NVIDIA has announced that 70 more widely used applications have added support for GPU acceleration so far this year, bringing the total number available to researchers, engineers and designers to more than 200.

 

Three of the newest applications to offer GPU acceleration are:

 

  • ANSYS® Fluent®: ANSYS Fluent enables engineers to develop more aerodynamic cars and planes, which can save millions of dollars in fuel costs, or improve thermal management and reliability of electronic integrated circuit packages. ANSYS Fluent has added a new beta solver with single GPU support to its market-leading NVIDIA® CUDA® applications, including ANSYS Mechanical™.
  • MSC® Nastran®: Used by nearly every automotive manufacturer worldwide, MSC Nastran is a GPU-accelerated structural mechanics simulation application that helps optimize noise, vibration and harshness (NVH) performance, which are among the most often directly perceived quality attributes of a vehicle.
  • CHARMM: Widely used by scientists to study biological processes at the molecular level, CHARMM’s GPU acceleration enables a more accurate study of key proteins involved in disease, as well as interactions with drug candidates, as a means to develop more effective treatments.

 

“GPU computing first gained momentum among researchers who could download CUDA to accelerate their own applications for scientific discovery and research,” said Addison Snell, chief executive officer of Intersect360 Research. “We are now in a new era where more commercial software is GPU-optimized, providing accelerated options across the full spectrum of engineering and business computing.”

 

A partial list of other GPU-accelerating applications shipping or in development include:

 

  • Computer-aided Engineering: Abaqus/Standard, Agilent ADS & EMPro , ANSYS Mechanical, CST MWS, MSC Nastran, Marc, OpenFOAM solver libraries, RADIOSS™
  • Defense & Intelligence: DigitalGlobe Advanced Ortho Series, Exelis (ITT) ENVI, Incogna GIS, Intergraph Motion Video Analyst, MotionDSP Ikena ISR, PCI GEomatics GXL
  • Media & Entertainment: Adobe CS6, Autodesk 3ds Max & Maya, Blackmagic DaVinci Resolve, Chaos V-Ray RT, Elemental Server, Telestream Vantage
  • Oil & Gas: Acceleware AxRTM, ffA SVI Pro, Headwave Suite, Paradigm Echos RTM, Schlumberger Visage, WesternGeco Omega2 RTM
  • Scientific Computing: AMBER, CHARMM, Chroma, FastROCS, GAMESS, GROMACS, GTC, WL-LSMS, MATLAB, MILC, NAMD, QUDA, VASP, VMD
  • Weather & Climate Forecasting: COSMO, GEOS-5, HOMME, HYCOM, WRF, NEMO, NIM

 

A complete list is available at www.nvidia.com/teslaapps.

 

Most Accessible Parallel Processors

 

The advent of massively parallel GPU accelerators that are easily programmable in popular high-level languages or using auto-parallelizing compilers has given impetus to developers to maximize application performance.

 

Accelerators give developers a great degree of flexibility to take advantage of dramatic application speedups using familiar languages like C, C++ and Fortran, or using the directives-based OpenACC standard programming model.

 

Simple extensions to these high-level programming languages enable specifying parallelism using the NVIDIA CUDA parallel computing platform and programming model. Today the CUDA platform is supported by every NVIDIA GPU, resulting in a worldwide installed base of more than 415 million CUDA GPUs.

 

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