5 papers
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…
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…
The Cambrian Explosion of Mixed-Precision Matrix Multiplication for Quantized Deep Learning Inference
Héctor MartÃnez, Adrián Castelló, Francisco D. Igual +1
Recent advances in deep learning (DL) have led to a shift from traditional 64-bit floating point (FP64) computations toward reduced-precision formats, such as FP16, BF16, and 8- or…
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…
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…