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Articles and news on parallel programming and code modernization

Video: Speeding up Programs with OpenACC in GCC

Thomas Schwinge from Mentor gave this talk at FOSDEM’19. “Requiring only few changes to your existing source code, OpenACC allows for easy parallelization and code offloading to accelerators such as GPUs. We will present a short introduction of GCC and OpenACC, implementation status, examples, and performance results.”

Argonne Looks to Singularity for HPC Code Portability

Over at Argonne, Nils Heinonen writes that Researchers are using the open source Singularity framework as a kind of Rosetta Stone for running supercomputing code almost anywhere. “Once a containerized workflow is defined, its image can be snapshotted, archived, and preserved for future use. The snapshot itself represents a boon for scientific provenance by detailing the exact conditions under which given data were generated: in theory, by providing the machine, the software stack, and the parameters, one’s work can be completely reproduced.”

Are Platform Configuration Problems Degrading Your Application’s Performance?

The Intel VTune™ Amplifier Platform Profiler on Windows* and Linux* systems shows you critical data about the running platform that help identify common system configuration errors that may be causing performance issues and bottlenecks. Fixing these issues, or modifying the application to work around them, can greatly improve overall performance.

Podcast: Doug Kothe Looks back at the Exascale Computing Project Annual Meeting

In this podcast, Doug Kothe from the Exascale Computing Project describes the 2019 ECP Annual Meeting. “Key topics to be covered at the meeting are discussions of future systems, software stack plans, and interactions with facilities. Several parallel sessions are also planned throughout the meeting.”

Accelerated Python for Data Science

The Intel Distribution for Python takes advantage of the Intel® Advanced Vector Extensions (Intel® AVX) and multiple cores in the latest Intel architectures. By utilizing the highly optimized Intel MKL BLAS and LAPACK routines, key functions run up to 200 times faster on servers and 10 times faster on desktop systems. This means that existing Python applications will perform significantly better merely by switching to the Intel distribution.

Apply Now for 2019 Argonne Training Program on Extreme-Scale Computing

Computational scientists are invited to apply for the upcoming Argonne Training Program on Extreme-Scale Computing (ATPESC) this Summer. “This program provides intensive hands-on training on the key skills, approaches, and tools to design, implement, and execute computational science and engineering applications on current supercomputers and the HPC systems of the future. As a bridge to that future, this two-week program fills many gaps that exist in the training computational scientists typically receive through formal education or other shorter courses.”

Call for Papers: Distributed & Heterogeneous Programming in C/C++ Event in Boston

The DHPCC++19 conference has issued its Call for Papers. Held in conjunction with the IWOCL event, the Distributed & Heterogeneous Programming in C/C++ event takes place May 13, 2019 in Boston. “This will be the 3rd DHPCC++ event in partnership with IWOCL, the international OpenCL workshop with a focus on heterogeneous programming models for C and C++, covering all the programming models that have been designed to support heterogeneous programming in C and C++.”

Podcast: Improving Parallel Applications with the TAU tool

In the podcast, Mike Bernhardt from ECP catches up with Sameer Shende to learn how the Performance Research Lab at the University of Oregon is helping to pave the way to Exascale. “Developers of parallel computing applications can well appreciate the Tuning and Analysis Utilities (TAU) performance evaluation tool—it helps them optimize their efforts. Sameer has worked with the TAU software for nearly two and a half decades and has released more than 200 versions of it. Whatever your application looks like, there’s a good chance that TAU can support it and help you improve your performance.”

Call for Papers: International Workshop on Performance Portable Programming models for Manycore or Accelerators

The 4th International Workshop on Performance Portable Programming models for Manycore or Accelerators (P^3MA) has issued their Call for Papers. This workshop will provide a forum to bring together researchers and developers to discuss community’s proposals and solutions to performance portability.

Latest Intel Tools Make Code Modernization Possible

Code modernization means ensuring that an application makes full use of the performance potential of the underlying processors. And that means implementing vectorization, threading, memory caching, and fast algorithms wherever possible. But where do you begin? How do you take your complex, industrial-strength application code to the next performance level?