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 (Initiatives on Measurement of Power Consumption & Performance) (hyPACK - 2013) ” which is scheduled from October 15-18, 2013 at CMSD, UoH. The workshop aims at understanding power-aware computing and performance of application kernels on High Performance Computing Systems with Intel Xeon Phi Co-processors & GPU Accelerators.
What is New in hypack-2013 :
Day-1 &
Day-2 :
HPC Cluster - Intel Xeon/Phi coprocessors, ARM multicore processor & HPC System : 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 4.0, Intel TBB, Intel Cilk Plus, Intel MKL; Intel Xeon-Phi Coprocessor Architecture; System software; Tuning Memory Allocation Performance - Huge Page Sizes; Profiling & Tuning Tools; - Measurement of Power Consumption & Performance Issues using External Power-Off-Meter; Application Kernels- Prog. on ARM processor systems;
Day 3 &
Day-4 :
An Overview of CUDA enabled NVIDIA GPUs : CUDA SDK/APIs; CUDA - Optimization & Performance Issues; Efficient use of different memory types, CUDA Libraries (CUBLAS, CUFFT, CULA Tools, MAGMA, CUSPARSE, Thurst); CUDA-OpenACC APIs; NVIDIA - OpenCL; 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 lib. - BLAS & FFTs; AMD APP SDK, AMD tools - Aparapi AP; AMD OpenCL tuning - performance; HPC AMD GPU Cluster: Host CPU (Pthreads, OpenMP 4.0, MPI) with OpenCL on AMD GPUs; GPU Cluster - Health Monitoring
Programming on ARM Processor multi-core systems; power-aware performance Issues on ARM processor systems; Prog. on carma - NVIDIA CUDA on ARM Develop. Kit; An Overview of FPGA Systems; Energy Efficiency - Power-Off Meters and NVML libraries; Power Efficient API - Perf. Issues; Health Monitoring GPUs in Cluster;
Apps: 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; Invited lectures on Information Sciences & Computational Physics
Important Dates...
Final Announcement
Reg. Open
Tech. Prog.
Early Bird Reg.
Final Tech. Prog.