NVIDIA today announced availability of its newest PGI Accelerator Fortran, C and C++ compilers (version 15.10) now with support for OpenACC directives-based parallel programming standard on x86 architecture multicore microprocessors. The new compilers allow OpenACC-enabled source code to be compiled for parallel execution on a multicore CPU or a GPU accelerator. “Our goal is to Read more…
As the non-profit standards group behind the push for wider adoption via easier use of accelerators, OpenACC has quite a big job ahead. Although analysts agree that accelerators sit along a comfortable adoption curve, usability, programmability and portability are key concerns, among others. Over the last couple of years, OpenACC has worked with user groups Read more…
Moments ago, NVIDIA announced its acquisition of the Portland Group (PGI) which has provided compiler and tools for the HPC-oriented C and Fortran markets. According to the company’s Sumit Gupta, this will allow them to further build their software portfolio and to push the adoption of GPUs through OpenACC in particular. NVIDIA and PGI will…
<img style=”float: left;” src=”http://media2.hpcwire.com/hpcwire/Gerhard_Wellein_small.jpg” alt=”” width=”95″ height=”85″ />At this June’s International Supercomputing Conference (ISC’13) in Leipzig, Germany, Gerhard Wellein will be delivering a keynote entitled, Fooling the Masses with Performance Results: Old Classics & Some New Ideas. HPCwire caught up with Wellein and asked him to preview some of the themes of his upcoming talk and expound on his philosophy of programming for performance in the multicore era.
<img style=”float: left;” src=”http://media2.hpcwire.com/hpcwire/green_mb.bmp” alt=”” width=”109″ height=”91″ />There are several approaches being developed to program heterogeneous systems, but none of them have proven to successfully address the real goal. This article will discuss a range of potentially interesting heterogeneous systems for high performance computing, why programming them is hard, and why developing a high level programming model is even harder.
<img style=”float: left;” src=”http://media2.hpcwire.com/hpcwire/OpenCL_logo.png” alt=”” width=”80″ height=”76″ />As the two major programming frameworks for GPU computing, OpenCL and CUDA have been competing for mindshare in the developer community for the past few years. Until recently, CUDA has attracted most of the attention from developers, especially in the high performance computing realm. But OpenCL software has now matured to the point where HPC practitioners are taking a second look.
CUDA versus OpenMP for GPUs. What’s a developer to do?
Cray has released the details of its GPU-equipped supercomputer: the XK6. The machine is a derivative of the XE6, an AMD Opteron-based machine that the company announced a year ago. Although Cray is calling this week’s announcement the XK6 launch, systems will not be available until the second half of the year.
In May, Intel announced the Many Integrated Core (MIC) architecture, with a development kit codenamed Knights Ferry. NVIDIA has announced and started to deliver its next-generation architecture, Fermi. PGI’s Michael Wolfe presents an in-depth comparison of the two designs.
HPC compiler maker PathScale has unveiled ENZO, a new GPU software development suite aimed at the high performance computing space. The solution includes a home-grown compiler, runtime system, and device driver. ENZO is being built for performance from top to bottom and will initially target NVIDIA’s high-end GPUs.