diff --git a/content/events/2025/an-introduction-to-developing-highly-parallel-applications-using-c++-and-sycl.md b/content/events/2025/an-introduction-to-developing-highly-parallel-applications-using-c++-and-sycl.md
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+---
+contributor: max
+date: '2025-01-22T14:46:00'
+starts: '2025-01-22T13:00:00+01:00'
+ends: '2025-12-04T16:30:00+01:00'
+title: 'An introduction to developing highly parallel applications using C++ and SYCL'
+external_url: 'https://www.hipeac.net/2025/barcelona/#/program/sessions/8191/'
+---
+
+In this tutorial, we will introduce SYCL and provide programmers with a solid foundation they can build on to gain
+mastery of this language. The main benefit of using SYCL over other heterogeneous programming models is the single
+programming language approach, which enables one to target multiple devices using the same programming model, and
+therefore to have a cleaner, portable, and more readable code.
+
+This is a hands-on tutorial. The real learning will happen as attendees write code. The format will be short
+presentations followed by hands-on exercises. Hence, attendees will require their own laptop to perform the hands-on
+exercises.
diff --git a/content/events/2025/introduction-to-certifiable-general-purpose-gpu-programming-for-safety-critical-systems-using-khronos-apis.md b/content/events/2025/introduction-to-certifiable-general-purpose-gpu-programming-for-safety-critical-systems-using-khronos-apis.md
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+---
+contributor: max
+date: '2025-01-20T14:46:00'
+starts: '2025-01-20T13:00:00+01:00'
+ends: '2025-01-20T16:30:00+01:00'
+title: 'Introduction to Certifiable General Purpose GPU Programming for Safety-Critical Systems using Khronos APIs'
+external_url: 'https://www.hipeac.net/2025/barcelona/#/program/sessions/8161/'
+---
+
+Tutorial at HiPEAC 2025 by Leonidas Kosmidis, Barcelona Supercomputing Center (BSC)
diff --git a/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 b/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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+---
+contributor: max
+date: '2024-12-19T09:43:10'
+title: 'Implementation of Two Numerical Solvers for the Study of Non-Equilibrium Gas Dynamics on GPU-Accelerated Platforms using SYCL'
+external_url: 'https://ruor.uottawa.ca/items/cb39b8e3-9904-4a65-89bf-5414d364e759'
+authors:
+  - El-Ghotmi, Osman
+tags:
+  - sycl
+  - gpu
+  - portability
+---
+
+The application of GPUs has extended beyond traditional graphics rendering because their parallel processing
+capabilities can accelerate many general-purpose tasks, such as machine learning and scientific computing. This thesis
+presents the implementation of two numerical solvers for the solution of non-equilibrium gas flows. It also demonstrates
+the computational performance of the two solvers when developed to target GPU-based supercomputers using the SYCL
+programming model. The first solver incorporates a novel ray-tracing technique and accurate mathematical relations to
+efficiently compute any observable property of free-molecular flow past convex shapes (FMFC). It computes integrals of
+the Maxwell-Boltzmann distribution function to create an algorithm that quickly evaluates any moment of the local
+particle-velocity distribution. This highly efficient technique is extended for GPUs to accelerate the computation of
+accurate results. Results produced with the solver serve as robust benchmarks in the validation of other scientific
+models that describe fluid motion in non-equilibrium regimes. The second solver extends a CPU-based implementation of
+the discontinuous Galerkin Hancock (DGH) method into an efficient GPU code. The DGH scheme is a high-order numerical
+method that solves hyperbolic partial differential equations (PDEs) with stiff source terms. This class of equations is
+common in many models that are used to describe non-equilibrium gas flows. The GPU implementation of the DGH solver that
+is presented in this work provides a computationally efficient and numerically accurate method to compute the solution
+for these models. Results produced by the FMFC and DGH solvers showcase their accuracy and parallel scalability as
+efficient GPU algorithms. Furthermore, the effectiveness of the FMFC solver as a validation tool is demonstrated by
+producing benchmarks to confirm the accuracy of scientific models that are solved with numerical schemes such as DGH.