Adoption of Python has been enormous over the last decade. Why? It’s easy to use, accessible, versatile and can be used for AI, machine learning, data analytics, data visualization, and all types of science. Tune into how 3 experts are involved in building common standards for Python data APIs that can help users use a large collection of libraries to develop high-performance code without limitations on adding exotic features. Regarding the huge growth of custom libraries, “it was more a social problem than a technical problem…we should avoid writing more code. Writing yet another library is very likely not going to be the answer.” The Python Data API Consortium was organized to bring people together and solve a fundamental problem to deliver a common standard. Listen in. [26:32]

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Ginkgo is a production-ready, sparse linear algebra library used for HPC on GPU architectures. It’s now using oneAPI cross-architecture programming to support its foundational design with a high level of performance portability, and focus on software sustainability. ExpertsHartwig Anzt at Karlsruhe Institute of Technology (KIT) and Univ. of Tennessee, and Terry Cojean of KIT provide their insights on lessons learned moving CUDA code to other hardware architectures, and tools that help smooth that transition. “…The oneAPI ecosystem has proven to be a very powerful and useful option for us to actually target different architectures that are all supported by oneAPI…” Listen in. [21:19]

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Scientific visualization (SciVis) is providing new insights in health care and many other research areas in ways that we couldn’t imagine a decade ago. It’s an evolving field where extracting visualizations from very large data sets can improve analysis, diagnosis and patient outcomes while reducing costs – or even uncover hidden discrimination. Hear from Teodora (Dora) Szasz of the University of Chicago and Donna Nemshick of Intel on how SciVis can be transformative in areas such as understanding a billion simulated cells for tumors, creating the Covid-19 model, pioneering medical care, and even studying images in children’s books for gender inequality.

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Donna Nemshick, performance validation lead, Intel Advanced Rendering & Visualization Architecture Group

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University of Chicago Research Computing Center

University of Chicago Visualization Laboratory

Heterogeneous programming is challenging for developers because it’s been difficult to code or forces compromises in performance. oneAPI is working to break that mold. Many HPC research centers, enterprises and developers are now adopting oneAPI. Hear from experts at Zuse Institute Berlin (ZIB) on their oneAPI story: “We want to have most code portability across different processor architectures, and we don’t want to be bound to specific architectures,” says Dr. Thomas Steinke, head of ZIB’s super computing department. Listen in. [24:01]

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Just as a carpenter needs tools to build a house, a developer needs tools to write code and programs. This often means relying on other coders to develop tools and building on that foundation. Xiaozhu Meng, a research scientist at Rice University shares the progress of the HPC Toolkit Project. It’s focused on performance tuning – to help with problems like how to map the performance numbers from machine-code back to a higher-level programming language construct; or for GPUs, doing fine-grained management to manage performance inside kernels. He also discusses exascale computing, and how oneAPI fits in the mix for tools to help developers. Listen in. [20:30]

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Bioinformatics is advancing health-care research by using computation to understand biological data. It’s useful for large complex data sets used in determining gene and protein functions, establishing evolutionary relationships, and predicting 3D shapes of proteins. Two experts, Sergio Santander-Jimenez at University of Extremadura, and Ricardo Nobre of INESC-ID, are combining the power of modern hardware (CPUs+GPUs), HPC compute, and software to advance bioinformatics applications in areas including epistasis detection. Hear how they made it happen: [16:30]

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The next generation of scientists and coders need more than a love of science and technology. The use of supercomputers in digital design to simulation pose opportunities solving the world’s biggest questions. Katherine Riley, director of science for Argonne’s Leadership Computing Facility, and Joe Curley, Intel senior director of oneAPI products, solutions and ecosystem, share what inspires them, and the unique characteristics to thrive in these careers. “It’s not just nerds working on ones and zeros, but we’re out to try to make a better planet.”

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INESC-ID researchers Aleksandar Ilic and Diogo Augusto Pereira Marques reveal their journey in extending Roofline Modeling for use in application optimization, known as the Cache-aware Roofline Model, or CARM, which has been incorporated into the Intel® Advisor tool and recognized with an award from the HiPEAC community in Europe. They are now taking this model further, tackling different types of devices, including CPUs and GPUs, with the help of DPC++. Using CARM, developers can detect bottlenecks in their code and derive strategies to squeeze maximum performance out of their architecture.

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Despite its tough challenges, our global pandemic has opened the door to big opportunities, ushering in incredible innovation in visual effects and the discovery of amazing talent regardless of location. Real-time technology and tools, machine learning and artificial intelligence, and the rise of volume rendering, in conjunction with geometric rendering, are transforming storytelling. Collaboration on open technologies through the Academy Software Foundation is accelerating and democratizing development. Rob Bredow, SVP and Chief Creative Officer at Industrial Light & Magic, and Jim Jeffers, Senior Principal Engineer and Senior Director of Intel’s Advanced Rendering and Visualization team, cover these topics and more on this episode.

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Dr. Ruymán Reyes Castro, CTO at Codeplay Software, and Kevin Harms, Senior Software Developer at Argonne Leadership Computing Facility, talk about their collaboration with the National Energy for Research Scientific Computing Center (NERSC) at Lawrence Berkeley Lab to enhance the LLVM-based DPC++ open source compiler, based on the SYCL standard, to support Nvidia GPUs. They discuss the key role of open communities in furthering innovation, building on top of the modern C++ standard to support accelerators and advanced hardware, fostering a strong ecosystem around SYCL and DPC++, the merits of the latest features in the SYCL 2020 standard, and more.

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