| NVIDIA CUDA Week in Review: Issue 38 |
| Written by NVIDIA | ||
| Tuesday, 12 October 2010 | ||
NVIDIA CUDA Week in Review: Issue 38NVIDIA CUDA & GPU computing news from around the worldHot picks on YouTube:
CUDA SPOTLIGHT: The Portland Group (PGI) recently announced a partnership with NVIDIA. For more info, see the PGI press release. CUDA NEWS: GTC 2010 Keynote Speaker Featured in New York Times The work of Dr. Sebastian Thrun, who delivered the closing address at this year's GTC, was highlighted in the New York Times on Oct. 10 in an article titled "Google Cars Drive Themselves, in Traffic." See: www.nytimes.com/2010/10/10/science/10google.html?_r=2&ref=technology Plenoptics and the Future of Digital Photography Abbas Jaffar Ali of T-Break Tech saw Adobe's plenoptics technology demoed at GTC 2010. He writes: "Plenoptics - remember that word as it might just be the future of digital photography. See: https://tbreak.com/tech/2010/10/plenoptics-the-future-of-digital-photography MATLAB Adds GPU Support Michael Feldman of HPCwire reports: "MATLAB users with a taste for GPU computing now have a perfect reason to move up to the latest version. Release R2010b adds native GPGPU support that allows users to harness NVIDIA graphics processors for engineering and scientific computing." See: www.hpcwire.com/features/MATLAB-Adds-GPGPU-Support-103307084.html New Version of Thrust NVIDIA released Thrust v1.3, an open-source template library for developing CUDA applications. Modeled after the C++ Standard Template Library (STL), Thrust brings a familiar abstraction layer to GPU computing. To get started, download Thrust v1.3 and then follow the online quick-start guide. Parallel Nsight and CUDA Toolkit Overview NVIDIA added new performance improvements and capabilities to Parallel Nsight and the CUDA Toolkit. For info, watch the video overview by NVIDIA's Will Ramey and Stephen Jones. CUDA JOB OF THE WEEK: Oak Ridge National Laboratory's Leadership Computing Facility (OLCF) is seeking a postdoc research associate for the project "Massively Parallel Block Structured Adaptive Mesh Refinement on Hybrid Architectures for Subsurface Flow Applications." The ideal applicant will have a Ph.D. in Applied Math, C.S. or related field; Experience with PETSc, Hypre, SAMRAI libraries; Parallel programming experience with MPI; and experience with CUDA. See: www.orau.org/ornl/postdocs/ornl-pd-pm/description.aspx?JobId=653 Read CUDA: Week in Review at: https://www.nvidia.com/object/cuda_week_in_review_newsletter.html Related Articles:
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