Today Supermicro announced the industry’s broadest portfolio of validated NGC-Ready systems optimized to accelerate AI and deep learning applications. Supermicro is highlighting many of these systems today at the Supermicro GPU Live Forum in conjunction with NVIDIA GTC Digital. “With support for fast networking and storage, as well as NVIDIA GPUs, our Supermicro NGC-Ready systems are the most scalable and reliable servers to support AI. Customers can run their AI infrastructure with the highest ROI.”
Julia Computing and GPU Acceleration
Julia is already well regarded for programming multicore CPUs and large parallel computing systems, but recent developments make the language suited for GPU computing as well. The performance possibilities of GPUs can be democratized by providing more high-level tools that are easy to use by a large community of applied mathematicians and machine learning programmers.
Simplifying AI, Data Science, and HPC Workloads with NVIDIA GPU Cloud
Adel El Hallak and Philip Rogers from NVIDIA gave this talk at the GPU Technology Conference. “Whether it’s for AI, data science and analytics, or HPC, GPU-Accelerated software can make possible the previously impossible. But it’s well known that these cutting edge software tools are often complex to use, hard to manage, and difficult to deploy. We’ll explain how NGC solves these problems and gives users a head start on their projects by simplifying the use of GPU-Optimized software.”
Why UIUC Built HPC Application Containers for NVIDIA GPU Cloud
In this video from the GPU Technology Conference, John Stone from the University of Illinois describes how container technology in the NVIDIA GPU Cloud help the University distribute accelerated applications for science and engineering. “Containers are a way of packaging up an application and all of its dependencies in such a way that you can install them collectively on a cloud instance or a workstation or a compute node. And it doesn’t require the typical amount of system administration skills and involvement to put one of these containers on a machine.”
Video: Deploy HPC Applications Faster with NVIDIA GPU Cloud
The HPC application containers available on NVIDIA GPU Cloud (NGC) drastically improve ease of application deployment, while delivering optimized performance. The containers include HPC applications such as NAMD, GROMACS, and Relion. NGC gives researchers and scientists the flexibility to run HPC application containers on NVIDIA Pascal and NVIDIA Volta-powered systems including Quadro-powered workstations, NVIDIA DGX Systems, and HPC clusters.
NVIDIA GPU Cloud comes to AWS with Volta GPUs
“In just a few steps, the NVIDIA GPU Cloud (NGC) container registry helps developers get started with no-cost access to a comprehensive, easy-to-use, fully optimized deep learning software stack. The cloud-based service is available immediately to users of the just-announced Amazon Elastic Compute Cloud (Amazon EC2) P3 instances featuring NVIDIA Tesla V100 GPUs. NVIDIA plans to expand support to other cloud platforms soon.”