NVIDIA today announced the release of NVIDIA Parallel Nsight software, the industry’s first development environment for GPU-accelerated applications that work with Microsoft Visual Studio. “By adding functionality specifically for GPU Computing developers, Parallel Nsight makes the power of the GPU more accessible than ever before,” said Sanford Russell, GM of GPU Computing at NVIDIA. NVIDIA Parallel NSight features a CUDA C/C++ debugger and application performance analyzer, and a graphics debugger and inspector. NVIDIA Parallel Nsight supports Windows HPC Server 2008, Windows 7 and Windows Vista. Download Parallel Nsight here.
OPENMM was designed to enhance the performance of almost any molecular dynamics simulation package (MD package) by allowing the code to be executed on high performance computer architectures, in particular Graphics Processing Units (GPUs). Most molecular dynamics packages can be modified to call OPENMM, resulting in significant acceleration on such high performance architectures, without changing the way users interact with the MD package. Read the rest of this entry »
EM Photonics announced today the general availability of CULA 2.0, its GPU-accelerated linear algebra library. The new version provides support for NVIDIA GPUs based on the latest “Fermi” architecture.
CULA contains a LAPACK interface comprised of over 150 mathematical routines from the industry standard for computational linear algebra, LAPACK. EM Photonics’ CULA library includes many popular routines including system solvers, least squares solvers, orthogonal factorizations, eigenvalue routines, and singular value decompositions. CULA offers performance up to a magnitude faster than highly optimized CPU-based linear algebra solvers. There is a variety of different interfaces available to integrate directly into your existing code. Programmers can easily call GPU-accelerated CULA from their C/C++, FORTRAN, MATLAB, or Python codes. This can all be done with no GPU programming experience. CULA is available for every system equipped with GPUs based on the NVIDIA CUDA architecture. This includes 32- and 64-bit versions of Linux, Windows, and OS X.
More information is available at www.culatools.com.
- Using platform and device layers to build robust OpenCL™ applications
- Program compilation and kernel objects
- Managing buffers
- Kernel execution
- Kernel programming – basics
- Kernel programming – synchronization
- Matrix multiply – a case study
- Kernel programming – built-ins
Graphic Remedy is proud to announce the release of gDEBugger Version 5.6 for Windows, Linux, Mac OS X, iPhone and iPad. This version introduces iPhone and iPad on-device debugging and profiling abilities, letting developers optimize their apps in real-time on actual iPhone and iPad hardware, while viewing invaluable inside information such as the device’s GPU, CPU, graphics driver and operating system performance counters.
gDEBugger is an OpenGL, OpenGL ES and OpenCL debugger and profiler that traces application activity on top of the OpenGL API, and lets programmers see what is happening within the graphics system implementation to find bugs and optimize OpenGL application performance. gDEBugger runs on Windows, Mac OS X, iPhone and Linux operating systems.
For our Australian readers interested in GPU computing. Next week there will be two free workshops on GPU Computing with CUDA. The workshops will both include a tutorial on CUDA C/C++ programming along with additional presentations by local speakers. Topics will include an overview of NVIDIA Tesla and the latest Fermi architecture GPUs, CUDA programming, debugging and profiling tools, and optimization strategies.
- “High-Performance GPU Computing with NVIDIA CUDA”
Wednesday, July 14
8:45 – 14:00
The University of New South Wales, Sydney
- “High-Performance GPU Computing with NVIDIA CUDA and Fermi”
Thursday, July 15
9:15 – 15:30
The Australian National University, Canberra
Follow the links above for full details. Space is limited, so be sure to RSVP to the addresses provided.
SagivTech plans to offer a 3-days course that deals with Image Processing with CUDA in the USA this September. This is an advanced course that is intended for experienced CUDA developers looking for optimization methods for image processing applications implemented on NVIDIA GPUs.
The course will be held in the San Francisco area, 9am to 5pm September 27-29.
The OpenCL 1.1 specification, including header files and documentation, has been released. It includes significant new functionality:
- Host-thread safety, enabling OpenCL commands to be enqueued from multiple host threads
- Sub-buffer objects to distribute regions of a buffer across multiple OpenCL devices
- User events to enable enqueued OpenCL commands to wait on external events
- Event callbacks that can be used to enqueue new OpenCL commands based on event state changes in a non-blocking manner
- 3-component vector data types
- Global work-offset which enable kernels to operate on different portions of the NDRange
- Memory object destructor callback
- Read, write and copy a 1D, 2D or 3D rectangular region of a buffer object
- Mirrored repeat addressing mode and additional image formats
- New OpenCL C built-in functions such as integer clamp, shuffle and asynchronous strided copies
- Improved OpenGL interoperability through efficient sharing of images and buffers by linking OpenCL event objects to OpenGL fence sync objects
- Optional features in OpenCL 1.0 have been bought into core OpenCL 1.1 including: writes to a pointer of bytes or shorts from a kernel, and conversion of atomics to 32-bit integers in local or global memory
The Theoretical and Computational Biophysics Group, NIH Resource for Macromolecular Modeling and Bioinformatics (www.ks.uiuc.edu) at the University of Illinois at Urbana-Champaign, presents a Workshop on GPU Programming for Molecular Modeling to be held August 6-8, 2010, at the Beckman Institute for Advanced Science and Technology, on the University of Illinois campus in Urbana, Illinois, USA. Application, selection, and notification of participants is on-going through July 29, 2010.
Note: Participants are encouraged to attend the multi-site “Proven Algorithmic Techniques for Many-core Processors” workshop the preceding week (August 2-6) at the location of their choice. Registration for this workshop is required for participants without equivalent GPU-programming training or experience.
OpenCurrent version 1.1.0 has been released. OpenCurrent is a library for solving certains types of PDEs over 3D cartesian grids. It supports single and double precision, and includes solvers for Poisson equations, diffusion, and incompressible Navier-Stokes.
- Multi-GPU communication library
- Multi-GPU versions of Multigrid solver, Incompressible Navier-Stokes solver, and more
- NetCDF support now optional
- Support for Fermi/CUDA 3.0
- Numerous bug fixes and enhancements
Get it here: http://code.google.com/p/opencurrent/downloads/list