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content/events/2025/an-introduction-to-developing-highly-parallel-applications-using-c++-and-sycl.md

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@@ -7,12 +7,11 @@ title: 'An introduction to developing highly parallel applications using C++ and
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external_url: 'https://www.hipeac.net/2025/barcelona/#/program/sessions/8191/'
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---
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In this tutorial, we will introduce SYCL and provide programmers with a solid foundation
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they can build on to gain mastery of this language. The main benefit of using SYCL over
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other heterogeneous programming models is the single programming language approach,
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which enables one to target multiple devices using the same programming model, and
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In this tutorial, we will introduce SYCL and provide programmers with a solid foundation they can build on to gain
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mastery of this language. The main benefit of using SYCL over other heterogeneous programming models is the single
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programming language approach, which enables one to target multiple devices using the same programming model, and
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therefore to have a cleaner, portable, and more readable code.
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This is a hands-on tutorial. The real learning will happen as attendees write code.
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The format will be short presentations followed by hands-on exercises.
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Hence, attendees will require their own laptop to perform the hands-on exercises.
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This is a hands-on tutorial. The real learning will happen as attendees write code. The format will be short
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presentations followed by hands-on exercises. Hence, attendees will require their own laptop to perform the hands-on
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exercises.

content/research_papers/2024/2024-12-19-implementation-of-two-numerical-solvers-for-the-study-of-non-equilibrium-gas-dynamics-on-gpu-accelerated-platforms-using-sycl.md

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- portability
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The application of GPUs has extended beyond traditional graphics rendering because their
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parallel processing capabilities can accelerate many general-purpose tasks, such as machine
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learning and scientific computing. This thesis presents the implementation of two numerical
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solvers for the solution of non-equilibrium gas flows. It also demonstrates the computational
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performance of the two solvers when developed to target GPU-based supercomputers using the SYCL
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programming model. The first solver incorporates a novel ray-tracing technique and accurate
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mathematical relations to efficiently compute any observable property of free-molecular flow
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past convex shapes (FMFC). It computes integrals of the Maxwell-Boltzmann distribution function
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to create an algorithm that quickly evaluates any moment of the local particle-velocity
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distribution. This highly efficient technique is extended for GPUs to accelerate the
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computation of accurate results. Results produced with the solver serve as robust benchmarks
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in the validation of other scientific models that describe fluid motion in non-equilibrium
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regimes. The second solver extends a CPU-based implementation of the discontinuous Galerkin Hancock (DGH)
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method into an efficient GPU code. The DGH scheme is a high-order numerical method that
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solves hyperbolic partial differential equations (PDEs) with stiff source terms. This class
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of equations is common in many models that are used to describe non-equilibrium gas flows.
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The GPU implementation of the DGH solver that is presented in this work provides a
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computationally efficient and numerically accurate method to compute the solution for these
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models. Results produced by the FMFC and DGH solvers showcase their accuracy and parallel
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scalability as efficient GPU algorithms. Furthermore, the effectiveness of the FMFC
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solver as a validation tool is demonstrated by producing benchmarks to confirm the
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accuracy of scientific models that are solved with numerical schemes such as DGH.
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The application of GPUs has extended beyond traditional graphics rendering because their parallel processing
15+
capabilities can accelerate many general-purpose tasks, such as machine learning and scientific computing. This thesis
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presents the implementation of two numerical solvers for the solution of non-equilibrium gas flows. It also demonstrates
17+
the computational performance of the two solvers when developed to target GPU-based supercomputers using the SYCL
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programming model. The first solver incorporates a novel ray-tracing technique and accurate mathematical relations to
19+
efficiently compute any observable property of free-molecular flow past convex shapes (FMFC). It computes integrals of
20+
the Maxwell-Boltzmann distribution function to create an algorithm that quickly evaluates any moment of the local
21+
particle-velocity distribution. This highly efficient technique is extended for GPUs to accelerate the computation of
22+
accurate results. Results produced with the solver serve as robust benchmarks in the validation of other scientific
23+
models that describe fluid motion in non-equilibrium regimes. The second solver extends a CPU-based implementation of
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the discontinuous Galerkin Hancock (DGH)method into an efficient GPU code. The DGH scheme is a high-order numerical
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method that solves hyperbolic partial differential equations (PDEs) with stiff source terms. This class of equations is
26+
common in many models that are used to describe non-equilibrium gas flows. The GPU implementation of the DGH solver that
27+
is presented in this work provides a computationally efficient and numerically accurate method to compute the solution
28+
for these models. Results produced by the FMFC and DGH solvers showcase their accuracy and parallel scalability as
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efficient GPU algorithms. Furthermore, the effectiveness of the FMFC solver as a validation tool is demonstrated by
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producing benchmarks to confirm the accuracy of scientific models that are solved with numerical schemes such as DGH.

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