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New PGI 17.7 Release Supports NVIDIA Volta GPUs

Today NVIDIA released Version 17.7 of PGI 2017 Compilers and Tools, delivering improved performance and programming simplicity to HPC developers who target multicore CPUs and heterogeneous GPU-accelerated systems.

OpenACC Brings Directives to Accelerated Computing at ISC 2017

In this video from ISC 2017, Sunita Chandrasekaran and Michael Wolfe describe how OpenACC makes GPU-accelerated computing more accessible to scientists and engineers. “OpenACC is a user-driven directive-based performance-portable parallel programming model designed for scientists and engineers interested in porting their codes to a wide-variety of heterogeneous HPC hardware platforms and architectures with significantly less programming effort than required with a low-level model.”

Introduction to Parallel Programming with OpenACC – Part 2

In this video, Michael Wolfe from PGI continues his series of tutorials on parallel programming. “The second in a series of short videos to introduce you to parallel programming with OpenACC and the PGI compilers, using C++ or Fortran. You will learn by example how to build a simple example program, how to add OpenACC directives, and to rebuild the program for parallel execution on a multicore system. To get the most out of this video, you should download the example programs and follow along on your workstation.”

Introduction to Parallel Programming with OpenACC

“This is the first in a series of short videos to introduce you to parallel programming with OpenACC and the PGI compilers, using C++ or Fortran. You will learn by example how to build a simple example program, how to add OpenACC directives, and to rebuild the program for parallel execution on a multicore system. To get the most out of this video, you should download the example programs and follow along on your workstation.”

PGI and NNSA to Open Source Fortran Compiler

Today the NNSA and its three national labs announced they have reached an agreement with Nvidia’s PGI software to create an open-source Fortran compiler designed for integration with the widely used LLVM compiler infrastructure.

PGI Accelerator Compilers Add OpenACC Support for x86

“Our goal is to enable HPC developers to easily port applications across all major CPU and accelerator platforms with uniformly high performance using a common source code base,” said Douglas Miles, director of PGI Compilers & Tools at NVIDIA. “This capability will be particularly important in the race towards exascale computing in which there will be a variety of system architectures requiring a more flexible application programming approach.”

Video: OpenACC for Fortran Programmers

“Learn how to program NVIDIA GPUs using Fortran with OpenACC directives. The first half of this presentation will introduce OpenACC to new GPU and OpenACC programmers, providing the basic material necessary to start successfully using GPUs for your Fortran programs. The second half will be intermediate material, with more advanced hints and tips for Fortran programmers with larger applications that they want to accelerate with a GPU. Among the topics to be covered will be dynamic device data lifetimes, global data, procedure calls, derived type support, and much more.”

PGI Steps up with Support for Jetson TK1 and Power8

At SC14, Nvidia announced that it is developing an enhanced version of the widely used PGI optimizing compilers which will allow developers to quickly develop new applications or run Linux x86-based GPU-accelerated applications on IBM POWER CPU systems with minimal effort.

PGI 14.4 Compiler Suite Adds OpenACC Features and Multicore Performance Gains

Today The Portland Group released Version 14.4 of the PGI 2014 Compilers and Tools suite with expanded OpenACC features and Multi-core x64 Performance Gains.

Free PGI Comes to OS X

This week PGI announced that Free PGI is now available for Macs running OS X. The package includes the PGI high-performance parallel C99 and Fortran 2003 compilers and parallel debugger for 64-bit and 32-bit Intel processor-based Macs.