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The Convergence of HPC, Databases, and Analytics: Opportunities and Challenges

Explore the convergence of High-Performance Computing (HPC), databases, and analytics, revealing both the potential benefits and challenges. HPC introduces powerful parallelization techniques and hybrid architectures, while analytics offers innovative algorithms for new market opportunities. However, programming highly parallel systems is complex, and big data raises scaling issues across the analytical process. Despite these challenges, embracing abstraction layers and advanced visualization techniques can provide profound insights and societal advancements from large mixed datasets.

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The Convergence of HPC, Databases, and Analytics: Opportunities and Challenges

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Presentation Transcript

  1. The convergence of HPC, Databases and Analytics The Good • HPC brings a wealth of parallelization experience, petaflop scaling and hybrid architectures. • Analytics brings new algorithms and new markets. • The Database world brings new paradigms, new users and… Big Data.

  2. The convergence of HPC, Databases and Analytics The Bad • Highly parallel HPC machines are frankly hard to program. Hybrid architectures make this worse. • Analytics, particularly over non-tabular data structures, requires users to think about their problem in an entirely new way. • Big Data brings scaling issues to every link of the analysis chain, including the user.

  3. The convergence of HPC, Databases and Analytics The Beautiful • The ugliness of massively parallel hybrid architectures can be hidden under layers of abstraction. • New visualization techniques can bring new ways of understanding large problems. High-level languages calling HPC subroutines make programming easier. • New levels of insight into very large and mixed datasets will bring new benefits to society.

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