Worldwide High-Performance Data Analysis Forecast, 2016–2020
This IDC study centers on IDC's worldwide revenue forecast for HPDA servers, that is, HPC server systems that are acquired primarily to run data-intensive (Big Data) workloads. HPC Big Data activity may employ long-standing methods based on numerical modeling and simulation; newer methods such as large-scale graph analytics, semantic technologies, and knowledge discovery algorithms; or a combination of long-standing and newer methods.According to Steve Conway, IDC research vice president for High Performance Computing, "The goal of HPDA activity is typically to maximize insights and innovation by applying both established and newer methods to the same scientific, industrial, or commercial problem, often using the same HPC cluster. In a growing number of cases, however, buyers are acquiring HPC systems for dedicated use on mission-critical, high-performance analytics workloads. Buyers are also turning more often to public and hybrid cloud resources to tackle HPDA problems. IDC believes that the data explosion in science, engineering, and commercial analytics is bound to drive rapid growth in HPDA usage. Nearly all HPC industry/application segments, along with a growing number of commercial first-time HPC adopters, have potential use cases for HPDA. Finally, the application to machine and deep learning of HPC-style parallelism, data movement, and big memories promises to transform that formative market over time."
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