Search results for: Ignacio Arnaldo

Items from 1 to 8 out of 8 results

chapter

Power Profiling-Guided Floorplanner for Thermal Optimization in 3D Multiprocessor Architectures

Ignacio Arnaldo, José L. Risco-Martín, José L. Ayala, J. Ignacio Hidalgo

Lecture Notes in Computer Science > Integrated Circuit and System Design. Power and Timing Modeling, Optimization, and Simulation > 11-21

3D integration has become one of the most promising techniques for the integration future multi-core processors, since it improves performance and reduces power consumption by decreasing global wire length. However, 3D integration causes serious thermal problems since the closer proximity of heat generating dies makes existing thermal hotspots more severe. Thermal-aware floorplanners can play an important...

chapter

AI^2: Training a Big Data Machine to Defend

Kalyan Veeramachaneni, Ignacio Arnaldo, Vamsi Korrapati, Constantinos Bassias, more

2016 IEEE 2nd International Conference on Big Data Security on Cloud (BigDataSecurity), IEEE International Conference on High Performance and Smart Computing (HPSC), and IEEE International Conference on Intelligent Data and Security (IDS) > 49 - 54

2016 IEEE 2nd International Conference on Big Data Security on Cloud (BigDataSecurity), IEEE International Conference on High Performance and Smart Computing (HPSC) and IEEE International Conference on Intelligent Data and Security (IDS)

We present AI2, an analyst-in-the-loop security system where Analyst Intuition (AI) is put together with state-of-the-art machine learning to build a complete end-to-end Artificially Intelligent solution (AI). The system presents four key features: a big data behavioral analytics platform, an outlier detection system, a mechanism to obtain feedback from security analysts, and a supervised learning...

article

Bring Your Own Learner: A Cloud-Based, Data-Parallel Commons for Machine Learning

Ignacio Arnaldo, Kalyan Veeramachaneni, Andrew Song, Una-May O'Reilly

IEEE Computational Intelligence Magazine > 2015 > 10 > 1 > 20 - 32

Abstract-We introduce FCUBE, a cloud-based framework that enables machine learning researchers to contribute their learners to its community-shared repository. FCUBE exploits data parallelism in lieu of algorithmic parallelization to allow its users to efficiently tackle large data problems automatically. It passes random subsets of data generated via resampling to multiple learners that it executes...

article

FlexGP

Kalyan Veeramachaneni, Ignacio Arnaldo, Owen Derby, Una-May O’Reilly

Journal of Grid Computing > 2015 > 13 > 3 > 391-407

We describe FlexGP, the first Genetic Programming system to perform symbolic regression on large-scale datasets on the cloud via massive data-parallel ensemble learning. FlexGP provides a decentralized, fault tolerant parallelization framework that runs many copies of Multiple Regression Genetic Programming, a sophisticated symbolic regression algorithm, on the cloud. Each copy executes with a different...

article

Blind optimisation problem instance classification via enhanced universal similarity metric

Iván Contreras, Ignacio Arnaldo, Natalio Krasnogor, J. Ignacio Hidalgo

Memetic Computing > 2014 > 6 > 4 > 263-276

The ultimate aim of Memetic Computing is the fully autonomous solution to complex optimisation problems. For a while now, the Memetic algorithms literature has been moving in the direction of ever increasing generalisation of optimisers initiated by seminal papers such as Krasnogor and Smith (IEEE Trans 9(5):474–488, 2005; Workshops Proceedings of the 2000 International Genetic and Evolutionary Computation...

article

Boosting the 3D thermal‐aware floorplanning problem through a master‐worker parallel MOEA

Ignacio Arnaldo, Alfredo Cuesta‐Infante, J. Manuel Colmenar, José L. Risco‐Martín, more

Concurrency and Computation: Practice and Experience > 25 > 8 > 1089 - 1103

The increasing transistor scale integration poses, among others, the thermal‐aware floorplanning problem consisting of how to place the hardware components in order to reduce overheating by dissipation. Because of the huge amount of feasible floorplans, most of the solutions found in the literature include an evolutionary algorithm for, either partially or completely, carrying out the task of floorplanning...

article

Matching island topologies to problem structure in parallel evolutionary algorithms

Ignacio Arnaldo, Iván Contreras, David Millán-Ruiz, J. Ignacio Hidalgo, more

Soft Computing > 2013 > 17 > 7 > 1209-1225

In the context of Parallel Evolutionary Algorithms, it has been shown that different population structures induce different search performances. Nevertheless, no work has shown a clear cut evidence that there is a correlation between the solver’s population structure and the problem’s network structure. In this work, we verify this correlation performing a clear and systematic analysis of a large...

chapter

Fast and scalable temperature-driven floorplan design in 3D MPSoCs

Ignacio Arnaldo, Alessandro Vicenzi, Jose L. Ayala, Jose L. Risco, more

2012 13th Latin American Test Workshop (LATW) > 1 - 6

2012 13th Latin American Test Workshop - LATW

Temperature-driven floorplaners have been recently proposed to alleviate the thermal problem in 3D multi-processor systems-on-chip (MPSoC). However, the proposed algorithms fail to provide fast placement of the modules when the complexity and the number of functional units in the stack increases. This paper proposes a fast and scalable CPU-GPU implementation of a multi-objective evolutionary algorithm...

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