NVIDIA announces breakthrough new GPU
In his online keynote at GTC 2000, NVIDIA founder and Chief
Executive Jensen Huang has announced innovations that rewrite what powers data centres worldwide:
- The NVIDIA A100, the first GPU based on the NVIDIA Ampere architecture.
- The NVIDIA DGX A100 system, which features eight NVIDIA A100 GPUs interconnected with NVIDIA NVLink.
- Two products for its EGX Edge AI platform — the EGX A100 for larger commercial off-the-shelf servers and the tiny EGX Jetson Xavier NX for micro-edge servers for high-performance, secure AI processing at the edge.
The NVIDIA A100 is in full production and shipping to customers worldwide. The A100 draws on design breakthroughs in the NVIDIA Ampere architecture — offering the company’s largest leap in performance to date within its eight generations of GPUs — to unify artificial intelligence (AI) training and inference and boost performance by up to 20x over its predecessors.
A universal workload accelerator, the A100 is also built for data analytics, scientific computing and cloud graphics.
“The powerful trends of cloud computing and AI are driving a tectonic shift in data centre designs so that what was once a sea of CPU-only servers is now GPU-accelerated computing,” said Huang.
“NVIDIA A100 GPU is a 20x AI performance leap and an end to-end machine learning accelerator — from data analytics to training to inference. For the first time, scale-up and scale-out workloads can be accelerated on one platform. NVIDIA A100 will simultaneously boost throughput and drive down the cost of data centres.”
New
elastic computing technologies built into A100 make it possible for it
to adapt computing resources for every job. A multi-instance GPU
capability allows each A100 GPU to be
partitioned into as many as seven independent instances for inferencing tasks, while third-generation NVIDIA NVLink interconnect technology allows multiple A100 GPUs to operate as
a 'giant GPU' for larger training tasks.
The world’s leading cloud service providers and systems builders that expect to incorporate A100
GPUs into their offerings include: Alibaba Cloud, Amazon Web Services (AWS), Atos, Baidu Cloud,
Cisco, Dell Technologies, Fujitsu, GIGABYTE, Google Cloud, H3C, Hewlett Packard Enterprise
(HPE), Inspur, Lenovo, Microsoft Azure, Oracle, Quanta/QCT, Supermicro, and Tencent Cloud.
Among the first to tap into the power of NVIDIA A100 GPUs is Microsoft, which will take
advantage of their performance and scalability.
“Microsoft trained Turing Natural Language Generation, the largest language model in the world,
at scale using the current generation of NVIDIA GPUs,” said Mikhail Parakhin, Corporate VP, Microsoft Corp.
“Azure will enable training of dramatically bigger AI models using NVIDIA’s new generation of A100 GPUs to push the state of the art on language, speech, vision and multi-modality.”
DoorDash, an on-demand food platform serving as a lifeline to restaurants during the pandemic,
notes the importance of having a flexible AI infrastructure.
“Modern and complex AI training and inference workloads that require a large amount of data
can benefit from state-of-the-art technology like NVIDIA A100 GPUs, which help reduce model
training time and speed up the machine learning development process,” said Gary Ren, Machine Learning Engineer at DoorDash, a food delivery service with a presence in Australia.
“In addition, using cloud-based GPU clusters gives us newfound flexibility to scale up or down as needed, helping to improve efficiency, simplify our operations and save costs."
Other early adopters include national laboratories and some of the world’s leading higher
education and research institutions, each using A100 to power their next-generation
supercomputers.
NVIDIA A100 in new systems
The NVIDIA DGX A100 system, also announced today, features eight NVIDIA A100 GPUs
interconnected with NVIDIA NVLink. It is available immediately from NVIDIA and approved
partners.
Alibaba Cloud, AWS, Baidu Cloud, Google Cloud, Microsoft Azure, Oracle, and Tencent Cloud are
planning to offer A100-based services.
Additionally, a wide range of A100-based servers are expected from leading systems
manufacturers, including Atos, Cisco, Dell Technologies, Fujitsu, GIGABYTE, H3C, HPE, Inspur,
Lenovo, Quanta/QCT, and Supermicro.
To help accelerate development of servers from its partners, NVIDIA has created HGX A100 — a
server building block in the form of integrated baseboards in multiple GPU configurations.
The four-GPU HGX A100 offers full interconnection between GPUs with NVLink, while the eight
GPU configuration offers full GPU-to-GPU bandwidth through NVIDIA NVSwitch. HGX A100,
with the new MIG technology, can be configured as 56 small GPUs, each faster than the NVIDIA T4,
all the way up to a giant eight-GPU server with 10 petaflops of AI performance.
Details:
The NVIDIA DGX A100 is available immediately from NVIDIA and approved partners.
- The NVIDIA A100, the first GPU based on the NVIDIA Ampere architecture.
- The NVIDIA DGX A100 system, which features eight NVIDIA A100 GPUs interconnected with NVIDIA NVLink.
- Two products for its EGX Edge AI platform — the EGX A100 for larger commercial off-the-shelf servers and the tiny EGX Jetson Xavier NX for micro-edge servers for high-performance, secure AI processing at the edge.
The NVIDIA A100 is in full production and shipping to customers worldwide. The A100 draws on design breakthroughs in the NVIDIA Ampere architecture — offering the company’s largest leap in performance to date within its eight generations of GPUs — to unify artificial intelligence (AI) training and inference and boost performance by up to 20x over its predecessors.
A universal workload accelerator, the A100 is also built for data analytics, scientific computing and cloud graphics.
“The powerful trends of cloud computing and AI are driving a tectonic shift in data centre designs so that what was once a sea of CPU-only servers is now GPU-accelerated computing,” said Huang.
“NVIDIA A100 GPU is a 20x AI performance leap and an end to-end machine learning accelerator — from data analytics to training to inference. For the first time, scale-up and scale-out workloads can be accelerated on one platform. NVIDIA A100 will simultaneously boost throughput and drive down the cost of data centres.”
 |
| Source: NVIDIA. The NVIDIA A100. |
partitioned into as many as seven independent instances for inferencing tasks, while third-generation NVIDIA NVLink interconnect technology allows multiple A100 GPUs to operate as
a 'giant GPU' for larger training tasks.
The world’s leading cloud service providers and systems builders that expect to incorporate A100
GPUs into their offerings include: Alibaba Cloud, Amazon Web Services (AWS), Atos, Baidu Cloud,
Cisco, Dell Technologies, Fujitsu, GIGABYTE, Google Cloud, H3C, Hewlett Packard Enterprise
(HPE), Inspur, Lenovo, Microsoft Azure, Oracle, Quanta/QCT, Supermicro, and Tencent Cloud.
Among the first to tap into the power of NVIDIA A100 GPUs is Microsoft, which will take
advantage of their performance and scalability.
“Microsoft trained Turing Natural Language Generation, the largest language model in the world,
at scale using the current generation of NVIDIA GPUs,” said Mikhail Parakhin, Corporate VP, Microsoft Corp.
“Azure will enable training of dramatically bigger AI models using NVIDIA’s new generation of A100 GPUs to push the state of the art on language, speech, vision and multi-modality.”
DoorDash, an on-demand food platform serving as a lifeline to restaurants during the pandemic,
notes the importance of having a flexible AI infrastructure.
“Modern and complex AI training and inference workloads that require a large amount of data
can benefit from state-of-the-art technology like NVIDIA A100 GPUs, which help reduce model
training time and speed up the machine learning development process,” said Gary Ren, Machine Learning Engineer at DoorDash, a food delivery service with a presence in Australia.
“In addition, using cloud-based GPU clusters gives us newfound flexibility to scale up or down as needed, helping to improve efficiency, simplify our operations and save costs."
Other early adopters include national laboratories and some of the world’s leading higher
education and research institutions, each using A100 to power their next-generation
supercomputers.
NVIDIA A100 in new systems
The NVIDIA DGX A100 system, also announced today, features eight NVIDIA A100 GPUs
interconnected with NVIDIA NVLink. It is available immediately from NVIDIA and approved
partners.
Alibaba Cloud, AWS, Baidu Cloud, Google Cloud, Microsoft Azure, Oracle, and Tencent Cloud are
planning to offer A100-based services.
Additionally, a wide range of A100-based servers are expected from leading systems
manufacturers, including Atos, Cisco, Dell Technologies, Fujitsu, GIGABYTE, H3C, HPE, Inspur,
Lenovo, Quanta/QCT, and Supermicro.
To help accelerate development of servers from its partners, NVIDIA has created HGX A100 — a
server building block in the form of integrated baseboards in multiple GPU configurations.
The four-GPU HGX A100 offers full interconnection between GPUs with NVLink, while the eight
GPU configuration offers full GPU-to-GPU bandwidth through NVIDIA NVSwitch. HGX A100,
with the new MIG technology, can be configured as 56 small GPUs, each faster than the NVIDIA T4,
all the way up to a giant eight-GPU server with 10 petaflops of AI performance.
Details:
The NVIDIA DGX A100 is available immediately from NVIDIA and approved partners.
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