In our increasingly connected and digitized era, greater volumes of data are being generated. But the amount of data is not just growing—it’s growing exponentially. Forward-looking companies that depend on high performance computing (HPC) applications are preparing for this surge. They are recognizing the need for using HPC capabilities to enable emerging analytics and AI workflows—and the opportunities that come with it. Intel provides the path to converging HPC, AI, and other workloads so that companies can be at the cutting edge of this technology wave.
Optimizing HPC Systems for Big Data Workloads
For data center managers, the rapid expansion of data represents a challenge of convergence—they need to optimize their HPC infrastructure to handle the very large workloads of big data, as well as concurrent analytics, AI, accelerated data visualization, and modeling and simulation workloads. This means ramping up the capabilities of today’s HPC systems.
The latest HPC resources make it possible to cost-effectively integrate extremely large and diverse workloads on current HPC systems. By enhancing the performance of HPC architecture, organizations can turn the challenge of too much data into a tremendous opportunity for analyzing and extracting insights. This is especially true when data-intensive workloads can scale to the edge, where data is being created.
Driving the Convergence of HPC and Big Data
Intel and our partners are leading the convergence of HPC and big data running on traditional HPC infrastructure to help address the largest data-driven problems and achieve extreme scale.
Unlocking the Amazing Possibilities of HPDA
At the center of the HPC-big data convergence is what’s known as high performance data analytics (HPDA), which allows companies to quickly analyze extremely large data sets. HPDA applies to any use case that involves data mining—discovering patterns and trends from massive data sets. HPDA is enabling companies to tackle today’s most complex scientific and analytical problems, ushering in new possibilities in real-time fraud detection, climate modeling, and weather forecasting.
As a major supporter of the open source software ecosystem, Intel contributes to projects such as Hadoop and continues to provide optimizations to open source big data analytics tools. HPC platforms based on Intel® architecture are helping advance HPDA capabilities for large data processing and big data Hadoop applications.
Integrating AI with HPC
Massive and complex data sets are driving the intersection of HPC and artificial intelligence (AI). By applying machine and deep learning to their traditional methods, HPC practitioners can better support tasks like pattern classification and clustering. For example, deep learning can help HPC systems identify fraudulent transactions or predict diseases. Conversely, in order to scale their deep learning models, data scientists are tapping into the enormous computing power of HPC systems. The convergence of AI and HPC is poised to make incredible advances in physics, weather prediction, global climate modeling, and many other practice areas.
Getting the Most from HPC-Based Analytics
Organizations adopting analytics platforms must find the most efficient path to an HPC infrastructure that will also support their data analytics initiatives and other applications, such as AI. These converged systems will deliver the greatest return on investment and, ideally, the lowest total cost of ownership (TCO). Intel provides a flexible platform to support converged analytics and AI workloads with hardware, software, and partner solutions designed for performance and scalability.
Powering Diverse Workloads on Converged HPC Clusters
To accelerate innovation and realize meaningful breakthroughs, enterprises are looking to run simulation and modeling, AI, and big data analytics workloads in HPC environments. However, they might believe that separate, dedicated clusters are required to handle these complex workloads and deliver the level of performance they need. Intel offers compute-intensive resources to allow enterprises to deploy these workloads within the same HPC infrastructure.
Intel® Select Solutions for HPC and AI Converged Clusters
Intel® Select Solutions for HPC and AI Converged Clusters build on Intel® Select Solutions for Simulation and Modeling to bring compatibility and optimized performance to existing HPC clusters. By adding a multidomain resource management layer, AI and analytics frameworks can run on the same system.
Propelling Genomics Analytics Forward
The interdisciplinary and fast-changing field of genomics involves the study of genetic material, including the structure and mapping of genomes. Rapid advancements in this field—made possible by leaps in HPC technologies—allow scientists today to process enormous quantities of genomic data, transforming our collective knowledge of human genetics and diseases. Powered by HPDA computing clusters, genomics analytics promises to unlock biomedical discoveries and inform precision medicine.
Intel® Select Solutions for Genomics Analytics
Intel® Select Solutions for Genomics Analytics provide end-to-end, optimized hardware and open source software configurations that leverage the high performance of Intel® architecture to accelerate insights and discoveries.
New Realms of Discovery
As HPC, AI, and data analytics continue to come together and HPDA applications become more mainstream, Intel is working with ecosystem partners and the HPC community to address tomorrow’s computational problems and the next scientific breakthroughs.
Through hardware innovation and ecosystem collaboration, Intel is helping organizations create unified clusters optimized for HPC, AI, and HPDA workloads.