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The Kokkos team will give a [tutorial at the SCA/HPCAsia](https://www.sca-hpcasia2026.jp/program.html).
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[Come and meet us there](https://www.sca-hpcasia2026.jp).
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The Kokkos team will conduct a 1-day tutorial on 26th of January at the combined HPC Asia / SCA 2026 conference in Osaka, Japan.
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For those new to Kokkos this will be an excellent opportunity to hear the introductory lectures, and get a running start into writing performance portable code with Kokkos.
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The abstract for the tutorial can be found below.
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HPSF will also be present at the conference with a BoF Session and a booth - be sure to check out both!
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### Abstract
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This tutorial provides a introduction to Kokkos, a C++ programming model designed for application performance portability across diverse computing architectures.
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As modern high-performance computing (HPC) increasingly relies on heterogeneous systems featuring GPUs, multicore CPUs,
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and other accelerators, developers face the challenge of writing code that efficiently utilizes these varied
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hardware resources without developing and maintaining multiple variants of the software.
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Kokkos addresses this by offering a single-source approach, allowing users to write code once and compile it for optimal execution on a wide range of platforms.
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Kokkos is an Open Source project under the Linux Foundation’s “High Performance Software Foundation" (https://hpsf.io).
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We'll start by exploring the fundamental concepts of Kokkos, including memory spaces and execution spaces,
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which are crucial for managing data placement and task execution on different devices.
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You'll learn about `Kokkos::parallel_for` for launching parallel computations and `Kokkos::View` for
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managing data arrays efficiently on various memory architectures.
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Through hands-on examples, we'll demonstrate how to port simple computational kernels to Kokkos,
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highlighting the benefits of its abstraction layers.
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By the end of this tutorial, beginners will have a solid foundation for developing performance-portable
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applications with Kokkos, enabling them to leverage the full power of modern HPC systems.
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No prior experience with parallel programming models like CUDA or OpenMP is required, though basic C++ knowledge is assumed.
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