Course Hero Logo

15 - Coding high performance big data analytics applications.pdf

Course Hero uses AI to attempt to automatically extract content from documents to surface to you and others so you can study better, e.g., in search results, to enrich docs, and more. This preview shows page 1 - 12 out of 24 pages.

The convergence of HPC and Big DataIntel® Data Analytics Acceleration Library (DAAL)Roger PhilpIntel HPC Software Workshop Series 2016HPC Code Modernization for Intel® Xeon and Xeon Phi™February 17th2016, Barcelona
Setting the stage for analytics2
Data analytics in the age of Big DataBig Data is converging with High Performance ComputingExtreme Data VolumesIntense Compute WorkloadsGap between current programming and hardware evolution More cores/threads, wider vectors, more memory, more storage, faster interconnectMany big data applications leave performance at the table Not optimized for underlying hardware3More CoresMore ThreadsMore MemoryMore StorageWider SIMD VectorsFaster Interconnect
Fraud detectionDetected using Benford‘sLaw4AB
Benford’slawAlso called the first digit lawStates that in listings, tables of statistics, etc., the digit 1 tends to occur with probability 30%, much greater than the expected 11.1% (i.e., one digit out of 9)Source: MathWorld530.1%17.6%12.5%9.7%7.9%6.7%5.8%5.1%4.6%0.000.050.100.150.200.250.30123456789P(D)IDC estimates that High Performance Data Analytics has saved PayPal more than $700 million so far (fraud detection)
Big data analytics: problem statement6Spark* MLLibBreezeNetlib-JavaJVMJNINetlibBLASRun on stat-of-art hardwareBuilt with patchwork of math libsNot exploiting HW performance featuresLimited performanceMany layers of dependenciesLow ROI on HW investment
Big data analytics: desired solution7Run on stat-of-art hardwareSingle library to cover all stages of data analyticsFully optimized for underlying HWOptimized performanceSimpler development/deploymentHigh ROI on HW investment
Intel® DAAL for HPC and analytics8
Introducing Intel® DAALData Analytics Acceleration LibraryAn industry leading end-to-end IA-based data analytics acceleration library of fundamental algorithms coveringall data analysis stagesWhat Intel DAAL brings to the game:Optimized algorithms based upon Intel® Math Kernel Library (Intel® MKL)Data serialization primitives to help running in a distributed systemSpeed and some building blocks for preprocessing dataSupport IA-32 and Intel64 architectures.C++, Java APIs. Static and dynamic linking.A standalone library, and also bundled in Intel® Parallel Studio XE 2016.Windows, Linux, OS-XMicrosoft Visual Studio* (Windows*) & Eclipse/CDT* (Linux*)9
Create faster code… fasterIntel® Parallel Studio XE Design, build, verify and tuneC++, C, Fortran and Java*Highlights from what’s new for “2016” editionIntel® Data Analytics Acceleration Library Vectorization Advisor:Custom Analysis and AdviceMPI Performance Snapshot: Scalable profiling Support for the latest Standards, Operating Systems and Processors 10
Intel® Parallel Studio XE 2016 configurationsComponentFull Licensing(including

Upload your study docs or become a

Course Hero member to access this document

Upload your study docs or become a

Course Hero member to access this document

End of preview. Want to read all 24 pages?

Upload your study docs or become a

Course Hero member to access this document

Term
Fall
Professor
Colette Maier
Tags
English, Ode, Intel DAAL, Intel Data Analytics

Newly uploaded documents

Show More

Newly uploaded documents

Show More

  • Left Quote Icon

    Student Picture

  • Left Quote Icon

    Student Picture

  • Left Quote Icon

    Student Picture