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NVIDIA at this time unveiled at SC23 the subsequent wave of applied sciences that can elevate scientific and industrial analysis facilities worldwide to new ranges of efficiency and vitality effectivity.
“NVIDIA {hardware} and software program improvements are creating a brand new class of AI supercomputers,” stated Ian Buck, vice chairman of the corporate’s excessive efficiency computing and hyperscale information middle enterprise, in a particular handle on the convention.
Among the programs will pack memory-enhanced NVIDIA Hopper accelerators, others a brand new NVIDIA Grace Hopper systems architecture. All will use the expanded parallelism to run a full stack of accelerated software program for generative AI, HPC and hybrid quantum computing.
Buck described the brand new NVIDIA HGX H200 as “the world’s main AI computing platform.”
![Image of H200 GPU system](https://blogs.nvidia.com/wp-content/uploads/2023/11/H200-image-672x411.jpg)
It packs as much as 141GB of HBM3e, the primary AI accelerator to make use of the ultrafast expertise. Operating fashions like GPT-3, NVIDIA H200 Tensor Core GPUs present an 18x efficiency enhance over prior-generation accelerators.
Amongst different generative AI benchmarks, they zip via 12,000 tokens per second on a Llama2-13B giant language mannequin (LLM).
Buck additionally revealed a server platform that hyperlinks 4 NVIDIA GH200 Grace Hopper Superchips on an NVIDIA NVLink interconnect. The quad configuration places in a single compute node a whopping 288 Arm Neoverse cores and 16 petaflops of AI efficiency with as much as 2.3 terabytes of high-speed reminiscence.
![Image of quad GH200 server node](https://blogs.nvidia.com/wp-content/uploads/2023/11/Quad-Grace-Hopper-node-configuration-672x405.jpg)
Demonstrating its effectivity, one GH200 Superchip utilizing the NVIDIA TensorRT-LLM open-source library is 100x quicker than a dual-socket x86 CPU system and almost 2x extra vitality environment friendly than an X86 + H100 GPU server.
“Accelerated computing is sustainable computing,” Buck stated. “By harnessing the ability of accelerated computing and generative AI, collectively we are able to drive innovation throughout industries whereas decreasing our impression on the atmosphere.”
NVIDIA Powers 38 of 49 New TOP500 Methods
The most recent TOP500 listing of the world’s quickest supercomputers displays the shift towards accelerated, energy-efficient supercomputing.
Due to new programs powered by NVIDIA H100 Tensor Core GPUs, NVIDIA now delivers greater than 2.5 exaflops of HPC efficiency throughout these world-leading programs, up from 1.6 exaflops within the Could rankings. NVIDIA’s contribution on the highest 10 alone reaches almost an exaflop of HPC and 72 exaflops of AI efficiency.
The brand new listing comprises the very best variety of programs ever utilizing NVIDIA applied sciences, 379 vs. 372 in Could, together with 38 of 49 new supercomputers on the listing.
Microsoft Azure leads the newcomers with its Eagle system utilizing H100 GPUs in NDv5 cases to hit No. 3 with 561 petaflops. Mare Nostrum5 in Barcelona ranked No. 8, and NVIDIA Eos — which lately set new AI training records on the MLPerf benchmarks — got here in at No. 9.
Exhibiting their vitality effectivity, NVIDIA GPUs energy 23 of the highest 30 programs on the Green500. They usually retained the No. 1 spot with the H100 GPU-based Henri system, which delivers 65.09 gigaflops per watt for the Flatiron Institute in New York.
Gen AI Explores COVID
Exhibiting what’s potential, the Argonne Nationwide Laboratory used NVIDIA BioNeMo, a generative AI platform for biomolecular LLMs, to develop GenSLMs, a mannequin that may generate gene sequences that carefully resemble real-world variants of the coronavirus. Utilizing NVIDIA GPUs and information from 1.5 million COVID genome sequences, it could additionally quickly determine new virus variants.
The work won the Gordon Bell special prize final 12 months and was skilled on supercomputers, together with Argonne’s Polaris system, the U.S. Division of Vitality’s Perlmutter and NVIDIA’s Selene.
It’s “simply the tip of the iceberg — the longer term is brimming with prospects, as generative AI continues to redefine the panorama of scientific exploration,” stated Kimberly Powell, vice chairman of healthcare at NVIDIA, within the particular handle.
Saving Time, Cash and Vitality
Utilizing the most recent applied sciences, accelerated workloads can see an order-of-magnitude discount in system price and vitality used, Buck stated.
For instance, Siemens teamed with Mercedes to investigate aerodynamics and associated acoustics for its new electrical EQE autos. The simulations that took weeks on CPU clusters ran considerably quicker utilizing the most recent NVIDIA H100 GPUs. As well as, Hopper GPUs allow them to cut back prices by 3x and cut back vitality consumption by 4x (beneath).
Switching on 200 Exaflops Starting Subsequent Yr
Scientific and industrial advances will come from each nook of the globe the place the most recent programs are being deployed.
“We already see a mixed 200 exaflops of AI on Grace Hopper supercomputers going to manufacturing 2024,” Buck stated.
They embrace the large JUPITER supercomputer at Germany’s Jülich middle. It will probably ship 93 exaflops of efficiency for AI coaching and 1 exaflop for HPC purposes, whereas consuming solely 18.2 megawatts of energy.
![Chart of deployed performance of supercomputers using NVIDIA GPUs through 2024](https://blogs.nvidia.com/wp-content/uploads/2023/11/Chart-on-350-exaflops-of-AI-performance-deployed-672x403.jpg)
Primarily based on Eviden’s BullSequana XH3000 liquid-cooled system, JUPITER will use the NVIDIA quad GH200 system structure and NVIDIA Quantum-2 InfiniBand networking for local weather and climate predictions, drug discovery, hybrid quantum computing and digital twins. JUPITER quad GH200 nodes might be configured with 864GB of high-speed reminiscence.
It’s certainly one of a number of new supercomputers utilizing Grace Hopper that NVIDIA introduced at SC23.
The HPE Cray EX2500 system from Hewlett Packard Enterprise will use the quad GH200 to energy many AI supercomputers coming on-line subsequent 12 months.
For instance, HPE makes use of the quad GH200 to energy OFP-II, a sophisticated HPC system in Japan shared by the College of Tsukuba and the College of Tokyo, in addition to the DeltaAI system, which is able to triple computing capability for the U.S. Nationwide Heart for Supercomputing Functions.
HPE can be constructing the Venado system for the Los Alamos Nationwide Laboratory, the primary GH200 to be deployed within the U.S. As well as, HPE is constructing GH200 supercomputers within the Center East, Switzerland and the U.Ok.
Grace Hopper in Texas and Past
On the Texas Superior Computing Heart (TACC), Dell Applied sciences is constructing the Vista supercomputer with NVIDIA Grace Hopper and Grace CPU Superchips.
Greater than 100 international enterprises and organizations, together with NASA Ames Analysis Heart and Whole Energies, have already bought Grace Hopper early-access programs, Buck stated.
They be a part of beforehand introduced GH200 customers corresponding to SoftBank and the University of Bristol, in addition to the large Leonardo system with 14,000 NVIDIA A100 GPUs that delivers 10 exaflops of AI efficiency for Italy’s Cineca consortium.
The View From Supercomputing Facilities
Leaders from supercomputing facilities world wide shared their plans and work in progress with the most recent programs.
“We’ve been collaborating with MeteoSwiss ECMWP in addition to scientists from ETH EXCLAIM and NVIDIA’s Earth-2 venture to create an infrastructure that can push the envelope in all dimensions of huge information analytics and excessive scale computing,” stated Thomas Schultess, director of the Swiss Nationwide Supercomputing Centre of labor on the Alps supercomputer.
“There’s actually spectacular energy-efficiency positive aspects throughout our stacks,” Dan Stanzione, govt director of TACC, stated of Vista.
It’s “actually the stepping stone to maneuver customers from the sorts of programs we’ve accomplished previously to this new Grace Arm CPU and Hopper GPU tightly coupled mixture and … we’re seeking to scale out by most likely an element of 10 or 15 from what we’re deploying with Vista once we deploy Horizon in a pair years,” he stated.
Accelerating the Quantum Journey
Researchers are additionally utilizing at this time’s accelerated programs to pioneer a path to tomorrow’s supercomputers.
In Germany, JUPITER “will revolutionize scientific analysis throughout local weather, supplies, drug discovery and quantum computing,” stated Kristel Michelson, who leads Julich’s analysis group on quantum info processing.
“JUPITER’s structure additionally permits for the seamless integration of quantum algorithms with parallel HPC algorithms, and that is necessary for efficient quantum HPC hybrid simulations,” she stated.
CUDA Quantum Drives Progress
The particular handle additionally confirmed how NVIDIA CUDA Quantum — a platform for programming CPUs, GPUs and quantum computer systems also referred to as QPUs — is advancing analysis in quantum computing.
For instance, researchers at BASF, the world’s largest chemical firm, pioneered a brand new hybrid quantum-classical methodology for simulating chemical compounds that may protect people towards dangerous metals. They be a part of researchers at Brookhaven Nationwide Laboratory and HPE who’re individually pushing the frontiers of science with CUDA Quantum.
NVIDIA additionally introduced a collaboration with Classiq, a developer of quantum programming instruments, to create a life sciences analysis middle on the Tel Aviv Sourasky Medical Heart, Israel’s largest instructing hospital. The middle will use Classiq’s software program and CUDA Quantum working on an NVIDIA DGX H100 system.
Individually, Quantum Machines will deploy the primary NVIDIA DGX Quantum, a system utilizing Grace Hopper Superchips, on the Israel Nationwide Quantum Heart that goals to drive advances throughout scientific fields. The DGX system might be linked to a superconducting QPU by Quantware and a photonic QPU from ORCA Computing, each powered by CUDA Quantum.
“In simply two years, our NVIDIA quantum computing platform has amassed over 120 companions [above], a testomony to its open, modern platform,” Buck stated.
Total, the work throughout many fields of discovery reveals a brand new development that mixes accelerated computing at information middle scale with NVIDIA’s full-stack innovation.
“Accelerated computing is paving the trail for sustainable computing with developments that present not simply superb expertise however a extra sustainable and impactful future,” he concluded.
Watch NVIDIA’s SC23 special address beneath.
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