intel.

During a call discussing the acquisition, Nvidia CFO Collette Kress said she expects the deal to close by the end of 2019. We don’t foresee any regulatory hurdles, given the complementary nature of the companies' portfolios (barring any U.S.-China-related scrutiny). At the end of its fiscal 2019, Nvidia held $7.42 billion in cash and equivalents on its balance sheet, which makes this deal fairly digestible. Kress also said there will be no initial revenue or cost synergies as the GPU titan intends to maintain all of Mellanox’s existing investments. We think this makes sense, as the deal rationale is initially to bolster Nvidia’s share of data center spending to potentially increase its switching costs. Also on the call, Nvidia CEO Jensen Huang said he anticipates Nvidia evolving "from a chip-level company to a server-level company to essentially a data center-scale company."

Mellanox’s InfiniBand interconnect products are tailored more to high-performance computing applications whereas its Ethernet offerings are focused in cloud and enterprise data centers. For 2018, Mellanox delivered 26% revenue growth and crossed the $1 billion mark for the first time ($1.09 billion for the year). By segment, Ethernet sales grew 54% year over year, with Mellanox boasting 69% share in the merchant Ethernet adapter market (other players are Intel and Marvell), while InfiniBand sales grew 8% in 2018. We think Mellanox’s forward revenue growth rate will be consistent with our expectations for Nvidia’s data center growth (31% five-year compound annual growth rate through fiscal 2024). By 2023, Nvidia anticipates a total addressable market of $50 billion for computing and $11 billion for high-speed networking with the inclusion of Mellanox. Although we expect intense competition for this TAM, Intel has its own Omni-Path interconnect solutions, with its reported and subsequently failed bid for Mellanox probably implying that its technology may be subpar.

Longer term, we do expect revenue synergies stemming from future variants of Mellanox’s Socket Direct technology, which that enables GPUs to directly send and receive data from the network without any CPU intervention (a key bottleneck today). Nevertheless, while this acquisition is likely to strengthen Nvidia’s hold on the AI training market, we still expect the AI inference market to be quite fragmented among CPUs, GPUs, FPGAs, and custom ASICs. While GPUs work well for inference workloads with large batches of data, we anticipate most of these workloads will feature smaller batches of data, which have unique requirements beyond raw processing power and thus unique chip solutions beyond GPUs. In fact, Socket Direct technology can also be used to bolster CPU performance. Today’s servers predominantly feature dual-socket CPU boards, with data traffic needing to pass through one CPU to reach the second. Mellanox’s Socket Direct technology enables each CPU to directly send and receive data from the network to drive data throughput.

For more on our thoughts on the AI chip opportunity, please see our August 2017 Technology Observer, "Accelerator: Rise of the Machine (and Deep) Learning Phenomenon."