NVIDIA GF100 GPU Fermi Architecture

http://benchmarkreviews.com/index.php?option=com_content&task=view&id=1885&Itemid=47

http://benchmarkreviews.com/index.php?option=com_content&task=view&id=440&Itemid=23

NVIDIA Corporation (Nasdaq: NVDA) today unveiled the Tesla 20-series of parallel processors for the high performance computing (HPC) market, based on its new generation CUDA(TM) processor architecture, codenamed “Fermi”.

Designed from the ground-up for parallel computing, the NVIDIA Tesla 20-series GPUs slash the cost of computing by delivering the same performance of a traditional CPU-based cluster at one-tenth the cost and one-twentieth the power.

The Tesla 20-series introduces features that enable many new applications to perform dramatically faster using GPU Computing. These include ray tracing, 3D cloud computing, video encoding, database search, data analytics, computer-aided engineering and virus scanning.

NVIDIA Launches Community Website Aimed at Biotech

http://www.genomeweb.com/blog/nvidia-launches-community-website-aimed-biotech

Today NVIDIA is singing from the rooftops about its new “Tesla Bio Workbench,” a community website aimed at spreading the GPU gospel to the life sciences community. Included in the site are links to resources for GPU computing, discussion forums, and a slew of freely available, CUDA-enabled GPU software. Currently, the site offers the following MD and quantum Chemistry applications for use of NIVIDIA cards:

AMBER
GROMACS
HOOMD
LAMMPS
NAMD
TeraChem (QC)
VMD

Coming soon are GROMOS, GPU-HMMER, MUMmerGPU, and CUDA-SmithWaterman. Of note here is NVIDIA’s attempt to show off its stuff with standard bioinformatics algorithms for sequence analysis, which are not usually thought of as benefiting from being ported to a graphics processor.

CUDA support on Netbook

http://www.liliputing.com/2009/12/intel-calls-nvidia-ion-overkill-for-netbooks.html

NVIDIA’s ION platform combines an Atom processor with NVIDIA GeForce graphics. The result is a computer platform that gives you notebooks and desktops with low power processors and the ability to handle 1080p HD video playback, Blu-Ray decoding, and a fair amount of 3D graphics processing for modern video games.

gpucomputing.net

I just saw this website.

http://gpucomputing.net/

There is not much there yet. A competing website to gpgpu.org?

Multi-core and Many-core

http://hi.baidu.com/liquidrainbow/blog/item/8b3db82a01f9f2f0e7cd404b.html

Interesting article about multi-core and many-core (in Chinese).

nVidia GPU Computing tools

I saw this from CNN: http://money.cnn.com/news/newsfeeds/articles/marketwire/0559840.htm

Rich Standards-Based Tools and Libraries Develop Around CUDA Architecture

CUDA Toolkit 3.0 Beta: With the CUDA Toolkit 3.0 Beta, developers can start developing applications today for the NVIDIA Fermi architecture. This beta release includes features such as ECC reporting, Dual DMA Engine, Concurrent Kernel Execution and NVIDIA Fermi HW debugging support in cuda-gdb. Performance profiling is included for both CUDA Visual Profiler and the OpenCL Visual Profiler. Also included is support for a new unified interoperability API for Direct3D and OpenGL including Direct3D 11.

OpenCL 1.0 Extensions: NVIDIA is the only vendor supporting OpenCL features beyond the minimum conformance level. New extensions released by NVIDIA include support for double precision, OpenGL interoperability and the new OpenCL Installable Client Device (ICD). These new features supplement existing NVIDIA-only support for 2D image, 32-bit atomics and byte addressable stores.

NVIDIA “Nexus,” the codename for the industry’s first development environment for massively parallel GPU applications, integrated into Microsoft Visual Studio IDE: Comprised of a Debugger, Performance Analyzer and Graphics Inspector, this beta release gives GPU Computing developers an immediate boost in productivity through common and easy to use tools.

The Portland Group (PGI) — CUDA Fortran: Production release of the world’s first Fortran compiler compatible with the NVIDIA CUDA-enabled GPUs. CUDA Fortran will accelerate the adoption of GPU Computing in areas where applications are written in Fortran, such as ocean modeling, weather forecasting, environmental modeling, seismic analysis, bioinformatics and other areas.

Professional HPC Debugging Solutions from Allinea and TotalView were also launched this week. These tools provide CUDA GPU features that complement existing capabilities for parallel debugging using MPI, OpenMP and pthreads on the Linux platform. It enables developers to debug applications that are running on hybrid clusters of x86-64 CPUs and Tesla GPU-based servers.

Numerical Analysis Packages: Significant advances in the use of CUDA-enabled GPUs have also been made in prominent numerical analysis and mathematical modeling packages such as MATLAB from Mathworks, Mathematica from Wolfram Research and LabVIEW from National Instruments.

CUDA Libraries: In addition, developers can take advantage of a rich set of CUDA-accelerated libraries available from NVIDIA and its partners including BLAS, FFT, LAPACK (EM Photonics CULA), MAGMA (ICL at the UTK), NVIDIA Performance Primitives (NPP), CUDA Vision Workbench (CVWB) and video and image processing libraries.

GPUGrid.net

Today I saw this GPU grid computing for computational molecular biology website. It is very interesting.

http://www.gpugrid.net/index.php

ORNL’s Jaguar Named World’s Most Powerful Supercomputer

I saw this news but I am wondering why it is not using nVidia GPU. I suspect next year will see a Fermi-based super computer.

 

http://news.download3000.com/ornls-jaguar-named-worlds-most-powerful-supercomputer/

According to the TOP500 Organization that publishes the list of the top supercomputers, the Oak Bridge National Laboratory, or ORNL, has the world’s most powerful supercomputer model based on GPU. The powerful complex system is known as the Jaguar, or Cray XT5, features a quarter million cores powered by the ATI Radeon RV770 technology. Using the six-core AMD Opteron processor, Jaguar enables 2.3 petaflop/s peak performance, as well as 1.75 petaflop/s performance, according to the Linpack benchmark.

AMD technologies also power the fifth high-performance supercomputer system called Tianhe-1, featuring the ATI Stream technology and 563.1 teraflop/s performance at 5,120 ATI graphic processing units in the RV770 architecture. It is used in China, while the Roadrunner with dual-CPU and AMD Opreton processors is the former number one supercomputer system.

SHIMMER and BioMOBIUS: A Health Research Platform

http://www.ddj.com/embedded/221700058

The combination of the BioMOBIUS and SHIMMER platforms lets researchers rapidly develop research tools — and open source is the key.

 

VMD 1.8.7, Now with CUDA Acceleration

http://www.vizworld.com/2009/08/vmd-1-8-7-now-with-cuda-acceleration/?utm_source=footer&utm_medium=relatedlinks&utm_campaign=layout

One of the key advancements included in VMD 1.8.7 is support for GPU accelerated visualization and analysis, based on NVIDIA CUDA. As reported in several publications, the massively parallel architecture of GPUs makes them ideal devices to accelerate many of the computationally demanding calculations in VMD. The range of acceleration provided by GPUs depends on the capabilities of the specific GPU devices installed, and the details of the calculation. Typical acceleration factors for the algorithms in VMD are: electrostatics 22x to 44x, implicit ligand sampling 20x to 30x, molecular orbital calculation 100x to 120x. Details on making best use of the GPU acceleration capabilities in VMD are provided here.