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Parallel Computing in Python: Current State and Recent Advances

Pierre Glaser from INRIA gave this talk at EuroPython 2019. “Modern hardware is multi-core. It is crucial for Python to provide high-performance parallelism. This talk will expose to both data-scientists and library developers the current state of affairs and the recent advances for parallel computing with Python. The goal is to help practitioners and developers to make better decisions on this matter.”

Podcast: Quantum Supremacy? Yes and No!

In this podcast, the RadioFreeHPC team discusses the Google/NASA paper, titled “Quantum Supremacy Using a Programmable Superconducting Processor”, that was published and then unpublished. “The tantalizing promise of quantum computers is that certain computational tasks might be executed exponentially faster on a quantum processor than on a classical processor. A fundamental challenge is to build a high-fidelity processor capable of running quantum algorithms in an exponentially large computational space.”

Recent Research on using Public Clouds for HPC Workloads

Alex Norton from Hyperion Research gave this talk at the HPC User Forum. “Hyperion Research provides data-driven research, analysis and recommendations for technologies, applications, and markets in high performance computing and emerging technology areas to help organizations worldwide make effective decisions and seize growth opportunities. Research includes market sizing and forecasting, share tracking, segmentation, technology and related trend analysis, and both user & vendor analysis for multi-user technical server technology used for HPC and HPDA (high performance data analysis).”

Video: Are women underrepresented in the HPC community?

Athina Frantzana from the University of Edinburgh gave this talk at the EuroPython Conference. “This study is the first attempt to understand the current gender demographics of the HPC community, and identify potential reasons and ways to tackle the gender imbalance. By listening to the people who constitute the community, the study offers a guideline on what the HPC community should focus on in order to become more attractive, accessible and useful to everyone.”

Podcast: FinTech and HPC-AI

In this podcast, the Radio Free HPC team looks back at the HPC-AI on Wall Street conference. “We discuss the well-received Cryptocurrency panel that he moderated, the challenges of using of AI in financial services, the emerging computational storage, and advanced HPC-class modeling that helps venture capital investors decide whether to invest in a startup.”

HPC in the Cloud Offers Flexible, Scalable Solutions for Enterprises and Research Institutions

In this guest article, our friends at Intel discuss how HPC as a Service (HPCaaS) reduces barriers to HPC and offers a cost-effective extension to on-premise solutions. High performance data analytics (HPDA), simulation and modeling, and artificial intelligence (AI) enable significant benefits like quicker business insights, the ability to design and bring products to market faster, or real-time monitoring of financial transactions for fraud.

An Update on ARM in HPC

Brent Gorda from Arm gave this talk at the Linaro Connect conference. “Arm-based systems are showing up in the HPC community and new silicon is coming. The architecture has also been selected for several of the exascale projects worldwide. Brent will talk about the aspects of Arm that are attractive to the HPC community, updates on projects and what we as a community can do to help accelerate adoption in this space.”

Reflections on Deep Learning, DNNs, and AI on Wall Street

In this special guest feature, Bob Fletcher from Verne Global reflects on the recent HPC and AI on Wall Street conference. “Almost every organization at the event talked about their use of machine learning and some indicated what would make them extend it into full-scale deep learning. The most important criteria were the appropriateness of the DNN training techniques.”

Exploring the Performance Optimization and Productivity Project

The “quest” for improved performance is never over, if you want to remain competitive in your respective market. Your end users will undoubtedly call for more speed in the future, and the models your clients are building are likely bigger and more complex than ever. Enter the Performance Optimisation and Productivity (PoP) project.

Study finds On-Premise Systems Critical to Enterprise AI

Today Cray released the findings of its industry report on the State of Enterprise AI Adoption 2019, which reveals that performance, data locality and security are the top considerations for choosing an AI infrastructure. “The survey assessed whether organizations and individuals are prepared to run AI effectively and to take advantage of the capabilities it offers.”