A free webinar on accelerating face-in-the-crowd recognition with GPU technology will be held on November 5th. It teaches how GPUs can be used to accelerate face detection and recognition of people in the crowd. The presentation will also cover the speakers’ use of ROS, OpenCV, OpenMP, and Armadillo libraries to develop fast reliable distributed video processing code. To register follow the link: https://www2.gotomeeting.com/register/292953058
GPU Technology Conference (GTC) is NVIDIA’s annual developer event and consistently attracts the world’s best and brightest GPU developers, creating opportunities for connection and learning through technical sessions and in-depth tutorials in science, professional graphics, game development, mobile computing, cloud computing and automotive applications, as well as first-hand interactions with peers, luminaries, and emerging and established companies.
If you are doing innovative work using GPU, please submit a proposal at https://gtc2014.consenseus.com/
The deadline is Friday, September 27.
Northeastern University and Boston University, together with NVIDIA, are hosting a “GPUs Accelerating Research” Week next month.
On the first day, Wednesday 4/24, Northeastern is hosting a day of talks focused on how graphics processors are accelerating new and interesting areas of research in novel ways. The goal of this meeting is to provide a venue for both industry and academia to come together to discuss these innovations, and explore what lies ahead in GPU acceleration. Given that we have limited space in this one-day workshop, papers not selected for presentation at the workshop will have the option to present at a poster session to be held during the workshop. Please visit our website for registration and other details.
On the second day, Thursday 4/25, Boston University is hosting an all-day CUDA and OpenACC developer’s workshop. Prerequisites for getting the most out of this workshop are a basic understanding of C and the Linux command line. More details can be found here.
The following new webinars about NVIDIA Tesla K20 have been announced. During these live webinars, developers will be able to get answers directly from the presenters.
From a recent announcement:
GTC is the largest conference dedicated to heterogeneous parallel computing to solve the most complex computational challenges and features 300+ sessions over four days.
Whether you’re a commercial developer responsible for getting applications or products to market quickly or a researcher whose results are tied to important funding sources, GTC 2013 offers exceptional opportunities to learn directly from some of the foremost thinkers and practitioners in parallel computing. Immerse yourself in the best practices, solutions, and techniques that can help you enhance your skills, improve your workflow, and accelerate time to your all-important results.
Register today at http://www.gputechconf.com/page/registration-pricing.html.
Attended GTC before? You’re entitled to a 15% discount off a Full Conference or One-Day Conference pass. Please use discount code GMALUM15 when you register.
Supercomputing luminaries and experts like Jack Dongarra and Takayuki Aoki will be presenting in NVIDIA’s GPU Technology Theater at SC12. Talks will happen every 30 minutes and will also be webcast live with interactive Q&A on NVIDIA’s website. For the complete lineup of science and developer talks visit http://www.nvidia.com/object/sc12-technology-theater.html. SC12 takes place Nov. 10-16 in Salt Lake City, Utah.
In Silicon Valley? Interested in C++? Join in an evening with Microsoft & NVIDIA to discuss new C++ technology for parallel computing. Register here: http://vnextmsvc.eventbrite.com/
- 5:45 PM Welcome & Registration
- 6:00 PM Heterogeneous Parallelism in General, C++ in AMP in Particular, presented by Herb Sutter, Principal Architect for Windows C++, Microsoft
- 7:15 PM ALM tools for C++ in Visual Studio V.NEXT, presented by Rong Lu, Program Manager C++, Microsoft
- 8:00 PM The Power of Parallel, presented by the NVIDIA Team;
- Parallel Nsight: Programming GPUs in Visual Studio, Stephen Jones, NVIDIA;
- CUDA 4.0: Parallel Programming Made Easy, Justin Luitjens, NVIDIA;
- Thrust: C++ Template Library for GPGPUs, Jared Hoberock, NVIDIA
The next GPU Technology Conference, GTC 2012, will be held May 14-17 2012, in San Jose, California. Los Alamos National Laboratory’s co-located Accelerated High Performance Computing (HPC) Symposium will move to the same week, as will the new InPar 2012 academic conference, geared towards providing a first-tier venue for peer-reviewed publications in the field of innovative parallel computing.
The North Carolina Renaissance Computing Institute (RENCI) is running Amber PMEMD on the Open Science Grid, the high throughput computing (HTC) fabric used by the Large Hadron Collider (LHC). This approach is likely to be helpful to researchers with any of these challenges:
- Constrained by limited computing resources including access to GPGPUs
- Manually executing the same simulation repeatedly with different parameters
- Making simulations easier to understand, share, scale and re-use across compute resources
For more information see these two blog posts: High Throughput Parallel Molecular Dynamics and CUDA/Tesla Accelerated PMEMD on OSG. Contact Steve Cox (email@example.com) if you’d like to discuss further and determine if your application is a fit. If it is, RENCI can provide access to the grid as well as tools for executing and managing simulations.
Expanding the already comprehensive breadth of topics covered at GTC 2010, the GTC Content Committee has added new topic areas for 2011. Below is a partial list; see the GTC website for full details:
- Application Design & Porting Techniques
- Climate & Weather Modeling
- Cluster Management
- Computational Structural Mechanics
- Parallel Programming Languages
GTC is also looking for posters that describe novel or interesting research topics in parallel computing, visual computing, and applications of GPUs, with a particular interest in submissions describing GPU computing and CUDA applications that solve diverse problems in scientific and engineering domains. Read the rest of this entry »