Center for Development of Advanced Computing (C-DAC) Pune and Centre for Modelling Simulation and Design (CMSD), High-Performance Computing (HPC) Facility University of Hyderabad, Hyderabad are jointly organizing Four days technology workshop on “ Hybrid Computing - Coprocessors & Accelerators - Power-aware Computing & Performance of Application Kernels (hyPACK-2013) ”.

hyPACK-2013 objective is to understand power-aware performance issues of various scientific application kernels and computational mathematics on parallel processing platforms such as computing systems with Intel Xeon-Phi Coprocessors and NVIDIA /AMD GPU accelerators as well as ARM processor based Linux multi-core processor systems. The aim is to achieve the best performance (turnaround time & throughput) and the total power consumption, a device or a system needs in order to solve a problem of given size in High Performance Computing (HPC) application kernels. The focus is to integrate different programming paradigms such as Pthreads, OpenMP 4.X, Intel TBB, Cilk Plus, MPI, Intel Xeon-Phi Offload Pragmas, MPI-OpenMP, & NVIDIA CUDA, OpenACC, OpenCL and extract the best achieved performance for application kernels on systems with coprocessors and accelerators. The workshop gives an opportunity to write, execute and demonstrate computational mathematics and application kernels using different programming paradigms. The workshop is aimed to cover classroom lectures in morning/forenoon session and four hours hands-on in afternoon session on every day.

Topics of interest include the following but not limited to:

Day 1 & Day-2 HPC Cluster - Intel Xeon/Phi coprocessors; ARM multi-core processor & HPC Cluster

• Programming on Intel Xeon-Phi Coprocessors; Xeon-Phi Coprocessor usage model : MPI vesus Offload; Compiler and Programming model; Approaches to Vectorization - Complier Offload Pragmas & Directives; Programming Paradigms - OpenMP-4.0, Intel TBB, Intel Cilk Plus, Intel MKL, MPI
• 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

• An Overview of CUDA enabled NVIDIA GPUs : CUDA SDK/APIs; CUDA - Optimization & Performance Issues; Efficient use of different memory types, Libraries-CUBLAS, CUFFT, CUSPARSE; CUDA-OpenACC APIs; Programming - 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 & Efficient use of 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; Efficient use of GPUs in Cluster; Open Source Software using GPUs - MAGMA, & Top-500 Benchmarks

• 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

hypack-2013 Registration