NEC Hackathon: HPC (SX-Aurora TSUBASA)

731 Registered Allowed team size: 1 - 4

This campaign is over.

idea phase
starts on:
Jul 21, 2019, 07:30 PM
ends on:
Aug 25, 2019, 01:29 PM
starts on:
Sep 27, 2019, 10:30 PM
ends on:
Sep 29, 2019, 06:30 AM


To read more about Aurora, please click here.


Accelerating Spark MLlib and DataFrame with Vector Processor "SX-Aurora TSUBASA"

Supercomputing 2018 (SC18) HandsOn Resources

Resources at Supercomputing 2018 hands-on about NEC SX-Aurora Tsubasa Vectorizing Compiler

Aurora Vectorization Training

Machine Learning Library:

The participants can use machine learning library called Frovedis which specially developed for SX-Aurura TSUBASA.

The top tells you what Frovedis is, how to install it in your system.

  • Tutorial of Python/Spark interface

There is Python/Spark interface for Frovedis functions.

The tutorial guides you to use the interface quickly. It includes how to set environmental variables before execution, how to write code with python/spark interface to perform matrix operation, machine learning, dataframe functionalities supported by Frovedis



  • Manual of Python/Spark API. We make python interface similar to scikit-learn, spark interface to spark MLlib. These are the API documentation which explains how to use classes, the member functions in detail.



  • Performance benchmark and tips to improve performance.

There are scripts to measure the time to run machine learning with Frovedis and scikit-learn. Also it has tips to improve the runtime performance. Click here

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