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| NVIDIA - CUDA: Week in Review - October 12, 2010 |
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| Tuesday, 12 October 2010 18:51 |
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Press Release
Welcome to CUDA: Week in Review, an online news summary for the worldwide CUDA and GPU computing community. CUDA ON YOUTUBE CUDA SPOTLIGHT The Portland Group (PGI) recently announced a partnership with NVIDIA. We interviewed PGI's Douglas Miles for more details. NVIDIA: Douglas, tell us about PGI. Douglas: PGI is based in Portland, Oregon. We create software tools that maximize performance and portability of applications across Linux, Windows and OSX. Today, these tools include CUDA Fortran and the PGI Accelerator for NVIDIA GPUs. NVIDIA: What did PGI announce at GTC 2010? Douglas: We announced the "PGI CUDA C compiler," a new tool that will enable CUDA developers to deploy their applications on systems based on the industry-standard x86 architecture. NVIDIA: Why is this significant? Douglas: Today's application developers need flexibility. They want to be able to create innovative apps that leverage parallel computing and then deploy these apps on a wide range of target systems. The new PGI CUDA C compiler will enable developers to write parallel CUDA C applications that can run on x86 workstations, servers and clusters - with or without NVIDIA GPUs. NVIDIA: Will the new PGI CUDA C compiler work with both AMD and Intel processors? Douglas: Yes. PGI compilers have been optimized for performance on the latest AMD and Intel processors since 1997. All of that technology will be put to work optimizing both the sequential and massively parallel components of CUDA C applications. NVIDIA: What is the timing for the rollout? Douglas: We will demonstrate a prototype at SC '10 in November in New Orleans. We aim to have a first production release in Q2 2011. For more info, see the PGI press release. CUDA NEWS GTC 2010 Keynote Speaker Featured in New York Times Plenoptics and the Future of Digital Photography MATLAB Adds GPU Support New Version of Thrust Parallel Nsight and CUDA Toolkit Overview 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. – Wolfram Technology Conference – CUDA Certification: www.nvidia.com/certification – GPU Computing Webinars: www.nvidia.com/webinars – Training from EMPhotonics: www.emphotonics.com/services/cuda-training (To list an event, email: This e-mail address is being protected from spambots. You need JavaScript enabled to view it ) – See presentations and keynotes from GTC 2010: www.nvidia.com/gtc – See list of CUDA-enabled GPUs: www.nvidia.com/object/cuda_gpus.html – Download CUDA Toolkit 3.2: http://bit.ly/aKCENp – Developer guides and docs: http://developer.nvidia.com/object/gpucomputing.html – Learn more at http://research.nvidia.com/ – Read previous issues of CUDA: Week in Review: http://is.gd/cBXbg About CUDA 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 |




