This IDC study centers on IDC's worldwide revenue forecast for 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; or newer methods such as large-scale graph analytics, semantic technologies, and knowledge discovery algorithms; or some combination of long-standing and newer methods. IDC forecasts that revenue for HPC servers acquired primarily for Big Data use will grow robustly (10.4% CAGR) during the 2010–2015 period, increasing from $602.9 million to approach $1 billion in 2015. IDC projects that in 2015, the largest segments for data-intensive server revenue will be government labs ($216.7 million) and university/academic ($214.8 million), followed by biosciences ($194.8 million) and defense ($133.2 million).
According to Steve Conway, IDC HPC Research vice president, The goal of HPC Big Data activity is typically to maximize insights and innovation by applying both established and newer methods to the same scientific or industrial problem, often using the same HPC system. In a growing number of cases, buyers are acquiring HPC systems for dedicated use to address a single, mission-critical problem. IDC believes that the HPC data explosion is bound to drive rapid growth in HPC Big Data usage. Nearly all HPC industry/application segments have potential use cases for Big Data methods.