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INESC-ID Achieves 9x Acceleration for Epistasis Disease Detection

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Overview

Regardless of whether you're involved in medical science, this session is a good one for anyone interested in materially improving performance on Intel® CPUs of computationally challenging, algorithm-heavy applications.

Watch how two researchers at Instituto de Engenharia de Sistemas e Computadores: Investigação e Desenvolvimento em Lisboa (INESC-ID) accomplished improved performance for a critical epistasis disease-detection application that uses datasets spanning millions of genetic markers in multiple high-order combinations. This effectively expands datasets into the hundreds of trillions of samples that must be quickly and accurately evaluated.

Find out how they took advantage of oneAPI tools to transform their legacy code into multiarchitecture state-of-the-art code, plus see the results they achieved on Intel CPUs, including Intel® Xeon® CPU Max Series with high-bandwidth memory (HBM).

Skill level: Intermediate

 

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  • Intel® oneAPI DPC++/C++ Compiler
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  • Matrix Multiply with Intel Advisor
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Develop high-performance, data-centric applications for CPUs, GPUs, and FPGAs with this core set of tools, libraries, and frameworks including LLVM*-based compilers.

 

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Design code for efficient vectorization, threading, memory use, and accelerator offload. Supports C, C++, Fortran, SYCL*, OpenMP*, OpenCL™ programs, and Python*.

 

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