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Parallelism in Python: Directing Vectorization with NumExpr

According to a new edition of Parallel Universe Magazine, from Intel, Python has several pathways to vectorization. These range from just-intime (JIT) compilation with Numba 1 to C-like code with Cython. A chapter from a recent edition of Parallel Universe Magazine, explores parallelism in Python.

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”.

Identifying Opportunities to Improve Efficiency in HPC Clusters

Jordi Blasco from HPC Now! gave this talk at HPCKP’19. “Jordi Blasco has developed a new open source monitoring tool which allows the HPC user support teams to identify new opportunities to improve the efficiency of the codes being executed on HPC resources. Earlier adopters of this new tool, and through the continuous monitoring of jobs efficiency, have been able to improve the scalability and performance of several codes and workflows.”

Thermoplastic Connectors Grow in Popularity Along with Liquid Cooling

As liquid cooling becomes more and more prevalent, new technology and types of connectors are becoming water cooler topics for those in the data and computing industries. According to a new report from CPC, long-term, leak-free performance in fluid management systems requires robust connectors. And advanced materials are growing the range of available QD options.

Insilico Medicine Brings GENTRL AI System to Open Source for Drug Discovery

Insilico Medicine has developed GENTRL, a new artificial intelligence system for drug discovery that dramatically accelerates the process from years to days. “By enabling the rapid discovery of novel molecules and by making GENTRL’s source code open source, we are ushering in new possibilities for the creation and discovery of new life-saving medicine for incurable diseases — and making such powerful technology more broadly accessible for the first time to the public.”

AMD: Delivering the Future of High-Performance Computing

Dr. Lisa Su from AMD gave this talk at the recent DARPA Electronics Resurgence Initiative Summit. “Optimum system performance requires co-design of silicon chips, system architecture, and software. She presented the example of the Frontier exascale computer system being developed for Oak Ridge National Lab, which should exhibit 1.5 exaflops by 2021. While the highest-performance chips and systems will initially be limited to the most expensive machines, it is expected that similar technology will become available within a few years in data centers, edge computers, and even mobile devices.”

Podcast: ECP Team Achieves Huge Performance Gain on Materials Simulation Code

The Exascale Atomistics for Accuracy, Length, and Time (EXAALT) project within the US Department of Energy’s Exascale Computing Project (ECP) has made a big step forward by delivering a five-fold performance advance in addressing its fusion energy materials simulations challenge problem. “Summit is at roughly 200 petaflops, so by the time we go to the exascale, we should have another factor of five. That starts to be a transformative kind of change in our ability to do the science on these machines.”

Supercomputing and the Scientist: How HPC and Analytics are transforming experimental science

In this video from DataTech19, Debbie Bard from NERSC presents: Supercomputing and the scientist: How HPC and large-scale data analytics are transforming experimental science. “Debbie Bard leads the Data Science Engagement Group NERSC. NERSC is the mission supercomputing center for the USA Department of Energy, and supports over 7000 scientists and 700 projects with supercomputing needs.”

The ABCI Supercomputer: World’s First Open AI Computing Infrastructure

Shinichiro Takizawa from AIST gave this talk at the MVAPICH User Group. “ABCI is the world’s first large-scale Open AI Computing Infrastructure, constructed and operated by AIST, Japan. It delivers 19.9 petaflops of HPL performance and world’ fastest training time of 1.17 minutes in ResNet-50 training on ImageNet datasets as of July 2019. In this talk, we focus on ABCI’s network architecture and communication libraries available on ABCI and shows their performance and recent research achievements.”

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.