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Debugging for Success and Accelerated Platform Bring-Up

Debugging can prove a substantial challenge, even for experienced engineers. In this video, Soflen Shih, a technical consulting engineer at Intel, discusses the benefits of Intel System Studio and how its built-in functionality can make the debugging process much easier. “Intel System Studio contains libraries, performance analyzers, and compilers as well as profiling and debugging tools. The combination of these elements provides a complete developer solution to assist with platform bring-up, power optimization, thermal tuning, and system performance profiling.”

Intel Performance Libraries Accelerate Python Performance for HPC and Data Science

Python is now the most popular programming language, according to IEEE Spectrum’s fifth annual interactive ranking of programming languages, ahead of C++ and C. Recent Intel Distributions for Python show that real HPC performance can be achieved with compilers and library packages optimized for the latest Intel architectures. Moreover, the library packages targeted for big data analysis and numerical computation included in this distribution now support scaling for multi-core and many-core processors as well as distributed cluster and cloud infrastructures.

Expressing Parallelism in C++ with Threading Building Blocks

Parallelism helps applications make the best use of processors on single or multiple devices. However, parallelism implementation itself can prove a challenging task. In this video, Mike Voss, principal engineer with the Core and Visual Computing Group at Intel discusses the benefits of Intel® Threading Building Blocks (Intel® TBB), a C++ library, and how it can simplify the work of adding parallelism without the need to probe into threading details.

Learn to Code for Parallel HPC with Appentra Parallelware Trainer 1.0

Today Appentra Solutions released their newest HPC training assistance tool, Parallelware Trainer 1.0, an interactive learning environment where users can learn how to parallelize while interacting with real code. For educators, the tool provides the ability to enhance traditional lecture-based training by allowing learners to apply their knowledge in real-time. “Appentra’s goal has always been to minimize and eventually remove the parallel software development barrier, democratizing access to HPC and making parallel computing easier for everyone. With the release of Parallelware Trainer 1.0 we bring this one step closer.”

Intel® Compilers Overview: Scalable Performance for Intel® Processors

Intel Compilers for C/C++ and Fortran empower developers to derive the greatest performance from applications and hardware. In this video, Igor Vorobtsov discusses nuances of Intel compiler features which enable high-level optimization, auto-parallelization, auto-vectorization, dynamic profile guided optimization, detailed optimization reports, inter-procedural optimization (IPO), and much more.

Altair Open Sources Model-Based Development Software

“Altair is now open-sourcing its open matrix language – a high-level, matrix-based numerical computing language – to encourage interested scientists and engineers to expand the language, add toolboxes, and employ it for their math modeling and simulation tasks. Opening up our scripting language to the worldwide community will allow us and our community members to actively collaborative to keep up with the ever-increasing pace of technology changes.”

Altair Rolls Out Inspire and Altair 365 for Product Development

Today Altair announced the release and immediate availability of the Altair Inspire simulation-driven design platform, and the Altair 365 cloud collaboration platform. The Altair Inspire platform enables manufacturers to leverage simulation to drive the entire design process, accelerating the pace of innovation and reducing time-to-market.

Job of the Week: Computer Science Postdoctoral Scholar at LBNL

LBNL is seeking a Computer Science Postdoctoral Scholar in our Job of the Week. “Berkeley Lab’s Computational Research Division has an opening for a Computer Science Postdoctoral Scholar. Develop performance modeling and analytical capabilities and tools for manycore and GPU-accelerated supercomputers and apply them to distributed memory Office of Science applications running on such platforms.”

Tutorial: “How to use Jupyter Notebooks”

In this video from the Blue Waters Symposium, Roland Haas from NCSA presents: Tutorial: How to use Jupyter Notebooks. “Jupyter notebooks provide a web-based interface to Python, R, Julia and other languages. They allow code, code output, and documentation to be mixed in a single document making it possible to contain self-documented workflows. Focusing on Python I will show how to use Jupyter notebooks on Blue Waters to explore data, produce plots and analyze simulation output using numpy, matplotlib and time permitting, I will show how to use notebooks on login nodes and on compute nodes as well as, time permitting, how to use parallelism inside of Jupyter notebooks.”

Codeplay Releases First Fully-Conformant SYCL 1.2.1 Solution for C++

SYCL is an open standard developed by the Khronos Group that enables developers to write code for heterogeneous systems using standard C++. Developers are looking at how they can accelerate their applications without having to write optimized processor specific code. SYCL is the industry standard for C++ acceleration, giving developers a platform to write high-performance code in standard C++, unlocking the performance of accelerators and specialized processors from companies such as AMD, Intel, Renesas, and Arm.