Browsing by Author "Buchaca Prats, David"
Now showing items 1-12 of 12
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A highly parameterizable framework for Conditional Restricted Boltzmann Machine based workloads accelerated with FPGAs and OpenCL
Jaksic, Zoran; Cadenelli, Nicola; Buchaca Prats, David; Polo Bardés, Jordà; Berral García, Josep Lluís; Carrera Pérez, David (Elsevier, 2020-03-01)
Article
Open AccessConditional Restricted Boltzmann Machine (CRBM) is a promising candidate for a multidimensional system modeling that can learn a probability distribution over a set of data. It is a specific type of an artificial neural ... -
A multilayer extension of the similarity neural network
Buchaca Prats, David (Universitat Politècnica de Catalunya, 2014-11-24)
Master thesis
Open AccessAquest projecte ajunta idees de les radial basis functions, i el multilayer perceptron per a desenvolupar una altra arquitectura de xarxa neuronal artificial i un mètode per a poder-la entrenar. És una extensió de la ... -
Automatic generation of workload profiles using unsupervised learning pipelines
Buchaca Prats, David; Berral García, Josep Lluís; Carrera Pérez, David (2017-12-27)
Article
Open AccessThe complexity of resource usage and power consumption on cloud-based applications makes the understanding of application behavior through expert examination difficult. The difficulty increases when applications are seen ... -
Improving maritime traffic emission estimations on missing data with CRBMs
Gutiérrez Torre, Alberto; Berral García, Josep Lluís; Buchaca Prats, David; Guevara Vilardell, Marc; Soret, Albert; Carrera Pérez, David (Elsevier, 2020-07-07)
Article
Open AccessMaritime traffic emissions are a major concern to governments as they heavily impact the Air Quality in coastal cities. Ships use the Automatic Identification System (AIS) to continuously report position and speed among ... -
Learning workload behaviour models from monitored time-series for resource estimation towards data center optimization
Buchaca Prats, David (Universitat Politècnica de Catalunya, 2021-01-14)
Doctoral thesis
Open AccessIn recent years there has been an extraordinary growth of the demand of Cloud Computing resources executed in Data Centers. Modern Data Centers are complex systems that need management. As distributed computing systems ... -
Proactive container auto-scaling for cloud native machine learning services
Buchaca Prats, David; Berral García, Josep Lluís; Wang, Chen; Youssef, Alaa (Institute of Electrical and Electronics Engineers (IEEE), 2020)
Conference lecture
Open AccessUnderstanding the resource usage behaviors of the ever-increasing machine learning workloads are critical to cloud providers offering Machine Learning (ML) services. Capable of auto-scaling resources for customer workloads ... -
Sequence-to-sequence models for workload interference prediction on batch processing datacenters
Buchaca Prats, David; Marcual Medina, Joan; Berral García, Josep Lluís; Carrera Pérez, David (Elsevier, 2020-09)
Article
Open AccessCo-scheduling of jobs in data centers is a challenging scenario where jobs can compete for resources, leading to severe slowdowns or failed executions. Efficient job placement on environments where resources are shared ... -
Stopping criteria in contrastive divergence: Alternatives to the reconstruction error
Buchaca Prats, David; Romero Merino, Enrique; Mazzanti Castrillejo, Fernando Pablo; Delgado Pin, Jordi (2014)
Conference report
Open AccessRestricted Boltzmann Machines (RBMs) are general unsupervised learning devices to ascertain generative models of data distributions. RBMs are often trained using the Contrastive Divergence learning algorithm (CD), an ... -
Theta-Scan: Leveraging behavior-driven forecasting for vertical auto-scaling in container cloud
Berral García, Josep Lluís; Buchaca Prats, David; Herron Mulet, Claudia; Wang, Chen; Youssef, Alaa (Institute of Electrical and Electronics Engineers (IEEE), 2021)
Conference report
Open AccessDetection of behavior patterns on resource usage in containerized Cloud applications is necessary for proper resource provisioning. Applications can use CPU/Memory with repetitive patterns, following a trend over time ... -
TunaOil: A tuning algorithm strategy for reservoir simulation workloads
Albuquerque Portella, Felipe; Buchaca Prats, David; Rodrigues, José Roberto; Berral García, Josep Lluís (Elsevier, 2022-09)
Article
Open AccessReservoir simulations for petroleum fields and seismic imaging are known as the most demanding workloads for high-performance computing (HPC) in the oil and gas (O&G) industry. The optimization of the simulator numerical ... -
Weighted contrastive divergence
Romero Merino, Enrique; Mazzanti Castrillejo, Fernando Pablo; Delgado Pin, Jordi; Buchaca Prats, David (2019-06)
Article
Open AccessLearning algorithms for energy based Boltzmann architectures that rely on gradient descent are in general computationally prohibitive, typically due to the exponential number of terms involved in computing the partition ... -
You only run once: Spark auto-tuning from a single run
Buchaca Prats, David; Albuquerque Portella, Felipe; Costa, Carlos H. A.; Berral García, Josep Lluís (2020-12)
Article
Open AccessTuning configurations of Spark jobs is not a trivial task. State-of-the-art auto-tuning systems are based on iteratively running workloads with different configurations. During the optimization process, the relevant features ...