Artificial Intelligence (AI) and High-Performance Computing (HPC) are both computationally-intensive workloads. They demand fast central processing units (CPUs), accelerators, very large data sets, and fast networking to support the high degree of scaling typically required. All this fast hardware can be difficult to manage and expensive. AI and HPC adopters must try to minimize costs while delivering the performance and agility demanded by the organization’s mission. Chief among the decisions that must be made is whether to build and host the application on a public cloud or build an on-premises infrastructure. While the industry trend is clearly to move new applications to the cloud, AI and HPC workloads have performance, data requirements, and utilization characteristics that could lead one to go in the opposite direction.
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Table Of Contents
- Introduction
- The Cloud Computing Landscape For AI And HPC
- The Dell EMC Computing Portfolio For AI And HPC
- Common Considerations
- Conclusions And Recommendations
- Figure 1: The Dell EMC PowerEdge C4140
Companies Cited
- AWS
- Amazon
- Dell EMC
- Microsoft
- NVIDIA
- RightScale Cloud Management
- Xilinx
