It’s no secret that every industry has been transformed by Artificial Intelligence (AI) and Machine Learning (ML), whether for improving the customer experience for their clients, improving operations within their organizations or many more such uses. To leverage the benefits of these new advances in technology, this next stage of digital transformation is led by strategic C-level AI initiatives within organizations. Recently, VMware announced the general availability of VMware Cloud Foundation 4.4 with Tanzu, now offering integration with NVIDIA AI Enterprise Suite. This integration means that the combination of these technologies, hybrid cloud infrastructure from VMware and best-in-class AI/ML suite of applications and GPUs from NVIDIA, can now enable organizations to build and deliver their AI/ML applications to deliver business outcomes.
VMware has published a solution brief, AI-Ready Infrastructure with NVIDIA and VMware Cloud Foundation, which details the challenges of adoption of AI/ML workloads for organizations and how the joint solution from VMware and NVIDIA can help these organizations in their digital transformation journey.
Challenges of AI/ML Adoption
Some of the challenges of AI/ML adoption include:
- High performance requirements for massive parallel processing for training, inferencing, and data analytics
- Need for specialized hardware such as network accelerators and Graphical Processing Units (GPUs)
- Coexistence of specialized infrastructure for AI/ML workloads and existing infrastructure
- Skillset gap for managing hybrid infrastructure
- High costs of hardware and management of infrastructure
One of the fallouts of these challenges is that many AI/ML projects never make it to production. VMware Cloud Foundation™ with Tanzu® provides a full-stack hybrid platform, based on a proven and comprehensive software-defined stack including VMware vSphere, VMware vSAN, VMware NSX-T Data Center and VMware vRealize Suite. The integration of NVIDIA AI Enterprise suite allows VMware to bring all the tools and lifecycle management capabilities that were previously available for VMs and extends them to GPU resources.
The solution brief describes how the joint solution from VMware and NVIDIA can help these organizations in their digital transformation journey and overcome these challenges.
These benefits include:
- Application focused management for unified visibility of VMs and containers
- Performance, security, and compliance of AI/ML workloads
- Higher productivity with less friction with self-serve capabilities for data scientists
- Raw performance of NVIDIA GPUs with full stack agility
- Enhanced raw performance for AI/ML workloads while maximizing utilization with AI and data science tools
- Efficient use and easy management of GPUs
- Infrastructure Lifecycle Management
- Intrinsic security at every layer of the stack
- Cloud operating model across public and private cloud