C-DAC,Pune : High-Perf. Comp. Frontier Technologies Exploration Group and CMSD, University of Hyderabad, Technology Workshop hyPACK (October 15-18), 2013

Overview Venue : CMSD, UoH Key-Note/Invited Talks Faculty / Speakers Proceedings Downloads Past Tech. Workshops Target Audience Benefits Organisers Accommodation Local Travel Sponsors Feedback Acknowledgements Contact Home

Topics of Interest Tech. Prog. Schedule Topic : Multi-Core Topic : ARM Proc. Topic : Coprocessors Topic : GPGPUs Topic : HPC Cluster Topic : App. Kernels. Topic : Lab. Session Key-Note / Invited Talks Home

Mode-1 Multi-Core Memory Allocators OpenMP Intel TBB Pthreads Java - Threads Charm++ Prog. Message Passing (MPI) MPI - OpenMP MPI - Intel TBB MPI - Pthreads Compilers - Opt. Features Threads-Perf. Math. Lib. Threads-Prof. & Tools Threads - I/O Perf. PGAS : UPC / CAF/ GA Power & Perf. Home

Mode-2 ARM Prog. Env Benchmarks Power & Perf. Home

Mode-3 Coprocessors Arch. Software Compiler & Vect. Prog. Env. Benchmarks Power & Perf. Home

Mode-4 GPGPUs NVIDIA - CUDA/OpenCL AMD APP - OpenCL GPGPUs - OpenCL GPGPUs : Power & Perf. Home

Mode-5 HPC Cluster HPC MPI Cluster GPU Cluster - NVIDIA GPU Cluster - AMD APP Cluster - Intel Coprocessors Cluster- Power & Perf. Home

Mode-6 App. Kernels PDE Solvers : FDM/FEM Image Processing - FFT Monte Carlo Methods String Srch. Seq. Analy. Video Process. Intr. Detcn. Sys App. Power & Perf. Home

Reg. Overview Pvt. Sector Pub. Sector Govt. Acad. Staff Students Reg. On-line Reg. Accommodation Contact Home

. Mode-4 GPGPUs . NVIDIA - CUDA/OpenCL . AMD APP OpenCL . GPGPUs - OpenCL . GPGPUs : Power & Perf. . Home

hyPACK-2013: PGI Compilers OpenACC CUDA enabled NVIDIA GPU

NVIDIA\92s Compute Unified Device Architecture (CUDA) is a software platform for massively parallel high-performance computing on the company's powerful GPUs. PGI compilers deliver world-class performance across a wide spectrum of applications and benchmarks. PGI is the compiler-of-choice among many popular performance-critical applications used in the fields of geophysical modeling, mechanical engineering, computational chemistry, weather forecasting, and high-energy physics.

The Portland Group, a leader in GPGPU development tools and technologies for HPC, offers one and two day courses on NVIDIA GPU Programming with CUDA C, CUDA Fortran and the PGI Accelerator programming model.The PGI Fortran & C accelerator programming model document covers only user-directed accelerator programming, where the user specifies the regions of a host program to be targeted for offloading to an accelerator device.

Application -Porting a 3D Elastic Wave Simulator to GPUs Using PGI Accelerator

Using MAGMA with PGI Fortran

Using the CULA GPU-enabled LAPACK Library with CUDA Fortran

Parallel Random Number Generation Using OpenMP, OpenCL and PGI Accelerator Directives

PGI 2012 compilers language support exisit for full CUDA C/C++ compiler for targettting multi-core x64 platforms. For GPU Computing, support for the OpenACC GPU programming directives specification v1.0 and Asynchronous data transfers and kernel launch are provided. One of the objectives to use PGI compiler on CUDA enabled NVIDIA GPUs is to introduce a collection of compiler directives in the specific regions of code in Fortran and C programs that can be offloaded from a host CPU to an attached CUDA enable d NVIDIA GPU accelerator. This method provides a model for accelerator programming that is portable across operating systems and various types of host CPUs and accelerators.

For more information PGI Accelerator Programming Model for Fortran & C

Module : Summary of Programs on OpenACC in hyPACK-2013 workshop

Set of Programs on Numerical Linear Algebra and Solution of Possion Equations by Finite Difference mehtod (FDM) will be discussed.
PGI tutorials on applications will be provided.

Centre for Development of Advanced Computing