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ExaHyPE Project to Develop Exascale Software for Geophysics and Astrophysics

A new EU research project called “ExaHyPE” is developing open-source software for exascale-class supercomputers. As an international project coordinated at TUM in Munich, ExaHyPE (“An Exascale Hyperbolic PDE Engine”) seeks to develop novel software, initially for simulations in geophysics and astrophysics.

Rogue Wave Software CodeDynamics Expands the Reach of Multithreaded Debugging

Today Rogue Wave Software announced CodeDynamics, the next generation of dynamic analysis for data-intensive commercial applications. CodeDynamics expands the reach of multithreaded debugging from high performance computing environment into the commercial market.

RCE Podcast on the Conduit Model for Hierarchical Scientific Data

In this RCE podcast, Brock Palen and Jeff Squyres discuss Conduit with Cyrus Harriston from LLNL. Conduit is an open source project from Lawrence Livermore that provides an intuitive model for describing hierarchical scientific data in C++, C, Fortran, and Python and is used for data coupling between packages in-core, serialization, and I/O tasks.

Video: Python for High Performance Computing

In this video from the recent Argonne Training Program on Extreme-Scale Computing, William Scullin from Argonne National Labs presents: Python for High Performance Computing.

Accelerated Science: GPU Cluster Case Study

A successful example of how a well-managed GPU cluster allowed scientist to focus on obtaining results comes from the Tokyo University of Agriculture and Technology (TUAT) results. A research group lead by Dr. Akinori Yamanaka develops computation models and simulates engineering materials, for a variety of applications, using HPC. Using Bright Cluster Manager, Dr. Yamanaka and his team were able to immediately focus on algorithm development and not burden the team with cluster administration issues.

Bill Gropp Presents: MPI and Hybrid Programming Models

Bill Gropp presented this talk at the Argonne Training Program on Extreme-Scale Computing. “Where it is used as an alternative to MPI, OpenMP often has difficulty achieving the performance of MPI (MPI’s much-criticized requirement that the user directly manage data motion ensures that the programmer does in fact manage that memory motion, leading to improved performance). This suggests that other programming models can be productively combined with MPI as long as they complement, rather than replace, MPI.”

Video: Oclgrind – An Extensible OpenCL Device Simulator

“We describe Oclgrind, a platform designed to enable the creation of developer tools for analysis and debugging of OpenCL programs. Oclgrind simulates how OpenCL kernels execute with respect to the OpenCL standard, adhering to the execution and memory models that it defines. A simple plugin interface allows developer tools to observe the simulation and collect execution information to provide useful analysis, or catch bugs that would be otherwise difficult to spot when running the application on a real device. We give details about the implementation of the simulator, and describe how it can be extended with plugins that provide useful developer tools. We also present several example use-cases that have already been created using this platform, motivated by real-world problems that OpenCL developers face.”

Advania in Iceland Tests HPC Cloud Bursting with Docker using the Ubercloud

An Iceland-based “HPC in the Cloud” company called Advania has published an interesting case study with The Ubercloud, and online community and marketplace where engineers, scientists, and their service providers discover, try, and buy Computing Power and Software as a Service, from Cloud Resource and Software Providers around the world.

Bitfusion Labs Opens for Boosting Application Performance

Today Bitfusion announced Bitfusion Labs, a collaborative proving ground for delivering performance improvements for hardware-accelerated applications.

James Reinders Presents: Vectorization (SIMD) and Scaling (TBB and OpenMP)

James Reinders from Intel presented this talk at the Argonne Training Program on Extreme-Scale Computing. “We need to embrace explicit vectorization in our programming. But, generally use parallelism first (tasks, threads, MPI, etc.).”