What Is NVLink? | NVIDIA Blogs

What Is NVLink? | NVIDIA Blogs
What Is NVLink? | NVIDIA Blogs

Accelerated computing —  a functionality as soon as confined to high-performance computer systems in authorities analysis labs — has gone mainstream.

Banks, automobile makers, factories, hospitals, retailers and others are adopting AI supercomputers to deal with the rising mountains of information they should course of and perceive.

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These highly effective, environment friendly techniques are superhighways of computing. They carry information and calculations over parallel paths on a lightning journey to actionable outcomes.

GPU and CPU processors are the assets alongside the best way, and their onramps are quick interconnects. The gold normal in interconnects for accelerated computing is NVLink.

So, What Is NVLink?

NVLink is a high-speed connection for GPUs and CPUs shaped by a sturdy software program protocol, usually driving on a number of pairs of wires printed on a pc board. It lets processors ship and obtain information from shared swimming pools of reminiscence at lightning pace.

A diagram showing two NVLink uses

Now in its fourth technology, NVLink connects host and accelerated processors at charges as much as 900 gigabytes per second (GB/s).

That’s greater than 7x the bandwidth of PCIe Gen 5, the interconnect utilized in typical x86 servers. And NVLink sports activities 5x the power effectivity of PCIe Gen 5, due to information transfers that eat simply 1.3 picojoules per bit.

The Historical past of NVLink

First launched as a GPU interconnect with the NVIDIA P100 GPU, NVLink has superior in lockstep with every new NVIDIA GPU structure.

A chart of the basic specifications for NVLink

In 2018, NVLink hit the highlight in excessive efficiency computing when it debuted connecting GPUs and CPUs in two of the world’s strongest supercomputers, Summit and Sierra.

The techniques, put in at Oak Ridge and Lawrence Livermore Nationwide Laboratories, are pushing the boundaries of science in fields equivalent to drug discovery, pure catastrophe prediction and extra.

Bandwidth Doubles, Then Grows Once more

In 2020, the third-generation NVLink doubled its max bandwidth per GPU to 600GB/s, packing a dozen interconnects in each NVIDIA A100 Tensor Core GPU.

The A100 powers AI supercomputers in enterprise information facilities, cloud computing companies and HPC labs throughout the globe.

In the present day, 18 fourth-generation NVLink interconnects are embedded in a single NVIDIA H100 Tensor Core GPU. And the expertise has taken on a brand new, strategic function that can allow essentially the most superior CPUs and accelerators on the planet.

A Chip-to-Chip Hyperlink

NVIDIA NVLink-C2C is a model of the board-level interconnect to hitch two processors inside a single package deal, making a superchip. For instance, it connects two CPU chips to ship 144 Arm Neoverse V2 cores within the NVIDIA Grace CPU Superchip, a processor constructed to ship energy-efficient efficiency for cloud, enterprise and HPC customers.

NVIDIA NVLink-C2C additionally joins a Grace CPU and a Hopper GPU to create the Grace Hopper Superchip. It packs accelerated computing for the world’s hardest HPC and AI jobs right into a single chip.

Alps, an AI supercomputer deliberate for the Swiss Nationwide Computing Middle, shall be among the many first to make use of Grace Hopper. When it comes on-line later this 12 months, the high-performance system will work on massive science issues in fields from astrophysics to quantum chemistry.

The Grace CPU uses NVLink-C2C
The Grace CPU packs 144 Arm Neoverse V2 cores throughout two die linked by NVLink-C2C.

Grace and Grace Hopper are additionally nice for bringing power effectivity to demanding cloud computing workloads.

For instance, Grace Hopper is a perfect processor for recommender techniques. These financial engines of the web want quick, environment friendly entry to plenty of information to serve trillions of outcomes to billions of customers each day.

A chart showing how Grace Hopper uses NVLink to deliver leading performance on recommendation systems
Recommenders rise up to 4x extra efficiency and higher effectivity utilizing Grace Hopper than utilizing Hopper with conventional CPUs.

As well as, NVLink is utilized in a strong system-on-chip for automakers that features NVIDIA Hopper, Grace and Ada Lovelace processors. NVIDIA DRIVE Thor is a automobile laptop that unifies clever capabilities equivalent to digital instrument cluster, infotainment, automated driving, parking and extra right into a single structure.

LEGO Hyperlinks of Computing

NVLink additionally acts just like the socket stamped right into a LEGO piece. It’s the premise for constructing supersystems to deal with the largest HPC and AI jobs.

For instance, NVLinks on all eight GPUs in an NVIDIA DGX system share quick, direct connections by way of NVSwitch chips. Collectively, they allow an NVLink community the place each GPU within the server is a part of a single system.

To get much more efficiency, DGX techniques can themselves be stacked into modular items of 32 servers, creating a strong, environment friendly computing cluster.

A picture of the DGX family of server products that use NVLink
NVLink is among the key applied sciences that permit customers simply scale modular NVIDIA DGX techniques to a SuperPOD with as much as an exaflop of AI efficiency.

Customers can join a modular block of 32 DGX techniques right into a single AI supercomputer utilizing a mix of an NVLink community contained in the DGX and NVIDIA Quantum-2 switched Infiniband cloth between them. For instance, an NVIDIA DGX H100 SuperPOD packs 256 H100 GPUs to ship as much as an exaflop of peak AI efficiency.

To get much more efficiency, customers can faucet into the AI supercomputers within the cloud such because the one Microsoft Azure is constructing with tens of 1000’s of A100 and H100 GPUs. It’s a service utilized by teams like OpenAI to coach among the world’s largest generative AI fashions.

And it’s yet one more instance of the ability of accelerated computing.


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