What is high-performance architecture?
High-performance architecture (HPA) is a platform and environment designed and purpose-built to process massive amounts of data and solve complex problems at very high speeds. An HPA includes high-performance computing (also referred to as accelerated computing), high-performance networking and high-performance storage.
Additional characteristics of an HPA can include:
- Parallel processing: Clusters of high-powered processors operating on similar workloads that can be spread across the multiple compute nodes, executed simultaneously, and the outputs consolidated for faster completion.
- Purpose-built and optimized for high performance: All components in an HPA are designed for high speed, high throughput and low latency to maximize throughput. You can fine-tune and make trade-offs to extract the highest possible performance across the architecture. This includes ensuring compute, storage and networking operate as a balanced throughput machine. Any one component in an idle state creates a less efficient environment that leads to bottlenecks, slowing the operations.
- Dynamic architecture: Compute, storage and networking can grow and shrink to match workload scale demands.
AI Solutions leverage the capabilities of an HPA. Explore WWT's AI Solutions to learn about the breadth of industry use cases WWT can address.
High-performance architecture is critical to each phase of the AI workflow, from model development through deployment. Without the right foundation, enterprises will struggle to realize the full value of investments in AI applications.
High-performance computing (HPC)
The right amount of combined CPU and GPU processing power is needed to train and run modern AI engines.
High-performance storage
The ability to reliability store, clean and scan massive amounts of data is required to train AI/ML models.
High-performance networking
AI/ML applications require extremely high-bandwidth and low-latency network connections.
Automation, orchestration, software and applications
HPA requires the right mix of data science tools and infrastructure optimization.
Strategy and governance
Data must be protected and readily accessible to systems and users.
Talent and skills
The right mix of experts is needed to build AI models and maintain HPA infrastructure.
High-Performance Architecture (HPA)
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