NVIDIA's (NVDA +1.23%) data center business has been one of its biggest growth drivers in recent quarters thanks to the growing application of GPUs (graphics processing units) in cloud computing applications. The chipmaker now gets almost 19% of its revenue by selling GPUs for data centers, up from 10% just a year ago as almost all the big cloud players are lining up for its chips to speed up their infrastructure and prepare for the era of artificial intelligence (AI).
In fact, NVIDIA's data center revenue shot up 175% year over year during the second quarter. More importantly, it is capable of maintaining this terrific pace of growth on the back of its recently launched Volta GPUs that are expected to enhance its lead in this space. Let's see why.
Volta will be a catalyst for the data center business
Jefferies analyst Mark Lipacis believes that NVIDIA's Volta GPUs, announced in May this year, will accelerate growth and help deliver positive earnings surprises over the next couple of years, based on their ability to power AI applications in the cloud. Lipacis also states that the chipmaker is on track to capture 80% of the profits of the AI chip market, which looks like a strong possibility given the pace at which cloud companies are lapping up its latest offering.
Image Source: NVIDIA
Amazon Web Services (AWS) recently launched its P3 cloud computing instance (an instance is a virtual server) powered by the latest Volta GPUs to target intensive applications such as autonomous vehicles, machine learning, and seismic analysis, among others. More specifically, AWS' P3 instance allows users to deploy up to eight Volta GPUs, boosting performance over the previous-generation P2 instance by as much as 14 times.
This enhanced performance will help users train artificial intelligence models in just hours instead of days, which isn't surprising as NVIDIA claims that the new Volta chips are 12 times faster than the preceding Pascal chips. The graphics specialist has managed to eke out such terrific performance from Volta with the help of tensor cores that are meant to substantially accelerate the training and inferencing of artificial intelligence algorithms and applications.
There has been a lot of interest in these new GPUs given the performance leap they deliver over the previous-generation architecture. The likes of HPE, IBM, Dell EMC, Huawei, and Lenovo have already announced that they will soon start using the Volta GPUs. Additionally, Chinese large-scale cloud computing providers Tencent, Baidu, and Alibaba have announced their commitment to NVIDIA's new chip, stating that they will upgrade from Pascal to Volta GPUs across data centers and related cloud infrastructure.
Amazon is also hopeful that AWS customers will quickly upgrade to the new P3 instance given their hunger for a more powerful virtual server. As AWS leads the cloud computing space with a 35% market share, it could boost Volta sales by rolling out the new GPU across its cloud infrastructure.
Therefore, NVIDIA's relationships with the biggest players in the cloud computing space should help Volta hit the ground running as its existing customers upgrade to the new chip. Additionally, Volta's enhanced performance will help NVIDIA make a bigger dent in high-performance computing (HPC) and machine learning servers where GPUs will be the major components.
Both these markets are set to grow at a tremendous pace. For instance, the cloud HPC market is expected to double by 2020 as per Markets and Markets, while the global machine learning market is anticipated to clock 44% annual growth through 2022, largely driven by cloud-based deployments.
What about the competition?
NVIDIA is the leader in GPUs with a 70% market share, and it is safe to say that it is the dominant supplier of GPUs to cloud companies thanks to its partnerships with the biggest names in this space. But rival Advanced Micro Devices (AMD +6.67%) is trying to steal some of its thunder in the cloud with its Radeon Instinct GPUs.
AMD is trying to strategically make its presence felt in the machine learning space through the Radeon Open Compute Platform. This is an open-source GPU computing software that's independent of the hardware deployed, which means that it can be used by systems running on NVIDIA GPUs to run various deep learning applications.
AMD's platform can deliver serious performance gains when compared to the other open source platform available on the market. It also supports major open-source machine learning frameworks including Google's TensorFlow and Facebook's Caffe. Therefore, AMD is trying to make inroads into the machine learning space by offering an open-source software first, strategically setting the stage for sales of its GPUs going forward.
In fact, AMD's chips have already started gaining traction in the cloud. In August, Baidu struck a partnership with AMD to use the latter's server GPUs and CPUs for its next-generation data centers. Then, in September, AWS announced that it has selected the chipmaker's FirePro server GPUs to power the Graphics Instance of the AppStream 2.0 service, which has traditionally been dominated by NVIDIA chips.
Evidently, AMD has started making progress in the GPU space. Though a threat, AMD cannot be considered to be a major challenger right now. NVIDIA has seized the initiative with its recent wins at Amazon, and also struck an agreement with Chinese cloud service providers (including Baidu) to supply its AI-centric GPUs.
NVIDIA is already driving more users to its platform thanks to the performance gains delivered by the Volta GPU. This is evident from the number of customers signing up to use this new chip, which should strengthen the chipmaker's position in the fast-growing server GPU accelerator market that could hit at least $4.5 billion in revenue in 2022, according to Ark Invest.
