How AI Plus HPC Equals the Future of Advanced Analytics Sponsored Content by HPE
Combining artificial intelligence (AI) and high-performance computing (HPC) can unlock the potential of each of these powerful analytics disciplines. This in turn can drive increased business agility, innovation, and competitive differentiation
To do this successfully, organizations must integrate AI and HPC infrastructure to create synergies through shared resources and improved flexibility. They also must work to improve collaboration between AI and HPC organizations, which are traditionally siloed.
A recent online study conducted by Forrester Consulting and commissioned by HPE confirmed this thinking. Participants in the study included 464 global decision-makers and practitioners, divided into business decision-makers relying on AI and/or HPC, AI experts, and HPC experts. Among the top findings:
- AI is an emerging discipline with high expectations
While many firms are currently investing in their AI disciplines, early returns show that AI capabilities are limited, and most are still in early stages of maturity. While 61% of AI experts say their firms are investing in infrastructure improvements currently, but just 26% of AI projects are in full deployment, and fewer than half of proofs of concept (POCs) deliver expected business value.
- Combining AI and HPC is the future
Most HPC experts say workflows incorporating machine learning algorithms to improve HPC speed and reduce costs will happen in the next year. Half of AI experts say they are using HPC infrastructure to improve unsupervised learning and machine learning (ML) model training by expanding processing flow with higher-performance data sourcing and calculating capabilities. As a result, experts expect unifying AI and ML to deliver critical benefits to innovation, competitive differentiation, business agility, and cost savings.
- Firms need integrated infrastructure to capitalize on the promise of AI and HPC
More than eight in 10 AI experts say that they will need to improve their infrastructure to meet future plans for AI. Meanwhile, over half of HPC experts say they need infrastructure upgrades to meet even current needs, with an additional 35% saying while their current infrastructure meets needs, they will require future improvements. With many of these future infrastructure improvements providing benefits to both AI and HPC, growing support for integrating AI and HPC infrastructure is on the horizon.
Adding Big Data into the equation
The study found synergies between HPC, AI, and big data can lead to top- and bottom-line business benefits. For example, big data reinvigorated the science of neural networks that led to deep learning breakthroughs.
Today deep learning (DL) is improving the benefits from HPC. Improvement in processing medical imagery is just one example. In fact, experts in the survey see many potential linkages between the use cases of AI, HPC, and big data. Top strategic business activities in which both AI and HPC can play a critical role include business modeling and simulation, process automation, and risk analysis.
Calculating your next move with HPC and AI
The in-depth survey of business decision-makers, HPC experts, and AI experts yielded three top recommendations:
- Look for synergies across workflows
Align organizations for better synergies across collaborative HPC and AI efforts to avoid data silos and to improve infrastructure efficiencies, enable better decision-making, and drive innovation improvement.
- Investigate a hybrid architecture
Increasing data growth and analysis for AI and HPC will require firms to invest in on-premises compute infrastructure. Choose technologies that support multiple use cases and mixed workflows, such as simulation, analytics, and AI). Look deeply at hybrid architectures to reduce bottlenecks when training complex AI models on large data sets.
- Expand to the edge
Growth of data at the edge will require firms to improve AI and analytics capabilities of the core data center and public cloud to deliver the insights organizations require. Choose infrastructure that can ingest and process data from the edge efficiently. Interconnectivity of edge and core will become increasingly important.
For more insights, you can register to download the complete study: AI Plus HPC: The Future of Advanced Analytics—How AI and HPC Will Support Each Other and Merge Over Time.