Tasks Fairness Scheduler for GPU

Nowadays GPU clusters are available in almost every data processing center. Their GPUs are typically shared by different applications that might have different processing needs and/or different levels of priority. As current GPUs do not support hardware-based preemption mechanisms, it is not possible to ensure the required Quality of Service (QoS) when application kernels are offloaded to devices. In this work, we present an efficient software preemption mechanism with low overhead that evicts and relaunches GPU kernels to provide support to different preemptive scheduling policies. We also propose a new fairness-based scheduler named Fair and Responsive Scheduler, (FRS), that takes into account the current value of the kernels slowdown to both select the new kernel to be launched and establish the time interval it is going to run (quantum).Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

A Framework For TV Logos Learning Using Linear Inverse Diffusion Filters For Noise Removal

Different logotypes represent significant cues for video annotations. A combination of temporal and spatial segmentation methods can be used for logo extraction from various video contents. To achieve this segmentation, pixels with low variation of intensity over time are detected. Static backgrounds can become spurious parts of these logos. This paper offers a new way to use several segmentations of logos to learn new logo models from which noise has been removed. First, we group segmented logos of similar appearances into different clusters. Then, a model is learned for each cluster that has a minimum number of members. This is done by applying a linear inverse diffusion filter to all logos in each cluster. Our experiments demonstrate that this filter removes most of the noise that was added to the logo during segmentation and it successfully copes with misclassified logos that have been wrongly added to a cluster

CUVLE: Variable-Length Encoding on CUDA

Data compression is the process of representing information in a compact form, in order to reduce the storage requirements and, hence, communication bandwidth. It has been one of the critical enabling technologies for the ongoing digital multimedia revolution for decades. In the variable-length encoding (VLE) compression method, most frequently occurring symbols are replaced by codes with shorter lengths. As it is a common strategy in many compression applications, efficient parallel implementations of VLE are very desirable. In this paper we present CUVLE, a GPU implementation of VLE on CUDA. Our approach is on average more than 20 and 2 times faster than the corresponding CPU serial implementation and the only known state-of-the-art GPU implementation, respectively.Junta de Andalucía, TIC-1692. Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tec

A Hybrid Piece-Wise Slowdown Model for Concurrent Kernel Execution on GPU

Current execution of kernels on GPUs allows improving the use of hardware resources and reducing the execution time of co-executed kernels. In addition, efficient kernel-oriented scheduling policies pursuing criteria based on fairness or Quality of Service can be implemented. However, achieved co-executing performance strongly depends on how GPU resources are partitioned between kernels. Thus, precise slowdown models that predict accurate co-execution performance must be used to fulfill scheduling policy requirements. Most recent slowdown models work with Spatial Multitask (SMT) partitioning, where Stream Multiprocessors (SMs) are distributed among tasks. In this work, we show that Simultaneous Multikernel (SMK) partitioning, where kernels share the SMs, obtains better performance. However, kernel interference in SMK occurs not only in global memory, as in the SMT case, but also within the SM, leading to high prediction errors. Here, we propose a modification of a previous state-of-the-art slowdown model to reduce median prediction error from 27.92% to 9.50%. Moreover, this new slowdown model is used to implement a scheduling policy that improves fairness by 1.41x on average compared to even partitioning, whereas previous models reach only 1.21x on average.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech P18-FR-3130 UMA20-FEDERJA-059 PID2019-105396RB-I0

Efficient OpenCL-based concurrent tasks offloading on accelerators

Current heterogeneous platforms with CPUs and accelerators have the ability to launch several independent tasks simultaneously, in order to exploit concurrency among them. These tasks typically consist of data transfer commands and kernel computation commands. In this paper we develop a runtime approach to optimize the concurrency between data transfers and kernel computation commands in a multithreaded scenario where each CPU thread offloads tasks to the accelerator. It deploys a heuristic based on a temporal execution model for concurrent tasks. It is able to establish a near-optimal task execution order that significantly reduces the total execution time, including data transfers. Our approach has been evaluated employing five different benchmarks composed of dominant kernel and dominant transfer real tasks. In these experiments our heuristic achieves speedups up to 1.5x in AMD R9 and NVIDIA K20c accelerators and 1.3x in an Intel Xeon Phi (KNC) device.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Low-textured regions detection for improving stereoscopy algorithms

The main goal of stereoscopy algorithms is the calculation of the disparity map between two frames corresponding to the same scene, and captured simultaneously by two different cameras. The different position (disparity) where common scene points are projected in both camera sensors can be used to calculate the depth of the scene point. Many algorithms calculate the disparity of corresponding points in both frames relying on the existence of similar textured areas around the pixels to be analyzed. Unfortunately, real images present large areas with low texture, which hinder the calculation of the disparity map. In this paper we present a method that employs a set of local textures to build a classifier that is able to select reliable pixels where the disparity can be accurately calculated, improving the precision of the scene map obtained by the stereoscopic technique.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech. Ministry of Education and Science of Spain under contract TIN2010-16144 and Junta de Andalucía under contract TIC-1692

Pre-Ictal Phase Detection with SVMs

Over 50 million persons worldwide are affected by epilepsy. Epilepsy is a brain disorder known for sudden, unexpected transitions from normal to pathological behavioral states called epileptic seizures. Epilepsy poses a significant burden to society due to associated healthcare cost to treat and control the unpredictable and spontaneous occurrence of seizures. There is a need for a quick screening process that could help neurologist diagnose and determine the patient’s treatment. Electroencephalogram has been traditionally used to diagnose patients by evaluating those brain functions that may correspond to epilepsy. The objective of this paper is to implement a novel detection technique of pre-ictal state that announces epileptic seizures from the online EEG data analysis. Unlike most published methods, that are aimed to distinguish only the normal from the epilepsy state, in this work the pre-ictal state is introduced as a new patient status, thus differentiating three possible states: normal (healthy), pre-ictal and epileptic seizure. In this manner, the patient should get timely alert about the possible seizure attack so that she/he can stop with its activities and take safety precautions.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech. This work is partially supported by the Ministry of Education and Science of Spain under contract TIN2010-16144 and Junta de Andalucía under contract TIC-1692

Inbreeding, native American ancestry and child mortality:Linking human selection and paediatric medicine

The children of related parents show increased risk of early mortality. The Native American genome typically exhibits long stretches of homozygosity, and Latin Americans are highly heterogeneous regarding the individual burden of homozygosity, the proportion and the type of Native American ancestry. We analysed nationwide mortality and genome-wide genotype data from admixed Chileans to investigate the relationship between common causes of child mortality, homozygosity and Native American ancestry. Results from two-stage linear-Poisson regression revealed a strong association between the sum length of runs of homozygosity (SROH) above 1.5 Megabases (Mb) in each genome and mortality due to intracranial non-traumatic haemorrhage of foetus and newborn (5% increased risk of death per Mb in SROH, P = 1 × 10(−3)) and disorders related to short gestation and low birth weight (P = 3 × 10(−4)). The major indigenous populations in Chile are Aymara–Quechua in the north of the country and the Mapuche–Huilliche in the south. The individual proportion of Aymara–Quechua ancestry was associated with an increased risk of death due to anencephaly and similar malformations (P = 4 × 10(−5)), and the risk of death due to Edwards and Patau trisomy syndromes decreased 4% per 1% Aymara–Quechua ancestry proportion (P = 4 × 10(−4)) and 5% per 1% Mapuche–Huilliche ancestry proportion (P = 2 × 10(−3)). The present results suggest that short gestation, low birth weight and intracranial non-traumatic haemorrhage mediate the negative effect of inbreeding on human selection. Independent validation of the identified associations between common causes of child death, homozygosity and fine-scale ancestry proportions may inform paediatric medicine

Inbreeding, Native American ancestry and child mortality: linking human selection and paediatric medicine

The children of related parents show increased risk of early mortality. The Native American genome typically exhibits long stretches of homozygosity, and Latin Americans are highly heterogeneous regarding the individual burden of homozygosity, the proportion and the type of Native American ancestry. We analysed nationwide mortality and genome-wide genotype data from admixed Chileans to investigate the relationship between common causes of child mortality, homozygosity and Native American ancestry. Results from two-stage linear-Poisson regression revealed a strong association between the sum length of runs of homozygosity (SROH) above 1.5 Megabases (Mb) in each genome and mortality due to intracranial non-traumatic haemorrhage of foetus and newborn (5% increased risk of death per Mb in SROH, P = 1 × 10−3) and disorders related to short gestation and low birth weight (P = 3 × 10−4). The major indigenous populations in Chile are Aymara–Quechua in the north of the country and the Mapuche–Huilliche in the south. The individual proportion of Aymara–Quechua ancestry was associated with an increased risk of death due to anencephaly and similar malformations (P = 4 × 10−5), and the risk of death due to Edwards and Patau trisomy syndromes decreased 4% per 1% Aymara–Quechua ancestry proportion (P = 4 × 10−4) and 5% per 1% Mapuche–Huilliche ancestry proportion (P = 2 × 10−3). The present results suggest that short gestation, low birth weight and intracranial non-traumatic haemorrhage mediate the negative effect of inbreeding on human selection. Independent validation of the identified associations between common causes of child death, homozygosity and fine-scale ancestry proportions may inform paediatric medicine.Fil: Koenigstein, Fabienne. Ruprecht Karls Universitat Heidelberg; AlemaniaFil: Boekstegers, Felix. Ruprecht Karls Universitat Heidelberg; AlemaniaFil: Wilson, James F.. University of Edinburgh; Reino UnidoFil: Fuentes Guajardo, Macarena. Universidad de Tarapacá; ChileFil: Gonzalez-Jose, Rolando. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Centro Nacional Patagónico. Instituto Patagónico de Ciencias Sociales y Humanas; ArgentinaFil: Bedoya Berrío, Gabriel. Universidad de Antioquia; ColombiaFil: Bortolini, Maria Cátira. Universidade Federal do Rio Grande do Sul; BrasilFil: Acuña Alonzo, Victor. Instituto Nacional de Antropología e Historia. Escuela Nacional de Antropología e Historia; MéxicoFil: Gallo, Carla. Universidad Peruana Cayetano Heredia; PerúFil: Ruiz-Linares, Andres. Fudan University; China. Aix-Marseille Université; Francia. Centre National de la Recherche Scientifique; Francia. University College London; Reino UnidoFil: Rothhammer, Francisco. Universidad de Tarapaca. Instituto de Alta Investigación; ChileFil: Lorenzo Bermejo, Justo. Ruprecht Karls Universitat Heidelberg; Alemani

Enfrentando los riesgos socionaturales

El objetivo del libro es comprender la magnitud de los Riesgos Socionaturales en México y Latinoamérica, para comprender el peligro que existe por algún tipo de desastre, ya sea inundaciones, sismos, remoción en masa, entre otros, además conocer qué medidas preventivas, correctivas y de contingencias existen para estar atentos ante alguna señal que la naturaleza esté enviando y así evitar alguna catástrofe. El libro se enfoca en los aspectos básicos de análisis de los peligros, escenarios de riesgo, vulnerabilidad y resiliencia, importantes para la gestión prospectiva o preventiva