VMware & NVIDIA bolster GPU services for high-performance computing
NVIDIA and VMware are putting their collective forces behind improving GPU services to power intensive machine learning, data science, and artificial intelligence workflows for VMware Cloud on AWS.
The two companies will deliver accelerated GPU services that will allow customers to migrate VMware vSphere-based applications and containers to the cloud, completely unchanged. Once on the cloud, they can take advantage of high-performance computing, machine learning, data analytics and video processing applications.
According to NVIDIA CEO Jensen Huang, businesses rely on GPU-accelerated computing in everything from operational intelligence and artificial intelligence to make predictions that impact their bottom line.
“Together with VMware, we’re designing the most advanced GPU infrastructure to foster innovation across the enterprise, from virtualisation, to hybrid cloud, to VMware's new Bitfusion data center disaggregation.”
The companies also state that businesses are using AI technologies to make themselves stand out from their competitors. AI-based strategies increasingly require powerful computers to create predictive models from petabytes of corporate data.
“Our customers are embracing the unique value of VMware Cloud on AWS to accelerate the migration and modernisation of business-critical applications,” says VMware CEO Pat Gelsinger.
“Through new innovations driven by partnerships we have with industry leaders such as NVIDIA and AWS, we will bring best-in-class GPU acceleration services for the most intense data-driven workloads and modern applications across the hybrid cloud.”
Once these services become available, businesses will be able to leverage an enterprise-grade hybrid cloud platform to accelerate application modernisation.
They will also be able to unify deployment, migration and operations across a consistent VMware infrastructure from data center to the AWS cloud in support of most compute-intensive workloads, including AI, machine learning and data analytics.
- Seamless portability: Customers will be able to move workloads powered by NVIDIA vComputeServer software and GPUs with a single click of a button, and no downtime, using VMware HCX. This will give customers more choice and flexibility to execute training and inference in the cloud or on-premises.
- Elastic AWS infrastructure: With the ability to automatically scale VMware Cloud on AWS clusters, accelerated by NVIDIA T4, administrators will be able to grow or shrink available training environments depending on the needs of their data scientists.
- Accelerated computing for modern applications: NVIDIA T4 GPUs feature Tensor Cores for acceleration of deep learning inference workflows. When these are combined with vComputeServer software for GPU virtualisation, businesses have the flexibility to run GPU-accelerated workloads like AI, machine learning and data analytics in virtualisation environments for improved security, utilisation and manageability.
- Consistent Hybrid Cloud Infrastructure and Operations: With VMware Cloud on AWS, organisations can establish consistent infrastructure and consistent operations across the hybrid cloud, leveraging VMware industry-standard vSphere, vSAN and NSX as a foundation for modernising business-critical applications. IT operators will be able to manage GPU-accelerated workloads within vCenter, alongside GPU-accelerated workloads running on vSphere on-premises.
- Seamless, end-to-end data science and analytics pipeline: The NVIDIA T4 data center GPU supercharges mainstream servers and accelerates data science techniques using NVIDIA RAPIDSTM, a collection of NVIDIA GPU acceleration libraries for data science including deep learning, machine learning and data analytics.