CUDA: Week in Review
Friday, April 9, 2010, Issue #16 - Newsletter Home  
Welcome to this week’s issue of "CUDA: Week in Review," a weekly newsletter for the worldwide CUDA and GPU Computing community. Contact us at:
Italian Supercomputing Center Improves Flexibility, Usability
CASPUR, a computing consortium in Rome, manages a high-powered processing center open to the Italian national scientific community. Researchers in biology, chemistry, medicine, mathematics, and materials science use the center’s high performance computing (HPC) clusters to run simulations and process large amounts of data. To improve the usability of the center, CASPUR adopted a pilot cluster that utilizes NVIDIA Tesla GPUs and CUDA C running on the Windows HPC Server 2008 operating system. In tests, CASPUR found that the cluster’s performance exceeded that of previous systems. "We noted performance from 10 to more than 100 times greater than that of single-processor systems," comments Nico Sanna, Senior Technology Manager, CASPUR. See Microsoft case study:
Tokyo Institute of Technology Selected as a CUDA Center of Excellence
Tokyo Institute of Technology (Tokyo Tech) has been named Japan’s first CUDA Center of Excellence in recognition of its pioneering activities in parallel computing. Tokyo Tech is the 10th CUDA Center of Excellence, joining other institutions including Cambridge University, Chinese Academy of Sciences, Harvard University, National Taiwan University, Tsinghua University, University of Illinois at Urbana-Champaign, University of Maryland, University of Tennessee, and University of Utah. Tokyo Tech GSIC (Global Scientific and Information Computing Center) was the first supercomputing center to achieve a Top 500 ranking using GPUs. The Tokyo Tech TSUBAME 1.2 supercomputer uses 170 NVIDIA Tesla S1070 computing systems. For more info, see:
New on CUDA Zone: GPU-based Framework for Simulating Cortically-Organized Networks
Extract: "Computational models whose organization is inspired by the cortex are increasing in both number and popularity…. These models present two practical challenges. First, they are computationally intensive. Second, while the operations performed by individual cells are typically simple, the code needed to keep track of network connectivity can quickly become complicated…. We have created a programming framework called CNS (Cortical Network Simulator). CNS models are automatically compiled and run on a GPU, typically 80-100X faster than on a single CPU…. Authors: J. Mutch, U. Knoblich, T. Poggio, Center for Biological & Computational Learning, McGovern Institute for Brain Research, MIT.

Background on MIT’s Center for Biological & Computational Learning: "CBCL was founded with the belief that learning is at the very core of the problem of intelligence, both biological and artificial, and is the gateway to understanding how the human brain works and to making intelligent machines. CBCL studies the problem of learning within a multidisciplinary approach. Its main goal is to nurture serious research on the mathematics, the engineering, and the neuroscience of learning." See: and
CUDA Zone Submissions
Have a CUDA-related paper, research, or application? Show it on CUDA Zone:
Walt Disney Animation Studios seeks a senior development software engineer to join the team at the Burbank, Calif. studio. Responsibilities include: Re-engineer applications and libraries to leverage parallelism of emerging massive multicores; Be an evangelist for multicore computing throughout the organization. Requirements include: Practical experience with C++ or C; Experience with programming on the GPU using OpenGL, OpenCL, CUDA; Strong mathematical fundamentals, including linear algebra and numerical methods.
– See posting here:
– See more CUDA/GPU computing jobs here:
CUDA Education
GTC 2010: Call for Submissions Now Open
The GPU Technology Conference (GTC) 2010 will be held Sept. 20-23, 2010 in San Jose, Calif. Developers, researchers, scientists, and entrepreneurs are invited to submit proposals on topics related to the burgeoning GPU ecosystem. See:
Industry Event: Visual Studio Launch Conference
On April 12, Microsoft will launch Visual Studio 2010 and Silverlight 4 at the Microsoft Visual Studio Launch Conference, Las Vegas. NVIDIA will be on hand to demonstrate NVIDIA Parallel Nsight. See:
Seminar: GPU Computing in the Oil & Gas Industry
On May 12, Microsoft and NVIDIA will team up to offer a seminar/workshop for application programmers in the oil & gas. To register, visit:
GPGPU Conferences and Symposia
– Symposium on Applications of GPUs in Chemistry and Materials Science, June 28-30,
   University of Pittsburgh:
– Parallel Symbolic Computation 2010 (PASCO), July 21-23, France:
– Symposium on Chemical Computations on GPGPUs, Aug. 22-26, Boston:
– Workshop on UnConventional High Performance Computing 2010 (UCHPC 2010),
   Aug. 31-Sept. 1, Naples, Italy (with Euro-Par 2010):
Acceleware-Certified CUDA Training
Calgary, April 12-16:
Silicon Valley, May 19-20:
GPU Computing Webinars (CUDA C, OpenCL, Parallel Nsight and more…)
See schedule:
CUDA and GPU Computing Courses
Over 320 universities are teaching CUDA and GPU Computing courses. See the list:
CUDA Books
"Programming Massively Parallel Processors," by D. Kirk and W. Hwu. Available on
– NEW: NVIDIA Performance Primitives (NPP) library now available for CUDA Toolkit 3.0:
– Download CUDA Toolkit 3.0:
– Download Developer Guides:
– 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 on YouTube:
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.

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