CUDA GPGPU Parallel Computing Newsletter - Issue 60

GPU-Accelerated Molecular Dynamics
This week’s spotlight is on Dr. Ross Walker, assistant research professor with the San Diego Supercomputer Center (SDSC) at UC San Diego and adjunct assistant professor in the Department of Chemistry and Biochemistry at UC San Diego.

Dr. Walker is a lead developer of AMBER (Assisted Model Building with Energy Refinement), a Molecular Dynamics (MD) software package for the simulation of biomolecules. A new update of AMBER, focusing on improved GPU acceleration, was recently made available to the public.

NVIDIA: Ross, tell us about the AMBER news announcement.

Ross: The announcement concerns a large scale update to the GPU acceleration support in AMBER. This is something we have been working on for the last nine months with funding from the National Science Foundation’s Scientific Software Infrastructure and Innovation program, in close collaboration with NVIDIA.

NVIDIA: What are potential applications of GPU-accelerated AMBER?

Ross: The latest update to GPU-accelerated AMBER provides performance that was previously unattainable, even with the fastest supercomputers. Thus we are now in a realm where for the first time we are talking about increasing capability and not just GPU acceleration. This widens the scope for the types of scientific questions one can attempt to solve.

NVIDIA: What kind of advantages have you achieved with CUDA?

Ross: I cannot begin to do justice to the revolution that GPU acceleration through CUDA is having on Molecular Dynamics. The GPU acceleration of MD through CUDA is, for the first time, making it possible for scientists to ‘experiment’ computationally. With our latest update, the performance of the code on a single Tesla M2090 GPU outstrips that achievable on 192 nodes of a Cray XT5 supercomputer.

NVIDIA: When you think about the future of Molecular Dynamics, what excites you the most?

Ross: We are only just beginning to scratch the surface in the types of questions we can ask with Molecular Dynamics. Traditionally it has been too slow and computationally expensive to make a significant impact in the drug discovery process but with GPU acceleration we are now at a point where the accuracy of MD approaches is no longer limited by the amount of sampling that can be done.

- Read the complete interview here

(Would you like to be in the CUDA Spotlight? Email cuda_week_in_review@nvidia.com)

CUDA Apps Roundup: New Releases and Updates

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- PGI CUDA Fortran v11.8 - CUDA development tool. www.pgroup.com/cudafortran
- ATL SeqNFind - Genomics toolset for bioinformatics. http://bit.ly/pexBP2
- TidePowerd GPU.NET v2.0 - New features. http://bit.ly/nNwk2m
- AccelerEyes Jacket v1.8 and LibJacket v1.1. http://bit.ly/n7zNl2
- CUDPP release v2.0 - CUDA data-parallel primitives library. http://bit.ly/nsbwx5
- TunaCode CUVI v0.5 - Image processing. http://cuvilib.com
- rCUDA v3.0 - CUDA calls to remote GPUs. http://bit.ly/n5vdV9
- Odeint - C++ library for ordinary differential equations. http://bit.ly/qeNeE3

Stanford Seminars on High Performance Computing with CUDA
Stanford has posted videos from the Spring 2011 seminar series held at the Institute for Computational and Mathematical Engineering (ICME). The ICME is directed by Professor Margot Gerritsen.
- Lecture 1: Intro to HPC with CUDA 1 (Cyril Zeller)
- Lecture 2: Intro to HPC with CUDA 2 (Justin Luitjens)
- Lecture 3: Optimizations 1 - Global Memory (Inderaj Bains)
- Lecture 4: Optimizations 2 - Shared Memory (Steven Rennich)
- Lecture 5: Finite Difference Stencils on Regular Grids (Paulius Micikevicius)
For videos, see: http://bit.ly/osrgYk
For slides, see: http://bit.ly/pYAEqN

SC 2011 – Register Today
- It’s not too early to register for SC 2011 in Seattle, Washington. The theme of the conference is Data Intensive Science: http://bit.ly/qRLIcB
- For a trip down memory lane, see proceedings from the inaugural SC conference in 1989: http://bit.ly/n4SPrC

ANSYS Regional Conferences
ANSYS, developer of CAE (computer-aided engineering) software, is hosting a series of regional conferences for end-users. The meetings are targeted to designers, engineers, analysts, managers and executives who are solving next-generation engineering challenges.
- To register, see: http://www.ansys.com/Conference
- To read more about NVIDIA and ANSYS, see: http://bit.ly/nOXze3

GPUs Crunch Data from Square Kilometer-Sized Radio Telescope, by Heather Mackay

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NEW: Each week we highlight sessions from GTC 2010 and ISC 2011. Here are our picks for this week:

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      Harnessing the GPU to Accelerate Automotive Development (GTC 10)
      Igor Juric and Tomislav Bosko – Dok-Ing
      http://nvidia.fullviewmedia.com/gtc2010/0921-d-2304.html

      Real-time Visualization of Medical Images (ISC 2011)
      Massimo Bernaschi – University La Sapienza
      http://www.nvidia.com/content/PDF/isc-2011/Bernaschi.pdf

NEW: Aptina Imaging is looking for talented software engineers to join the imaging solutions development team in San Jose, Calif. Required: Experience with GPGPU, OpenCL or CUDA; 3+ years of consumer software development in C++.
See: http://bit.ly/pL7CVN

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If you are travelling to any of these locations, feel free to drop in. Visitors are welcome.

- United States
        New York GPU Meetup – Aug. 22, 6:00 pm
        South Florida GPU Meetup – Aug. 29, 6:30 pm (inaugural meeting!)
        Denver/Boulder GPU Meetup – Aug. 29, 6:30 pm
        Boston GPU Meetup – Sept. 1, 6:00 pm
        New York GPU Meetup – (Special Meeting) September 8, 6:00 pm
        Silicon Valley GPU Meetup – Sept. 12, 6:15 pm

- Australia
        Sydney GPU Meetup – Sept. 15, 6:00 pm

August 2011	back to the top

- NEW: CUDA Optimization (Webinar)

Aug. 23, 2011

Presented by Paulius Micikevicius, NVIDIA

Note: First in a new series of optimization webinars

http://www.gputechconf.com/object/gtc-express-webinar.html

- NEW: In-Depth CUDA Training (Presented by Acceleware, with Microsoft)

Aug. 30-Sept. 2, 2011, Chicago, Illinois

http://acceleware.com/aug30chicago

September 2011

- Advanced Numerical Methods on GPUs

Mini-symposium at ENUMATH 2011

Sept. 5-9, 2011, Univ. of Leicester, Leicester, UK

http://www2.le.ac.uk/departments/mathematics/research/enumath2011/minisymposia

- Parallel Processing and Applied Mathematics (PPAM 2011)

Sept. 11-14, 2011, Torun, Poland

Note: Scientific Computing with GPUs tutorial, incl. session by Tim Schroeder, NVIDIA

http://ppam.pl/tutorials/21

- Geospatial Summit

Sept. 13-14, 2011, Herndon, Virginia

http://cfp.foseinstitute.org/gis2011

- Rapid Problem Solving Using Thrust (Webinar)

Sept. 14, 2011

Presented by Nathan Bell, NVIDIA

Note: Thrust is a library that enables programmers to develop high-performance applications on CUDA with minimal effort.

http://www.gputechconf.com/object/gtc-express-webinar.html

- CUDA Course (Presented by SagivTech)

Sept. 18-20, 2011, Ramat Gan, Israel

Hands-on sessions and optimization techniques.

http://www.sagivtech.com/24054.html

- CUDA Course (Presented by Tech-X)

Sept. 19-21, Boulder, Colorado

http://www.txcorp.com/products/GPULib/cuda_training/download.php

- Russian-German HPC School

Sept. 19-30, Novosibirsk

http://conf.nsc.ru/hpcschool

- SPIE Conference on High-Performance Computing in Remote Sensing

Sept. 19-22, 2011, Prague, Czech Republic

http://spie.org/rs11

- SEG (Society of Exploration Geophysicists) Annual Meeting

Sept. 18-23, 2011, San Antonio, Tex.

http://www.seg.org/events/annual-meeting/sanantonio2011/am2011techprogram

(To list an event, email: cuda_week_in_review@nvidia.com)

Downloads	back to the top
– CUDA 4.0: www.nvidia.com/getcuda – Parallel Nsight: http://developer.nvidia.com/nvidia-parallel-nsight
Webinars
– CUDA: www.nvidia.com/webinars – Parallel Nsight: http://developer.nvidia.com/developer-webinars

CUDA Registered Developer Program

– Sign up: www.nvidia.com/paralleldeveloper

CUDA GPUs

– List of CUDA-enabled GPUs: www.nvidia.com/object/cuda_gpus.html

CUDA on the Web

– See previous issues of CUDA: Week in Review: http://is.gd/cBXbg
– Follow CUDA & GPU Computing on Twitter: www.twitter.com/gpucomputing
– Network with other developers: www.gpucomputing.net
– Stayed tuned to GPGPU news and events: www.gpgpu.org
– Learn more about CUDA on CUDA Zone: www.nvidia.com/cuda
– Check out the NVIDIA Research page: www.nvidia.com/research

CUDA Recommended Reading

– Future of Computing Performance: http://bit.ly/hYqH2H
– Supercomputing for the Masses, Part 21: http://is.gd/Fj56gf
– CUDA books: http://www.nvidia.com/object/cuda_books.html

CUDA Recommended Viewing

– The Third Pillar of Science: www.nvidia.com/object/race-for-better-science.html

– GTC 2010 presentations: www.nvidia.com/gtc

– SC10 presentations: www.nvidia.com/object/sc10_theater.html

CUDA is NVIDIA’s parallel computing hardware architecture. NVIDIA provides a complete toolkit for programming on the CUDA architecture, supporting standard computing languages such as C, C++ and Fortran as well as APIs such as OpenCL and DirectCompute. Send comments and suggestions to: cuda_week_in_review@nvidia.com

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