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Galindo Garre, Víctor

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Galindo Garre, Víctor
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Ingeniería y Tecnología de Computadores
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    An autotuning approach to select the inter-GPU communication library on heterogeneous systems
    (Springer, 2024-12-12) Cámara, Jesús; Cuenca Muñoz, Antonio Javier; Cuenca, Javier; Boratto, Murilo; Vicente Jaén, Arturo; Galindo Garre, Víctor; Ingeniería y Tecnología de Computadores
    In this work, an automatic optimisation approach for parallel routines on multi-GPU systems is presented. Several inter-GPU communication libraries (such as CUDA- Aware MPI or NCCL) are used with a set of routines to perform the numerical oper- ations among the GPUs located on the compute nodes. The main objective is the selection of the most appropriate communication library, the number of GPUs to be used and the workload to be distributed among them in order to reduce the cost of data movements, which represent a large percentage of the total execution time. To this end, a hierarchical modelling of the execution time of each routine to be opti- mised is proposed, combining experimental and theoretical approaches. The results show that near-optimal decisions are taken in all the scenarios analysed.
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    Towards a hierarchical approach for autotuning task-based libraries
    (Springer, 2025) Cámara, Jesús; Cuenca Muñoz, Antonio Javier; Boratto, Murilo; Vicente Jaén, Arturo; Galindo Garre, Víctor; Ingeniería y Tecnología de Computadores; Facultades de la UMU::Facultad de Informática
    This work proposes a hierarchical approach to reduce the training time of task-based routines by reusing previously obtained autotuning information. This approach has been integrated into a working prototype of Chameleon, a dense linear algebra software whose tile-based routines are executed on the available computational resources by means of a runtime system. The results show that this approach provides a high degree of scalability to the entire self-optimization process, achieving a reduction in training time of up to 80% and an appropriate selection of values for the adjustable parameters.
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