Accelerating Power Flow studies on Graphics Processing Unit

March 29th, 2011

Abstract:

In this paper, we present the design of Power Flow algorithm that has enhanced performance on the Graphics Processing Unit (GPU) using Compute Unified Device Architecture (CUDA). This work investigates the performance of optimized CPU versions of Newton-Raphson (Polar form) and Gauss-Jacobi power flow algorithms, highlights the approach used to reduce the computation time by performing these studies on massively parallel GPU cores. Simulations results demonstrate the significant acceleration of the GPU version compared to its CPU variant, thus reducing processing time making them suitable for real-time online dispatching purposes.

(Singh, J. and Aruni, I.: “Accelerating Power Flow studies on Graphics Processing Unit”, Proceedings of the Annual IEEE India Conference 2010 (INDICON), pp 1-5, Dec. 2010. [DOI])

AMD Fusion Developer Summit

March 29th, 2011

Heterogeneous computing is moving into the mainstream, and a broader range of applications are already on the way. As the provider of world-class CPUs, GPUs, and APUs, AMD offers unique insight into these technologies and how they interoperate. We’ve been working with industry and academia partners to help advance real-world use of these technologies, and to understand the opportunities that lie ahead. It’s time to share what we’ve learned so far.

With tutorials, hands-on labs, and sessions that span a range of topics from HPC to multimedia, you’ll have the opportunity to expand your view of what heterogeneous computing currently offers and where it is going. You’ll hear from industry innovators and academic pioneers who are exploring different ways of approaching problems, and utilizing new paradigms in computing to help identify solutions. You’ll meet AMD experts with deep knowledge of hardware architectures and the software techniques that best leverage those platforms. And you’ll connect with other software professionals who share your passion for the future of technology.

Learn more at developer.amd.com/afds.

CFP: First International Workshop on Accelerator Architectures for the Masses (WACy 2011)

March 29th, 2011

The First International Workshop on Accelerators Architectures for the Masses (WACy 2011) will be held in conjunction with 25th Int’l. Conference on Supercomputing (ICS 2011), on June 4th 2011. The submission of short papers (approximately ~6 pages) is encouraged. This workshop is organized by Arrvindh Shriraman and Tor Aamodt, the submission deadline is April 15th 11:59pm PST. More information is available at http://wacy.cs.sfu.ca.

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Multicore/Multi-GPU Accelerated Simulations of Multiphase Compressible Flows Using Wavelet Adapted Grids

March 29th, 2011

Abstract:

We present a computational method of coupling average interpolating wavelets with high-order finite volume schemes and its implementation on heterogeneous computer architectures for the simulation of multiphase compressible flows. The method is implemented to take advantage of the parallel computing capabilities of emerging heterogeneous multicore/multi-GPU architectures. A highly efficient parallel implementation is achieved by introducing the concept of wavelet blocks, exploiting the task-based parallelism for CPU cores, and by managing asynchronously an array of GPUs by means of OpenCL. We investigate the comparative accuracy of the GPU and CPU based simulations and analyze their discrepancy for two-dimensional simulations of shock-bubble interaction and Richtmeyer–Meshkov instability. The results indicate that the accuracy of the GPU/CPU heterogeneous solver is competitive with the one that uses exclusively the CPU cores. We report the performance improvements by employing up to 12 cores and 6 GPUs compared to the single-core execution. For the simulation of the shock-bubble interaction at Mach 3 with two million grid points, we observe a 100-fold speedup for the heterogeneous part and an overall speedup of 34.

(Rossinelli D., Hejazialhosseini B., Spampinato D., Koumoutsakos P.: “Multicore/Multi-GPU Accelerated Simulations of Multiphase Compressible Flows Using Wavelet Adapted Grids”, SIAM Journal of Scientific Computing 33:512-540, 2011 [DOI])

GTC 2011 Call for submissions

March 22nd, 2011

The call for Submissions for GPU Technology Conference 2011 (GTC), October 11-14, is now open.  You can find more details and instructions for submitting here.

Expanding the already comprehensive breadth of topics covered at GTC 2010, the GTC Content Committee has added new topic areas for 2011. Below is a partial list; see the GTC website for full details:

  • Application Design & Porting Techniques
  • Bioinformatics
  • Climate & Weather Modeling
  • Cluster Management
  • Computational Structural Mechanics
  • Parallel Programming Languages
  • Supercomputing

GTC is also looking for posters that describe novel or interesting research topics in parallel computing, visual computing, and applications of GPUs, with a particular interest in submissions describing GPU computing and CUDA applications that solve diverse problems in scientific and engineering domains. Read the rest of this entry »

CUDAfy – GPGPU completely in .NET

March 21st, 2011

From a recent press release:

CUDAfy is a .NET SDK that allows you to write, debug and emulate CUDA GPU applications in any .NET language including C# or Visual Basic. The aim is to bring the power of GPGPU to the large number of .NET developers out there. Features include:

  • .NET object orientated CUDA model (GThread)
  • Write .NET code marking methods, structures and constants that should be translated to CUDA (“Cudafying”)
  • An add-in for Red Gate’s .NET Reflector tool that translates to CUDA C
  • Built in emulation of GPU kernel functions
  • 1D, 2D and 3D array support including access to Array class’s Length, GetLength and Rank members
  • Use all standard .NET value types. No new types even for managing data allocated on GPU
  • Simple .NET wrapper for CUFFT and CUBLAS

During our work with the European Space Agency, Astrium and NLR we saw how GPUs could significantly improve performance of the emulation of algorithms targeted on FPGAs and ASICs. The SDEs and SDKs produced were .NET based and CUDAfy is the result of efforts to more tightly integrate the GPU and CPU code development. There are user guides and sample projects. Many of the samples in the book CUDA by Example have been ported to .NET. See www.hybriddsp.com for downloads and more information.

OpenCL Studio 1.0 has been released

March 21st, 2011

OpenCL Studio combines OpenCL and OpenGL into a single integrated development environment for high performance computing. The feature rich editor, interactive scripting language and extensible plug-in architecture support the rapid development of complex parallel algorithms and accompanying visualization. The first production version of OpenCL Studio including instructional videos and demo applications are available at www.opencldev.com.

Jacket v1.7 for Faster MATLAB® Code

March 21st, 2011

AccelerEyes has released version 1.7 of Jacket for GPU computing with MATLAB®. Version 1.7 delivers even more speed to MATLAB with a new Sparse Linear Algebra Library, a new Signal Processing Library, a big boost to convolution functions, and more.

Jacket is the premier GPU software plugin for MATLAB. It enables rapid prototyping and problem solving across a range of government, manufacturing, energy, media, biomedical, financial, and scientific research applications. Jacket accelerates performance of common arithmetic and linear algebra functionality using the complete line of CUDA-capable GPUs from NVIDIA, including top of the line Tesla GPUs as well as Quadro visualization GPUs and GeForce gaming GPUs.

Some of the new features available with Jacket 1.7 include:

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Exact string matching algorithms in CUDA

March 21st, 2011

Exact String Matching algorithms are heavily used in a lot of applications like antivirus engines, DNA sequencing, text editors etc. This project provides CUDA implementations of  the naive, horspool and quicksearch algorithms, including a performance comparison against CPU versions: http://code.google.com/p/exactstrmatchgpu.

CUDA 4.0 Release Aims to Make Parallel Programming Easier

March 1st, 2011

Today NVIDIA announced the upcoming 4.0 release of CUDA.  While most of the major CUDA releases accompanied a new GPU architecture, 4.0 is a software-only release, but that doesn’t mean there aren’t a lot of new features.  With this release, NVIDIA is aiming to lower the barrier to entry to parallel programming on GPUs, with new features including easier multi-GPU programming, a unified virtual memory address space, the powerful Thrust C++ template library, and automatic performance analysis in the Visual Profiler tool.  Full details follow in the quoted press release below.

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