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Articles and news on parallel programming and code modernization

Checkpointing the Un-checkpointable: MANA and the Split-Process Approach

Gene Cooperman from Northeastern University gave this talk at the MVAPICH User Group. “This talk presents an efficient, new software architecture: split processes. The “MANA for MPI” software demonstrates this split-process architecture. The MPI application code resides in “upper-half memory”, and the MPI/network libraries reside in “lower-half memory”.

7 Ways HPC Software Developers Can Benefit from Intel Software Investments

Intel has long focused on supporting HPC software. But, as the years have gone by, much has changed — and the company’s offerings have grown and evolved. A chapter from a recent edition of Parallel Universe Magazine, from this past July outlines this evolution and offers seven ways HPC software developers can benefit from Intel software investments. 

Appentra Releases Parallelware Trainer 1.3

Appentra has released Parallelware Trainer 1.3, an interactive, real-time code editor with features that facilitate the learning, usage, and implementation of parallel programming by understanding how and why sections of code can be parallelized. “We’re happy to announce the release of Parallelware Trainer 1.3 which now supports the detection of defects and recommendations for concurrency and parallelism. We expect this new feature to further improve the learning process by providing feedback about code issues right in the integrated editor.”

Chapel Comes of Age: a Language for Productivity, Parallelism, and Performance

Brad Chamberlain from Cray gave this talk at the HPCKP’19 conference. “Though Chapel has been under development for some time now, its performance and feature  set have only recently reached the point where it can seriously be considered by users with HPC-scale scientific, data analytic, and artificial intelligence workloads. In this talk, I will introduce Chapel for those who are new to the language, and cover recent advances, milestones, and performance results for those who are already familiar with it.”

Overview of the MVAPICH Project and Future Roadmap

DK Panda gave this talk at the MVAPICH User Group. “This talk will provide an overview of the MVAPICH project (past, present, and future). Future roadmap and features for upcoming releases of the MVAPICH2 software family (including MVAPICH2-X and MVAPICH2-GDR) for HPC and Deep Learning will be presented. Features and releases for Microsoft Azure and Amazon AWS will also be presented. Current status and future plans for OSU INAM, OMB, and Best Practices Page will also be presented.”

Video: Three Perspectives on Message Passing

Robert Harrison from Brookhaven gave this talk at the MVAPICH User Group. “MADNESS, TESSE/EPEXA, and MolSSI are three quite different large and long-lived projects that provide different perspectives and driving needs for the future of message passing. All three of these projects employ MPI and have a vested interest in computation at all scales, spanning the classroom to future exascale systems.”

Job of the Week: Senior HPC Specialist at New York University

New York University is seeking a Senior HPC Specialist in our Job of the Week. “In this role, you will provide technical leadership in design, development, installation and maintenance of hardware and software for the central High-Performance Computing systems and/or research computing services at New York University. Plan, design, and install Linux operating system’s hardware, cluster management software, scientific computing software and/or network services.”

Video: High-Performance Computing with Python – Reducing Bottlenecks

This course addresses scientists with a working knowledge of NumPy who wish to explore the productivity gains made possible by Python for HPC. “We will show how Python can be used on parallel architectures and how to optimize critical parts of the kernel using various tools. The following topics will be covered: – Interactive parallel programming with IPython – Profiling and optimization – High-performance NumPy – Just-in-time compilation with Numba – Distributed-memory parallel programming with Python and MPI – Bindings to other programming languages and HPC libraries – Interfaces to GPUs.”

Multiple Endpoints in the Latest Intel MPI Library Boosts Hybrid Performance

The performance of distributed memory MPI applications on the latest highly parallel multi-core processors often turns out to be lower than expected. Which is why hybrid applications using OpenMP multithreading on each node and MPI across nodes in a cluster are becoming more common. This sponsored post from Intel, written by Richard Friedman, depicts how to boost performance for hybrid applications with multiple endpoints in the Intel MPI Library. 

PASC19 Evolves into an International Conference on Computational Science

In this video from PASC19, Torsten Hoefler from ETH Zurich describes how PASC19 has grown into an international conference with over 60 percent of attendees from outside Switzerland. After that, he describes a new groundbreaking programming model his team is developing that centers around the minimization of data movement for computation.