most citedTeaching Experiences using the RVfpga Package

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cs.DC2026

A comprehensive evaluation of spatial co-execution on GPUs using MPS and MIG technologies

Jorge Villarrubia, Luis Costero, Francisco D. Igual +1

To mitigate the increasingly common underutilization of computational resources in modern GPUs, spatial sharing methods enable multiple applications to use them simultaneously. Thi…

cs.DC2025

Leveraging Multi-Instance GPUs through moldable task scheduling

Jorge Villarrubia, Luis Costero, Francisco D. Igual +1

NVIDIA MIG (Multi-Instance GPU) allows partitioning a physical GPU into multiple logical instances with fully-isolated resources, which can be dynamically reconfigured. This work h…

cs.DC2025

Balanced segmentation of CNNs for multi-TPU inference

Jorge Villarrubia, Luis Costero, Francisco D. Igual +1

In this paper, we propose different alternatives for convolutional neural networks (CNNs) segmentation, addressing inference processes on computing architectures composed by multip…

cs.DC2025

Improving inference time in multi-TPU systems with profiled model segmentation

Jorge Villarrubia, Luis Costero, Francisco D. Igual +1

In this paper, we systematically evaluate the inference performance of the Edge TPU by Google for neural networks with different characteristics. Specifically, we determine that, g…

cs.DC2024

Energy efficiency optimization of task-parallel codes on asymmetric architectures

Luis Costero, Francisco D. Igual, Katzalin Olcoz +1

We present a family of policies that, integrated within a runtime task scheduler (Nanox), pursue the goal of improving the energy efficiency of task-parallel executions with no int…

cs.DC2024

Leveraging knowledge-as-a-service (KaaS) for QoS-aware resource management in multi-user video transcoding

Luis Costero, Francisco D. Igual, Katzalin Olcoz +1

The coexistence of parallel applications in shared computing nodes, each one featuring different Quality of Service (QoS) requirements, carries out new challenges to improve resour…