Welcome to CUDA: WEEK IN REVIEW, a news summary for the worldwide CUDA, GPGPU and parallel programming community. |
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CUDA SPOTLIGHT | |||||||||||||||||
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CUDA NEWS | |||||||||||||||||
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GPU THESIS WATCH | |||||||||||||||||
Title: Scalable GPU Acceleration of B-Spline Signal Processing Operations Author: Alexander Karantza, Rochester Institute of Technology Advisor: Dr. Sonia Lopez Alarcon URL: https://ritdml.rit.edu/handle/ | |||||||||||||||||
CUDA JOB OF THE WEEK | |||||||||||||||||
HGST, a Western Digital Company, seeks a researcher in the area of magnetic recording heads. Candidate should have expertise in analytical and numerical modeling of nano-structured devices using micromagnetic, electron and spin-transport, thermal, and/or optical modeling. Desired skills: Ph.D.in Physics or EE; MPI, OpenMP, and/or CUDA experience. Job #6366. Contact: hgstcareers (at) hitachigst.com | |||||||||||||||||
FROM THE BLOGOSPHERE | back to the top | ||||||||||||||||
New on the NVIDIA blog: How NVIDIA Gave Film Makers Early Look at Skyfall, by Joachim Zell, EFILM How GPUs Accelerate Innovation, by Liza Gabrielson Four Amazing Things Carnegie Mellon is Doing, by Chandra Cheij Beyond Seeing Through Walls to Real-Time Body Scanning, by Bob Sherbin New on the Parallel Forall blog: Performance Metrics in CUDA Fortran, by Greg Ruetsch An Easy Introduction to CUDA C and C++, by Mark Harris An Easy Introduction to CUDA Fortran, by Greg Ruetsch Do More, Code Less with ArrayFire GPU Matrix Library, by Chris McClanahan, AccelerEyes (Subscribe to the Parallel Forall RSS feed) | |||||||||||||||||
CUDA TECH TIP | back to the top | ||||||||||||||||
Output from a GPU Kernel with printf(): When debugging code or outputting results, the first go-to for any programmer is usually C’s trusty printf() command. Did you know that CUDA allows printf() directly from a GPU kernel? All the usual format specifiers are supported, and every thread can call printf() independently. If you only want to output something once, however, then you must conditionally choose a thread. The following example shows how it works: | |||||||||||||||||
__global__ void helloCUDA() { if(threadIdx.x == 0) printf("Hello CUDA from...\n"); // Only thread 0 will print this printf("Thread %d\n", threadIdx.x); // Every thread will print this } | |||||||||||||||||
Note that printf() in device code requires a GPU with Compute Capability 2.0 or later. | |||||||||||||||||
(Thank you to Mark Harris for this Tech Tip. Have one you’d like to share? Email: cuda_week_in_review@nvidia.com | |||||||||||||||||
GPU MEETUPS | back to the top | ||||||||||||||||
Meetup Momentum: Congrats to the brand new GPU Meetup in Minneapolis, Minn., led by Kirk Dybvik. The New York GPU Meetup, led by Andrew "Shep" Sheppard, now has over 800 members. The Silicon Valley GPU Meetup, led by Jike Chong, has over 500 members. The Boston GPU Meetup, led by Eliot Eshelman, has over 250 members. Find a GPU Meetup in your location, or start one up. Upcoming meetings include: Paris, Nov. 13 Brisbane, Nov. 22 New York, Nov. 29 Silicon Valley, Dec. 3 | |||||||||||||||||
CUDA CALENDAR | back to the top | ||||||||||||||||
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CUDA RESOURCES | |||||||||||||||||
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ABOUT CUDA | |||||||||||||||||
CUDA® is a parallel computing platform and programming model invented by NVIDIA. It enables dramatic increases in computing performance by harnessing the power of the graphics processing unit (GPU). NVIDIA provides a complete toolkit for programming on the CUDA architecture, supporting standard computing languages such as C, C++ and Fortran. Send comments and suggestions on the newsletter to cuda_week_in_review@nvidia.com | |||||||||||||||||
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