About Tech Program Multicore ARM Coprocessor GPUs Cluster Applications Registration


FINAL CALL FOR PARTICIPATION (Early Bird Registration is Extended till october 01, 2013 )

Center for Development of Advanced Computing (C-DAC) Pune , and Centre for Modelling Simulation and Design (CMSD), University of Hyderabad (UoH) are jointly organizing Four Days Technology Workshop on Hybrid Computing - Coprocessors & Accelerators - Power-aware Computing & Performance of Application Kernels (HyPACK 2013) which is scheduled from October 15-18, 2013 at CMSD, UoH.




The HyPACK-2013 workshop is aimed to cover classroom lectures in morning/forenoon session and four hours hands-on in afternoon session on every day and invited talks from leading academic institutes and industries. Programming on Multi-Core Processors, basic programs using CUDA/OpenCL enabled NVIDIA GPUs and OpenCL - AMD GPUs, please visit hyPack-2013

What Is New In hyPACK-2013 Important Dates
Intel Xeon Phi Coprocessor (OpenMP 4.0)
Power-aware Computing & Performance issues
OpenCL-enabled AMD APUs (GPU Accelerators)
July 14 : Final Announcement
July 25 : Reg. Open
July 25 : Tech. Prog.
July 30 : Lab. Session
Sep 20 : Early Bird Reg.
Oct 01 : Extended Early Bird
Oct 01 : Final Tech. Prog.

Topics of interest include but are not limited to:

Day 1    & Day 2
HPC Cluster - Intel Xeon Phi coprocessors ; ARM processors & HPC Systems

  • Programming on Intel Xeon Phi Coprocessors; Xeon Phi Coprocessor usage model : MPI vesus Offload; Compiler and Programming model; Approaches to Vectorization - Complier Directives; Programming Paradigms - OpenMP, Intel TBB, Intel Cilk Plus, Intel MKL
  • Intel Xeon-Phi Coprocessor Architecture; Linux OS on Coprocessor; Coprocessor System software; Tuning Memory Allocation Performance - Huge Page Sizes; Profiling & Tuning Tools - PAPI & MPI tools
  • Tuning and Performance Issues - Power Consumption for Application Kernels; Measurement of Power Consumption - External Power-Off-Meter; Application Kernels; Programming on ARM processor multi-core processor systems; Energy Efficiency & Performance Issues
Day 3     & Day 4
HPC Cluster - NVIDIA & AMD GPUs ; ARM processors ; HPC Cluster - Accelerators

  • An Overview of CUDA enabled NVIDIA GPUs : CUDA SDK/APIs; CUDA - Optimization & Performance Issues; Efficient use of different memory types, CUDA accelerated Libraries (CUBLAS, CUFFT, CULA Tools, MAGMA, CUSPARSE, Thurst); CUDA-OpenACC APIs; NVIDIA - OpenCL; CUDA NVIDIA GPU Cluster
  • An Overview of AMD Accelerated Parallel Processing (APP) Capabilities; AMD APUs - OpenCL Prog. On Multi-Core CPUs & Multi-GPUs; AMD APP Math libraries - BLAS & FFTs; AMD APP SDK, AMD tools - Aparapi AP; AMD OpenCL tuning - performance; HPC AMD GPU Cluster: Host CPU (Pthreads, OpenMP, MPI) with OpenCL on AMD GPUs; GPU Cluster - Health Monitoring - AMD GPUs using OpenCL
  • Programming on ARM Processor multi-core systems; power-aware performance Issues on ARM Multi-Coprocessor systems; Prog. on carma - NVIDIA CUDA on ARM Development Kit
  • An Overview of FPGA Device Systems; Energy Efficiency - Power-Off Meters and NVML libraries - Health Monitoring - NVML Power Efficient API - Performance Issues of GPUs in Cluster; Top-500 Benchmarks
Application Kernels
HPC Cluster - Intel Xeon Phi Coprocessors ; ARM processor systems ; NVIDIA & AMD GPUs Accelerators

  • Mixed Programming for Numerical /Non-Numerical Computations on multi-core processors with Intel Xeon-Phi coprocessors - and NVIDIA /AMD GPU accelerators and ARM processor systems; Application & System Benchmarks & Performance; Image Processing Applications; Bio-Informatics - String Search Algorithms & Sequence Analysis; Dense /Sparse Matrix Computations on HPC GPU Cluster; Solution of Partial Differential Eqs. (FDM & FEM); FFT Libraries; Information Sciences & Computational Physics