Limited to 40 participants ONLY!!!

The 9th High Performance Computing Workshop (HPC9) is a series of workshop organized by Institute for Mathematical Research. High-performance computing (HPC) is the use of super computers and parallel processing techniques for solving complex computational problems. HPC and parallel processing is nowadays common. It is in all the computational environments, from mobile devices, laptops and desktops to clusters, large-scale data centers and supercomputers, often comprising CPUs and/or co- processors of different types (GPU, MIC, FPGA).

This workshop will conduct a series of talk by expert from academia and industry on the uses and current trend of high performance computer and parallel programming. There will be a workshop conducted by OEMS Intipakar Sdn. Bhd for Wolfram Mathematica technologies in the area of data analytics & machine learning, with world-class machine learning and classification algorithms, semantic data representation, and the knowledge-based programming.Additionally, this workshop also introduces the OpenACC, which is designed to simplify parallel programming of heterogeneous CPU/GPU systems. An introductory hands-on lesson will also be organized which introduce the implementation of OpenMPI, OpenMP and OpenACC. The main objectives of providing three (3) different parallel programming is to expose participants on differences of the style of programming, uses, performance and suitability of the parallel architecture.


  1. To share the uses and current trend of high performance computer and parallel programming.
  2. To expose users on the variety of parallel programming languages.
  3. To provide introductory information on how to modify, write, compile and run a parallel program.
Who Should Attend

We recommend attending this event for: 

  • Researchers
  • Students
  • Graduate students
  • Users new to HPC and anyone interested in an overview of HPC

©2019. Laboratory of Computational Sciences and Mathematical Physics. Institute for Mathematical Research. UPM.