Abstract
We show the benefits of the novel MLIR compiler technology to the generation of code from a DSL, namely EasyML used in openCARP, a widely used simulator in the cardiac electrophysiology community. Building on an existing work that deeply modified openCARP’s native DSL code generator to enable efficient vectorized CPU code, we extend the code generation for GPUs (Nvidia CUDA and AMD ROCm). Generating optimized code for different accelerators requires specific optimizations and we review how MLIR has been used to enable multi-target code generation from an integrated generator. Experiments conducted on the 48 ionic models provided by openCARP show that the GPU code executes \(3.17\times \) faster and delivers more than \(7\times \) FLOPS per watt than the vectorized CPU code, on an Nvidia A100 GPU versus a 36-cores AVX-512 Intel CPU.
T. T. Jost and A. Thangamani—Both authors contributed equally to the paper.
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Acknowledgments
This work was supported by the European High-Performance Computing Joint Undertaking EuroHPC under grant agreement No 955495 (MICROCARD), co-funded by the Horizon 2020 programme of the European Union (EU), and France, Italy, Germany, Austria, Norway, and Switzerland (https://microcard.eu).
Some experiments presented in this paper were carried out using the PlaFRIM experimental test bed, supported by Inria, CNRS (LABRI and IMB), Université de Bordeaux, Bordeaux INP and Conseil Régional d’Aquitaine (https://plafrim.fr). Some experiments presented in this paper were carried out using the Grid’5000 testbed, supported by a scientific interest group hosted by Inria and including CNRS, RENATER and several Universities as well as other organizations (https://www.grid5000.fr).
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Trevisan Jost, T., Thangamani, A., Colin, R., Loechner, V., Genaud, S., Bramas, B. (2023). GPU Code Generation of Cardiac Electrophysiology Simulation with MLIR. In: Cano, J., Dikaiakos, M.D., Papadopoulos, G.A., Pericàs, M., Sakellariou, R. (eds) Euro-Par 2023: Parallel Processing. Euro-Par 2023. Lecture Notes in Computer Science, vol 14100. Springer, Cham. https://doi.org/10.1007/978-3-031-39698-4_37
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