Some of the industry's biggest players were interested in acquiring Mellanox and had submitted offers before Nvidia swooped in to make a bid over the., and had all emerged as potential buyers before the Nvidia deal was announced.
Mellanox had 2,330 full-time employees and 116 part-time employees as of the end of past year, according to a filing with the U.S. Securities and Exchange Commission.
Nvidia has come out on top in a bidding war for chipmaker Mellanox.
Nvidia is the leading bidder ahead of rivals including Intel, though no final decision has been made and the outcome could still change, the sources said.
Nvidia's advantage is that it would have a greater chance of obtaining USA and Chinese regulatory approval as Intel and Mellanox control the market for InfiniBand technology, a networking communications standard commonly used in supercomputers, Calcalist said.
Huang said Nvidia studied carefully how the deal would be reviewed by regulators and believed it wouldn't face significant hurdles because the two companies are complementary.
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"The emergence of AI (artificial intelligence) and data science, as well as billions of simultaneous computer users, is fuelling sky-rocketing demand on the world's data centres", said Nvidia Chief Executive Jensen Hung.
Nvidia gets more revenue diversification and data center sales.
Even if Nvidia doesn't explicitly repurpose Mellanox's networking technology for distributed GPU clusters of this type, it still owns another piece of the data center puzzle at a time when data center markets have been enjoying long-term robust growth and are expected to continue growing in the future as the IoT scales up and more enterprises shift to the cloud.
NVIDIA says it will use the acquisition to cement its leadership in high-performance computing (HPC).
It is expected to close by the end of 2019.
Add it up and Nvidia with Mellanox can better optimize systems. With its ownership of Mellanox, Nvidia hopes to go forward and "optimise datacenter-scale workloads across the entire computing, networking and storage stack to achieve higher performance, greater utilization and lower operating cost for customers." .