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Batched linear solvers play a vital role in computational sciences,especially in the fields of plasma physics and combustion simulations. With theimminent deployment of the Aurora Supercomputer and other upcoming systemsequipped with Intel GPUs, there is a compelling demand to expand thecapabilities of these solvers for Intel GPU architectures.  In this paper, we present our efforts in porting and optimizing the batchediterative solvers on Intel GPUs using the SYCL programming model. These newsolvers achieve impressive performance on the Intel GPU Max 1550s (PonteVecchio GPUs) which surpass our previous CUDA implementation on NVIDIA H100GPUs by an average of 2.4x for the PeleLM application inputs. The batchedsolvers are ready for production use in real-world scientific applicationsthrough the Ginkgo library, complementing the performance portability of thebatched functionality of Ginkgo.

Porting Batched Iterative Solvers onto Intel GPUs with SYCL