The combination of artificial intelligence (AI) and high performance computing (HPC) can unlock the potential of each of these powerful analytics disciplines. This in turn can drive business agility, innovation and competitive differentiation.
To achieve this, organizations must integrate AI and HPC infrastructure to create synergies through shared resources and improved flexibility. They should also strive to improve collaboration between AI and HPC organizations, which have traditionally been siled.
A recent online study conducted by Forrester Consulting and commissioned by HPE confirmed this idea. Study participants included 464 global decision makers and practitioners, broken down into AI and/or HPC-enabled business decision makers, AI experts, and HPC experts. Among the main discoveries:
- AI is an emerging discipline with high expectations
While many companies are currently investing in their AI disciplines, early feedback shows that AI capabilities are limited and most are still in their early stages of maturity. While 61% of AI experts say their companies are currently investing in infrastructure improvements, only 26% of AI projects are in full deployment and less than half of proofs of concept (POCs) deliver the value commercial expected.
- Combining AI and HPC is the future
Most HPC experts say that workflows integrating machine learning algorithms to improve HPC speed and reduce costs will happen next year. Half of AI experts say they use HPC infrastructure to improve unsupervised learning and machine learning (ML) model training by expanding processing flow with better data sourcing and computing capabilities . As a result, experts expect the unification of AI and ML to bring critical benefits to innovation, competitive differentiation, business agility, and cost savings.
- Businesses need an integrated infrastructure to capitalize on the promise of AI and HPC
More than eight in 10 AI experts say they will need to improve their infrastructure to meet future AI plans. Meanwhile, more than half of HPC experts say they need infrastructure upgrades to meet even current needs, and a further 35% say that if their current infrastructure meets needs, they will need future improvements. . With many of these future infrastructure enhancements providing benefits to both AI and HPC, growing support for the integration of AI and HPC infrastructure is on the horizon.
Add Big Data to the equation
The study found that synergies between HPC, AI, and Big Data can drive business benefits in terms of revenue and bottom line. For example, big data has reinvigorated the science of neural networks which has led to breakthroughs in deep learning.
Today, deep learning (DL) enhances the benefits of HPC. Improving medical imaging processing is just one example. In fact, experts in the survey see many potential connections between the use cases of AI, HPC, and Big Data. Key strategic business activities where AI and HPC can play a vital role include business modeling and simulation, process automation, and risk analytics.
Calculate your next move with HPC and AI
The in-depth survey of business decision makers, HPC experts and AI experts resulted in three main recommendations:
- Look for synergies between workflows
Align organizations for better synergies between collaborative HPC and AI efforts to avoid data silos and improve infrastructure efficiency, enable better decision-making and drive improvement of innovation.
- Study a hybrid architecture
Increasing data growth and analytics for AI and HPC will require enterprises to invest in on-premises compute infrastructure. Choose technologies that support multiple use cases and mixed workflows, such as simulation, analytics, and AI). Dig deep into hybrid architectures to reduce bottlenecks when training complex AI models on large datasets.
- Expand to edge
The growth of data at the edge will require companies to improve the AI and analytics capabilities of the core data center and public cloud to deliver the insights organizations need. Choose an infrastructure that can efficiently ingest and process data from the edge. The interconnectivity of edge and core will become increasingly important.
For more information, you can register to download the full study: AI Plus HPC: The future of advanced analytics: how AI and HPC will support each other and merge over time.