Monday, June 17th 2019
NVIDIA Brings CUDA to ARM, Enabling New Path to Exascale Supercomputing
NVIDIA today announced its support for Arm CPUs, providing the high performance computing industry a new path to build extremely energy-efficient, AI-enabled exascale supercomputers. NVIDIA is making available to the Arm ecosystem its full stack of AI and HPC software - which accelerates more than 600 HPC applications and all AI frameworks - by year's end. The stack includes all NVIDIA CUDA-X AI and HPC libraries, GPU-accelerated AI frameworks and software development tools such as PGI compilers with OpenACC support and profilers. Once stack optimization is complete, NVIDIA will accelerate all major CPU architectures, including x86, POWER and Arm.
"Supercomputers are the essential instruments of scientific discovery, and achieving exascale supercomputing will dramatically expand the frontier of human knowledge," said Jensen Huang, founder and CEO of NVIDIA. "As traditional compute scaling ends, power will limit all supercomputers. The combination of NVIDIA's CUDA-accelerated computing and Arm's energy-efficient CPU architecture will give the HPC community a boost to exascale."
"Arm is working with our ecosystem to deliver unprecedented compute performance gains and exascale-class capabilities to Arm-based SoCs," said Simon Segars, CEO of Arm. "Collaborating with NVIDIA to bring CUDA acceleration to the Arm architecture is a key milestone for the HPC community, which is already deploying Arm technology to address some of the world's most complex research challenges."
According to the Green500 list released today, NVIDIA powers 22 of the world's 25 most energy-efficient supercomputers.
Key factors making this possible are: the ability of NVIDIA GPU-powered supercomputers to offload heavy processing jobs to more energy-efficient parallel processing CUDA GPUs; NVIDIA's collaboration with Mellanox to optimize processing across entire supercomputing clusters; and NVIDIA's invention of SXM 3D-packaging and NVIDIA NVLink interconnect technology, which allows for extremely dense scale-up nodes.
NVIDIA's support for Arm-based HPC systems builds on more than 10 years of collaboration. NVIDIA uses Arm for several of its system on a chip products available for portable gaming, autonomous vehicles, robotics and embedded AI computing.
"Supercomputers are the essential instruments of scientific discovery, and achieving exascale supercomputing will dramatically expand the frontier of human knowledge," said Jensen Huang, founder and CEO of NVIDIA. "As traditional compute scaling ends, power will limit all supercomputers. The combination of NVIDIA's CUDA-accelerated computing and Arm's energy-efficient CPU architecture will give the HPC community a boost to exascale."
According to the Green500 list released today, NVIDIA powers 22 of the world's 25 most energy-efficient supercomputers.
Key factors making this possible are: the ability of NVIDIA GPU-powered supercomputers to offload heavy processing jobs to more energy-efficient parallel processing CUDA GPUs; NVIDIA's collaboration with Mellanox to optimize processing across entire supercomputing clusters; and NVIDIA's invention of SXM 3D-packaging and NVIDIA NVLink interconnect technology, which allows for extremely dense scale-up nodes.
NVIDIA's support for Arm-based HPC systems builds on more than 10 years of collaboration. NVIDIA uses Arm for several of its system on a chip products available for portable gaming, autonomous vehicles, robotics and embedded AI computing.
24 Comments on NVIDIA Brings CUDA to ARM, Enabling New Path to Exascale Supercomputing
Samsung going AMD should have Nvidia very worried lol. Samsung is chipzilla.
Only exception was Switch and that's probably because they had a stockpile of Tegra chips, not knowing what to do with them.
This news piece is just missing those comments from HPC industry, which are on Nvidia's press release. So there are some shift to arm on future HPC projects and Nvidia are just making their gpus available for such a endeavors. In short this has nothing to do with Tegra.
Nvidia's Lead Exceeds Intel's in Cloud
Nvidia holds a more commanding share of dedicated accelerators than Intel holds in overall compute among the top four public cloud services.
Nvidia’s GPUs now account for 97.4% of infrastructure-as-a-service (IaaS) instance types of dedicated accelerators deployed by the top four cloud services. By contrast, Intel’s processors are used in 92.8% of compute instance types, according to one of the first reports from Liftr Cloud Insights’ component tracking service.
www.eetimes.com/author.asp?section_id=36&doc_id=1334812&_mc=RSS_EET_EDT#
Not sure where you, guys, get the "failed" part. It was an awful platform for portables, but "surprisingly" a commercial success due to its full-featured GPU. Tegra 3 was in Nexus 7 tablets - the most popular and best-selling tablet of its time, K1 was in Shield tablet and several popular chromebook models (only beaten by Samsung XE303C12 as the only "other" ARM alternative). Tegra X1 was relatively expensive and only made its way into a Shield TV, but X2 on the other hand is currently powering the best-selling console on the market. All of the above does not even include automotive applications (Drive PX/CX etc), and thousands of Jetson dev kits they sourced for educational institutions and sold to hobbyists and CV/AI/Robotics researchers.
How time change :)