Share:   Facebook Twitter Linked-in Google Reddit Stumbleupon email
CUDA Week in Review Newsletter
Thurs., Jan. 30, Issue #106 Newsletter Home
Welcome to CUDA: Week In Review, news and resources for the worldwide parallel programming community. (Please fill out our reader survey so we can improve in 2014. Thanks!)
CUDA Pro Tip: In CUDA 5.5, a new racecheck analysis mode presents a more human-readable analysis of your code, even reporting which source lines conflict with other lines. Learn more at Parallel Forall.
GPU TECHNOLOGY CONFERENCE

GPU TECHNOLOGY CONFERENCE Register today for GTC 2014!
The GPU Tech Conference (March 24-27) will feature 500 sessions, tutorials, labs and opportunities for interaction with experts and peers.
Registration (20% discount code: GM20CD)
Call for posters (open through Jan. 31)

CUDA SPOTLIGHT
Todd MartinezCUDA-Accelerated Quantum Chemistry
This week’s Spotlight features Professor Todd Martinez of Stanford. His research lies in the area of theoretical chemistry, emphasizing development of new methods which accurately capture quantum mechanical effects. These effects are crucial in understanding chemical bonding, molecular transformations and reactions involving light. Read the Spotlight.

CUDA NEWS
Bin ZhouNew CUDA Fellow
Bin Zhou is an adjunct research professor at the University of Science and Technology of China (USTC), where he established a CUDA Teaching Center and trained 500+ developers and students in CUDA programming. Read the announcement.

New Beta from Mellanox
Mellanox announced the GPUDirect RDMA Beta. This new technology provides a significant decrease in GPU-GPU communication latency and completely offloads the CPU, removing it from GPU-GPU communications across the network. Melanox is a supplier of high-performance, end-to-end interconnect solutions.

New Licensing from ANSYS
ANSYS, a provider of engineering simulation products, updated its HPC/GPU licensing with ANSYS 15.0 to enable users to more easily take advantage of both CPUs and GPUs in ANSYS Mechanical and ANSYS Fluent simulations.

InsideHPC Interview with Rob Farber
In this podcast, Rob Farber and Rich Brueckner discuss NVIDIA Tegra K1 and the future of HPC

CUDA TRAINING AND EDUCATION

 back to the top
Need CUDA training or advice? See list of worldwide CUDA trainers and consultants.
Want to learn about parallel programming? Sign up for Udacity CS344.

UPCOMING GPU WEBINARS

 back to the top
Jan. 30: Debugging CUDA Fortran using Allinea, B. Paisley, Allinea
Feb. 5: OpenMM - Accelerating and Customizing MD Simulations on GPUs, V. Pande, Stanford
Feb. 25: GPUs for Visualization and Analysis of MD Simulations with VMD, J. Stone, Univ. of Illinois

UPCOMING GPU MEETUPS

 back to the top
Feb. 1: Minneapolis
Feb. 19: Singapore
Feb. 24: Silicon Valley
Note: New GPU Meetups have launched in Russia and Norway.

NEW ON THE BLOG

 back to the top
Subscribe to the Parallel Forall RSS feed Parallel Forall:
CUDA Pro Tip: Control GPU Visibility with CUDA_VISIBLE_DEVICES, by Mark Harris
The Saint on Porting C++ Classes to CUDA with Unified Memory, by Mark Harris
Register for GTC 2014 Now, by Mark Harris
CUDACasts Episode 14: Racecheck Analysis with CUDA 5.5, by Mark Ebersole
Subscribe to NVIDIA RSS feed NVIDIA:
Applications Accelerated by World's Most Powerful Graphics Chip, by Roy Kim
ILM Gets 25th Scientific and Technical Achievement Award, by Greg Estes
NVIDIA Names Bin Zhou as Newest CUDA Fellow, by Chandra Cheij

CUDA CALENDAR

 back to the top

2014


Stanford Conference and Exascale Workshop 2014
  Feb. 3-5, 2014, Stanford, Calif.
Sponsored by HPC Advisory Council

CUDA and OpenACC Training (Univ. of Madrid)
  Feb. 12-13, 2014, Madrid, Spain

GPU Programming and Applications Workshop (IIT Bombay)
  Feb. 24-26, 2014, Mumbai, India

4-Day CUDA Course (Acceleware)
  Feb. 25-28, 2014, Baltimore, Maryland

ASPLOS 2104
  March 1-5, 2014, Salt Lake City, Utah

GPU Technology Conference (GTC 2014)
  March 24-27, 2014, San Jose, Calif.
500 sessions | Hands-on developer labs & tutorials
Meet with luminaries, technologists and peers from 50+ countries

4-Day CUDA Course (Acceleware)
  May 6-9, 2014, Calgary, AB, Canada

IEEE Int’l Parallel & Distributed Processing Symposium
  May 19-23, 2014, Phoenix, Arizona

Programming Heterogeneous Systems in Physics (Workshop)
  July 14-15, 2014, Jena, Germany

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

CUDA RESOURCES

 back to the top

Online Learning
Udacity | Coursera

Online CUDA Course in Russian
Try out this new course designed for Russian speakers.

GPU Test Drive
Want to try Tesla K20 for free? Sign up here.

CUDACasts
Check out our new series of short videos about CUDA.

Tell Us Your CUDA Story
If you are a CUDA developer, tell us how you are using CUDA. Your submission will be considered for display on the NVIDIA website.

GPU-Accelerated Apps
See updated list of 240+ GPU-accelerated applications.

GPU Meetups
Learn about Meetups in your city, or start one up.

CUDA Documentation
The new CUDA documentation site includes release notes, programming guides, manuals and code samples.

NVIDIA Developer Forums
Join us on the NVIDIA DevTalk forums to share your experience and learn from other developers. You can also ask questions on Stack Overflow, using the ’cuda’ tag.

CUDA Consulting
Training, programming and project development services are available from CUDA consultants around the world. To be considered for inclusion on list, email: cuda_week_in_review@nvidia.com.

GPU Computing on Twitter
For daily updates about GPU computing and parallel programming, follow @gpucomputing on Twitter.

Downloads
CUDA 5
Nsight

CUDA on the Web
CUDA Spotlights
CUDA Newsletters
CUDA Zone
GPU Test Drive
GPGPU.org

NVIDIA Newsletters
Sign up for NVIDIA Newsletters, including Media & Entertainment, GeForce, NVIDIA GRID VDI and Shield.

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 to cuda_week_in_review@nvidia.com
Copyright © 2014 NVIDIA Corporation. All rights reserved. 2701 San Tomas Expressway, Santa Clara, CA 95050.