CUDA: Week in Review
Tue., August 30, 2011, Issue #61 - Newsletter Home
Welcome to CUDA: Week in Review, an online news summary for the worldwide CUDA, GPU computing and parallel programming ecosystem.
Alexander Doronin, Univ. of Otago
GTC Asia Announced
GTC Worldwide Call for Submissions
Project Maximus Update
GPU Mini-Supercomputer for Every Scientist
MAGMA v1.0 Supports Tesla GPUs
Gaussian to Support GPU Acceleration
Sign up to be a CUDA Registered Developer
Follow @GPUComputing on Twitter
CUDA Spotlight
GPU-Accelerated Biophotonics & Biomedical Optics
This week’s spotlight is on Alexander Doronin, a PhD candidate in the Biophotonics & Biomedical Imaging Research Group at the University of Otago in New Zealand.

His research interests include biophotonics, light-tissue interaction, Monte Carlo (MC) computational modeling and parallel programming on GPUs using CUDA.
Alexander Doronin
NVIDIA: Alex, what is biophotonics?
Alex: Biophotonics refers to the interaction between biology and photonics. Photonics is a science that deals with the particle properties of light. A number of revolutionary applications have arisen in the field of photonics as a result of advancements in high technology and the miniaturization of solid-state optical/laser devices. A recent trend is the mapping of photonics technologies to the life sciences and medicine -- hence the term "biophotonics" was coined. It is a fast moving and very exciting area of research.
NVIDIA: What’s an example of an application that could benefit from biophotonics?
Alex: One example is cancer diagnostics. The current, most widely-used methodology for cancer diagnosis is histological analysis with microscopy. However, morphological variations (and especially morphological changes associated with early grades of cancer tissue) are difficult to resolve regarding what type or sub-type of cancer is present.

In our research, we are investigating the use of circular polarized light -- and the manipulation of the coherent properties of light -- to improve cancer diagnostics. The technique has the potential to revolutionize the ability to detect cancer at the very early stage.
NVIDIA: Tell us about the online Monte Carlo tool developed by your group.
Alex: With the rapid growth of the Internet, rich, browser-based applications have become more and more popular. Solutions such as Google Apps, Google Docs, online video sharing and gaming portals have become a large part of our everyday life.

Leveraging modern, web-based technology, we have created a free online MC computational tool for researchers in the area of biophotonics and biomedical optics. On the server side, the tool is accelerated by CUDA GPUs. On the client side, a lightweight, user-friendly web interface allows multiple clients to set up optical system parameters, perform modeling, and download results in a typical journal paper format.

We are currently extending our GPU cluster with additional M2090s and are expecting even more performance. The online MC tool is made available to the worldwide biophotonics community through the Biophotonics & Biomedical Imaging Research Group, which is headed up by my supervisor, Dr. Igor Meglinski.
  - Read the complete interview here

  (Would you like to be in the CUDA Spotlight? Email
CUDA Developer News
GTC Asia Announced back to the top
NVIDIA announced GTC Asia, the next major event in NVIDIA’s international series of GPU Technology Conference (GTC) events. GTC Asia will take place on Dec. 14-15, 2011 at the China National Convention Center in Beijing.
GTC Worldwide Call for Submissions
NVIDIA is now accepting poster proposals for the following events:
- GTC Express Live Theater @ SC11 (Nov. 12-18, 2011)
- GTC Asia 2011 (Dec. 14-15, 2011)
- GTC U.S. 2012 (May 14-17, 2012)

Project Maximus Update
NVIDIA’s ‘Project Maximus’ is an initiative to build a technology platform that enables workstation applications to take advantage of multi-GPU computing. By adding the computational power of a Tesla GPU with the advanced graphics capability of Quadro, users will be able to experience the highest level of productivity. Read what AnandTech’s Ryan Smith says about it:

A GPU Mini-Supercomputer for Every Scientist
The new GPU Starter Kit from HP is a pre-configured system that provides researchers with a ready-to-use GPU computing cluster, straight out of the box. It combines eight HP ProLiant SL390 G7 servers (containing 24 Tesla M2070 GPUs) with 16 CPUs. It is pre-configured with CUDA 4.0. For info, read Roy Kim’s recent blog on A GPU Mini-Supercomputer for Every Scientist or send an email to:

MAGMA v1.0 Supports Tesla GPUs
The Innovative Computing Laboratory (ICL) at University of Tennessee has released MAGMA v1.0 with support for NVIDIA Tesla GPUs. The MAGMA (Matrix Algebra for GPU and Multicore Architectures) Project aims to create a next generation of linear algebra libraries on heterogeneous systems. The ICL is directed by Dr. Jack Dongarra.

Gaussian to Support GPU Acceleration
NVIDIA, Gaussian, Inc., and The Portland Group (PGI) will develop a GPU-accelerated release of Gaussian, the quantum chemistry software app. Dr. Michael Frisch, president of Gaussian, said: "By coordinating the development of hardware, compiler technology and application software, the new app will bring the speed and cost-effectiveness of GPUs to the challenging problems and applications that Gaussian’s customers need to address."
Replays of the Week
A GPU Mini-Supercomputer for Every Scientist, by Roy Kim back to the top
Replays of the Week
NEW: Each week we highlight sessions from GTC 2010 and ISC 2011. Here are our picks for this week: back to the top
      Enabling On Demand Value-At-Risk for Financial Markets (GTC 10)
      Matthew Dixon – UC Davis and Jike Chong – Parasians

      Texture Unit in 3D Volume Reconstruction (ISC 2011)
      Karl Schwartz – Siemens AG
NEW: Dell is seeking a systems engineer for its HPC engineering team in Austin, TX. Experience with GPUs, CUDA and/or OpenCL required.
back to the top
If you are travelling to any of these locations, feel free to drop in to a GPU Meetup. Visitors are welcome.

- United States
        Boston GPU Meetup – Sept. 1, 6:00 pm
        New York GPU Meetup – (Special Meeting) September 8, 6:00 pm
        Silicon Valley GPU Meetup – Sept. 12, 6:15 pm
        New York GPU Meetup – Sept. 26, 6:00 pm
        Boston GPU Meetup – Oct. 6, 6:00 pm

- Australia
        Sydney GPU Meetup – Sept. 15, 6:00 pm
        Brisbane GPU Meetup – Sept. 15, 6:00 pm
CUDA Calendar
August 2011 back to the top
- In-Depth CUDA Training (Presented by Acceleware, with Microsoft)
Aug. 30-Sept. 2, 2011, Chicago, Illinois

- NEW: ANSYS Regional Conference
Aug. 30, 2011, Chicago, Illinois

- NEW: ANSYS Regional Conference
Aug. 31-Sept. 1, 2011, Houston, Texas
September 2011

- Advanced Numerical Methods on GPUs
Mini-symposium at ENUMATH 2011
Sept. 5-9, 2011, Univ. of Leicester, Leicester, UK

- NEW: GPU Direct and Unified Virtual Addressing (Webinar)
Sept. 6, 2011
Presented by Timothy Schroeder, NVIDIA

- Parallel Processing and Applied Mathematics (PPAM 2011)
Sept. 11-14, 2011, Torun, Poland
Note: Scientific Computing with GPUs tutorial, incl. session by Tim Schroeder, NVIDIA

- Geospatial Summit
Sept. 13-14, 2011, Herndon, Virginia

- Rapid Problem Solving Using Thrust (Webinar)
Sept. 14, 2011
Presented by Nathan Bell, NVIDIA
Note: Thrust is a library that enables programmers to develop high-performance applications on CUDA with minimal effort.

- CUDA Course (Presented by SagivTech)
Sept. 18-20, 2011, Ramat Gan, Israel
Hands-on sessions and optimization techniques.

- SEG (Society of Exploration Geophysicists) Annual Meeting
Sept. 18-23, 2011, San Antonio, Tex.

- CUDA Course (Presented by Tech-X)
Sept. 19-21, Boulder, Colorado

- Russian-German HPC School
Sept. 19-30, Novosibirsk

- SPIE Conference on High-Performance Computing in Remote Sensing
Sept. 19-22, 2011, Prague, Czech Republic

- NEW: CUDA Optimization: Memory Bandwidth Limited Kernels (Webinar)
Sept. 20, 2011
Presented by Timothy Schroeder, NVIDIA

- NEW: CUDA Optimization: Instruction Limited Kernels (Webinar)
Sept. 27, 2011
Presented by Gernot Ziegler, NVIDIA

- NEW: GPU-Accelerated Derivative Pricing Models
Sept. 27, 2011, New York
Presented by SciComp, NVIDIA, Dell, Microsoft

October 2011

- NEW: CUDA Optimization: Register Spilling and Local Memory Usage (Webinar)
Oct. 4, 2011
Presented by Paulius Micikevicius, NVIDIA

- NEW: GPU-Accelerated Derivative Pricing Models
Presented by SciComp, NVIDIA, Dell, Microsoft
Oct. 17, 2011, London, UK

November 2011

- NEW: Supercomputing 2011 (SC11)
Nov. 12-18, Seattle, Washington

(To list an event, email:

CUDA Resources
Downloads back to the top
– CUDA 4.0:
– Parallel Nsight:
– Parallel Nsight:
CUDA Registered Developer Program
– Sign up:
– List of CUDA-enabled GPUs:
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:
– Check out the NVIDIA Research page:
CUDA Recommended Reading
– Future of Computing Performance:
– Supercomputing for the Masses, Part 21:
– CUDA books:
CUDA Recommended Viewing
– The Third Pillar of Science:
– GTC 2010 presentations:
– SC10 presentations:
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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