CUDA: Week in Review
Tues., Dec. 7, 2010, Issue #43 - Newsletter Home
Welcome to CUDA: Week in Review, an online news summary for the worldwide CUDA and GPU computing community.
Industry Luminaries Talk About GPU Computing
At SC10, the premier supercomputing conference, NVIDIA hosted presentations by experts from a broad range of computational research areas, including Bill Dally (NVIDIA), Jack Dongarra (University of Tennessee), Satoshi Matsuoka and Takayuki Aoki (Tokyo Institute of Technology), and Jeff Vetter (Oak Ridge National Laboratory).
  - Download presentations here:

Achieving Excellence in 2010
Tech analyst Rob Enderle reflects on 2010, writing: "As the end of the year nears, it’s time to look back at the firms that set positive examples of how to do things right in the technology market. Each of these companies stood out for excellence either in marketing, products or services."
  - See list:
GPU Computing with .NET
TidePowerd recently released a solution called GPU.NET, which integrates GPU computing support for .NET languages like C# (the .NET framework is a Microsoft programming model). Now you can write GPU kernels in C# and call them like any other .NET-based methods. TidePowerd CEO and co-founder Jack Pappas will present a live webinar about GPU.NET on Wed., Dec. 15 at 9:00 a.m. pacific.
  - Sign up for webinar:
  - Download the beta:
  - Discuss on the forums:

LIBJACKET: Fast GPU Software Library
AccelerEyes introduced LIBJACKET, a broad and fast C/C++ library for GPU computing. With over 500 C/C++ functions, LIBJACKET represents the largest GPU computing library in the world. This library integrates seamlessly in any application, enabling optimized utilization of CUDA-capable GPUs. LIBJACKET is currently a free beta product.
  - See:

Affordable Voice Search: One Step Closer
Last summer we interviewed Ben Jiang, CEO of startup Nexiwave, who told us about using GPUs and CUDA to accelerate voice search in large volumes of multimedia content. We recently learned that Nexiwave has entered into a partnership with UbiCast, a webcast company based in France.
  - Read more in the NVIDIA blog:

NEW: Each week we will highlight a session from GTC 2010. Here’s our pick for this week:
  - Mathematica for GPU Programming
    Presented by Ulises Cervantes-Pimentel, Wolfram Research (30 mins.)

December 2010

NEW: CUDA 3.2 Toolkit and SDK Update - Webinar
Dec. 9, 9:00 a.m. pacific

CUDA and Advanced Image Processing - SagivTech
Dec. 12-14, Ramat Gan, Israel

UK GPU Computing Conference - Univ. of Cambridge
Dec. 13-14, Cambridge, UK

NEW: Introduction to GPU.NET - Webinar
Dec. 15, 9:00 a.m. pacific

Dec. 16-18, Seoul

NEW: CUDA Workshop - SIGGRAPH Asia
Dec. 16, 9:00 a.m., Room 317B/C, Coex Convention & Exhibition Center, Seoul
Note: Open to all attendees. Presented in English, translated simultaneously to Korean

NEW: Tutorials on GPU Programming - HiPC 2010
Dec. 19-22, Goa, India


Scientific Computing in the Americas: The Challenge of Massive Parallelism
Jan. 3-14, 2011, Valparaiso, Chile

IEEE International Parallel & Distributed Processing Symposium
May 16-20, 2011, Anchorage

Intelligent Vehicles Conference - IEEE
June 5-9, 2011, Baden-Baden, Germany

Internat'l. Conference on Computer Systems and Applications
June 27-30, 2011, Sharm El-Sheikh, Egypt

– CUDA Certification:
– GPU Computing Webinars:
– Training from EMPhotonics:

(To list an event, email:

GPU Technology Conference
– See presentations and keynotes from GTC 2010:
– See list of CUDA-enabled GPUs:
CUDA and Parallel Nsight Overview
– See blog post and video:
CUDA Downloads
– Download CUDA Toolkit 3.2:
– Download OpenCL v1.1 pre-release drivers and SDK code samples (Log in or
   apply for an account
– Get developer guides and docs:
CUDA and Academia
– Learn more at
CUDA on the Web
– See previous issues of CUDA: Week in Review:
– Follow CUDA & GPU Computing on Twitter:
– Network with other developers:
– Stayed tuned to GPGPU news and events:
– Learn more about CUDA on CUDA Zone:
CUDA Recommended Reading
– Read Kudos for CUDA:
– Read Supercomputing for the Masses, Part 20:
– Read CUDA books:
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. Send comments and suggestions to:
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