• Solving partial differential equations efficiently on the heterogeneous computing systems. There is some emphasis on GPU computing, but other accelerators and the efficient use of large multi-core cluster nodes are considered as well.
• Optimization of computational kernels coming from finite differences, spectral methods, and lattice gauge theory on accelerators.
• We plan to have a tutorial day, two days of talks and a poster session. We plan for discussion and talks to provide an overview of current work in these areas, and to develop future lines of research and collaborations. The deadline for submission of talks is 15 August 2011.

Please visit http://wwwsfb.tpi.uni-jena.de/Events/Event-PHSP11.shtml for more information. This workshop is organised by G. Zumbusch (Chair, Jena), B. Bruegmann (Jena), A. Weyhausen (Jena), L. Rezzolla (Potsdam) and B. Zink (Tuebingen).

Particle–mesh interpolations are fundamental operations for particle-in-cell codes, as implemented in vortex methods, plasma dynamics and electrostatics simulations. In these simulations, the mesh is used to solve the field equations and the gradients of the fields are used in order to advance the particles. The time integration of particle trajectories is performed through an extensive resampling of the flow field at the particle locations. The computational performance of this resampling turns out to be limited by the memory bandwidth of the underlying computer architecture. We investigate how mesh–particle interpolation can be efficiently performed on graphics processing units (GPUs) and multicore central processing units (CPUs), and we present two implementation techniques. The single-precision results for the multicore CPU implementation show an acceleration of 45–70×, depending on system size, and an acceleration of 85–155× for the GPU implementation over an efficient single-threaded C++ implementation. In double precision, we observe a performance improvement of 30–40× for the multicore CPU implementation and 20–45× for the GPU implementation. With respect to the 16-threaded standard C++ implementation, the present CPU technique leads to a performance increase of roughly 2.8–3.7× in single precision and 1.7–2.4× in double precision, whereas the GPU technique leads to an improvement of 9× in single precision and 2.2–2.8× in double precision.

(Diego Rossinelli, Christian Conti and Petros Koumoutsakos: “Mesh−particle interpolations on GPUs and multicore CPUs”, Phil. Trans. R. Soc. A 2011, 369:2164-2175 [doi])

• PCG – Preconditioned conjugate gradient solver for symmetric matrices (e.g., p)
• PBiCG – Preconditioned biconjugate gradient solver for asymmetric matrices (e.g., Ux, k)

ofgpu also has support for the OpenFOAM preconditioners:

• no
• diagonal

For more details see “GPU Linear Solver Library for OpenFOAM”. OpenFOAM is a registered trademark of OpenCFD and is unaffiliated with Symscape.

This paper proposes a new sparse matrix storage format which allows an efficient implementation of a sparse matrix vector product on a Fermi Graphics Processing Unit (GPU). Unlike previous formats it has both low memory footprint and good throughput. The new format, which we call Sliced ELLR-T has been designed specifically for accelerating the iterative solution of a large sparse and complex-valued system of linear equations arising in computational electromagnetics. Numerical tests have shown that the performance of the new implementation reaches 69 GFLOPS in complex single precision arithmetic. Compared to the optimized six core Central Processing Unit (CPU) (Intel Xeon 5680) this performance implies a speedup by a factor of six. In terms of speed the new format is as fast as the best format published so far and at the same time it does not introduce redundant zero elements which have to be stored to ensure fast memory access. Compared to previously published solutions, significantly larger problems can be handled using low cost commodity GPUs with limited amount of on-board memory.

(A. Dziekonski, A. Lamecki, and M. Mrozowski: “A memory efficient and fast sparse matrix vector product on a GPU“, Progress In Electromagnetics Research, Vol. 116, 49-63, 2011. [PDF])

• Multi-GPU support
• Tested on Fermi architecture (GTX460 and Tesla C2050)
• Automated submission of the domain to the GPU cards (using decomposePar from OpenFOAM)
• Optimized submission of computational tasks to the best GPU card in the system for any number of computational threads
• Plugin picks the most powerful GPU card for a single thread cases

The OpenFOAM SpeedIT plugin is available at http://speedit.vratis.com.

ACUSim vortex shedding

From a recent press release:

ACUSIM Software, Inc., a leader in computational fluid dynamics (CFD) technology and solutions, today announced the immediate availability of AcuSolve™ 1.8, the latest version of ACUSIM’s leading general-purpose, finite-element based CFD solver. ACUSIM will demonstrate AcuSolve 1.8 during two free webinars, taking place at 9:30 a.m. – 10:30 a.m. ET and 6:30 p.m. – 7:30 p.m. ET, on Oct. 26, 2010, at http://www.acusim.com/html/events.html.

Used by designers and research engineers with all levels of expertise, AcuSolve is highly differentiated by its accelerated speed, robustness, accuracy and multiphysics/multidisciplinary capabilities. Contributing to its robustness is the product’s Galerkin/Least-Square (GLS) finite element formulation and novel iterative linear equation solver for the fully coupled equation system. The combination of these two powerful technologies provides a highly stable and efficient solver, capable of handling unstructured meshes with tight boundary layers automatically generated from complex industrial geometries.

“ACUSIM’s products are known for their advanced solver technology including Fluid-Structure Interaction solutions,” said Dr. Farzin Shakib, founder and CEO of ACUSIM Software. “While continuously adding to its core technology, the latest version of AcuSolve is concentrated on providing customers with ease of use and CAE automation to solve mission critical problems in a more efficient and timely fashion.”

AcuSolve 1.8 users will experience improvements and new features in the core technology and pre-processing and post-processing phases. These enhancements include:

• Core Technology:
  • Enriched simulation capabilities of ACUSIM’s leading Fluid-Structure Interaction (FSI) technology with added interface to MD Nastran
  • Extended Arbitrary Lagrangian Eulerian (ALE) Formulation to handle compressible flows with large density variation and mesh motion
  • Anisotropic thermal conductivity
  • Improved Free Surface Technology with the addition of multi-iterative coupling based nonlinear update solver
  • New Algebraic Multi-Grid (AMG) Technology for faster flow convergence and optimized linear solver performance
  • Support for GPU acceleration based on NVIDIA CUDA 3.0 technology

• Pre-processing:
  • Much improvement in meshing such as region of influence and anisotropic meshing and edge control
  • CAE Automation and Customization with improved Template Driven and Customization Driven Automation and batch oriented processing
  • Interface to electromechanical simulation software JMAG to perform full thermal flow analysis on electro-magnetic devices
  • Easier deployment with existing corporate Cloud Computing Clusters and Dassault Simulia SLM systems
  • Embedded CAD geometry generator

• Post-processing:
  • New AcuSolve/Paraview co-process visualization
  • Full batch-oriented report generation capability including text, pagination, equations, tables, 2D plots, full 3D visualization and animation
  • New flexible input structure for AcuSolve’s particle tracer, with the ability to add user evolution equations

IMPETUS Afea is proud to announce the launch of IMPETUS Afea Solver (version 1.0).

The IMPETUS Afea Solver is a non-linear explicit finite element tool. It is developed to predict large deformations of structures and components exposed to extreme loading conditions. The tool is applicable to transient dynamics and quasi-static loading conditions. The primary focus of the IMPETUS Afea Solver is accuracy, robustness and simplicity for the user. The number of purely numerical parameters that the user has to provide as input is kept at a minimum. The IMPETUS Afea Solver is adapted to GPU technology; utilizing the computational force of a potent graphics card can considerably speed up your calculations.

IMPETUS Afea Solver Video on YouTube

For more information or requests please contact sales@impetus-afea.com