System-Level Design of Energy-Proportional Many-Core Servers for Exascale Computing

Continuous advances in manufacturing technologies are enabling the development of more powerful and compact high-performance computing (HPC) servers made of many-core processing architectures. However, this soaring demand for computing power in the last years has grown faster than emiconductor technology evolution can sustain, and has produced as collateral undesirable effect a surge in power consumption and heat density in these new HPC servers, which result on significant performance degradation. In this keynote, I advocate to completely revise the current HPC server architectures. In particular, inspired by the mammalian brain, I propose to design a disruptive three-dimensional (3D) computing server architecture that overcomes the prevailing worst-case power and cooling provisioning paradigm for servers. This new 3D server design champions a new system-level thermal modeling, which can be used by novel proactive energy controllers for detailed heat and energy management in many-core HPC servers, thanks to micro-scale liquid cooling. Then, I will show the impact of new near-threshold computing architectures on server design, and how we can integrate new on-chip microfluidic fuel cell networks to enable energy-scalability in future generations of many-core HPC servers targeting Exascale computing.Universidad de Málaga, Campus de Excelencia Internacional Andalucía Tech

Optimisation of post-drawing treatments by means of neutron diffraction

The mechanical properties and the durability of cold-drawn eutectoid wires (especially in aggressive environments) are influenced by the residual stresses generated during the drawing process. Steelmakers have devised procedures (thermomechanical treatments after drawing) attempting to relieve them in order to improve wire performance. In thiswork neutron diffraction measurements have been used to ascertain the role of temperature and applied force – during post-drawing treatments – on the residual stresses of five rod batches with different treatments. The results show that conventional thermomechanical treatments are successful in relieving the residual stresses created by cold-drawing, although these procedures can be improved by changing the temperature or the stretching force. Knowledge of the residual stress profiles after these changes is a useful tool to improve the thermomechanical treatments instead of the empirical procedures used currently

A Developmental Perspective on College & Workplace Readiness

Reviews research on and identifies the physical, psychological, social, cognitive, and spiritual competencies high school graduates need to transition into college, the workplace, and adulthood. Includes strategies for meeting disadvantaged youths' needs

Stochastic Shell Models driven by a multiplicative fractional Brownian--motion

We prove existence and uniqueness of the solution of a stochastic shell--model. The equation is driven by an infinite dimensional fractional Brownian--motion with Hurst--parameter $H\in (1/2,1)$, and contains a non--trivial coefficient in front of the noise which satisfies special regularity conditions. The appearing stochastic integrals are defined in a fractional sense. First, we prove the existence and uniqueness of variational solutions to approximating equations driven by piecewise linear continuous noise, for which we are able to derive important uniform estimates in some functional spaces. Then, thanks to a compactness argument and these estimates, we prove that these variational solutions converge to a limit solution, which turns out to be the unique pathwise mild solution associated to the shell--model with fractional noise as driving process.Comment: 23 page

Random attractors for stochastic evolution equations driven by fractional Brownian motion

The main goal of this article is to prove the existence of a random attractor for a stochastic evolution equation driven by a fractional Brownian motion with $H\in (1/2,1)$. We would like to emphasize that we do not use the usual cohomology method, consisting of transforming the stochastic equation into a random one, but we deal directly with the stochastic equation. In particular, in order to get adequate a priori estimates of the solution needed for the existence of an absorbing ball, we will introduce stopping times to control the size of the noise. In a first part of this article we shall obtain the existence of a pullback attractor for the non-autonomous dynamical system generated by the pathwise mild solution of an nonlinear infinite-dimensional evolution equation with non--trivial H\"older continuous driving function. In a second part, we shall consider the random setup: stochastic equations having as driving process a fractional Brownian motion with $H\in (1/2,1)$. Under a smallness condition for that noise we will show the existence and uniqueness of a random attractor for the stochastic evolution equation

Pathwise solutions and attractors for retarded SPDEs with time smooth diffusion coefficients

In this paper we study the longtime dynamics of mild solutions to retarded stochastic evolution systems driven by a Hilbert-valued Brownian motion. As a preparation for this purpose we have to show the existence and uniqueness of a cocycle solution of such an equation. We do not assume that the noise is given in additive form or that it is a very simple multiplicative noise. However, we need some smoothing property for the coefficient in front of the noise. The main idea of this paper consists of expressing the stochastic integral in terms of non-stochastic integrals and the noisy path by using an integration by parts. This latter term causes that in a first moment only a local mild solution can be obtained, since in order to apply the Banach fixed point theorem it is crucial to have the H\"older norm of the noisy path to be sufficiently small. Later, by using appropriate stopping times, we shall derive the existence and uniqueness of a global mild solution. Furthermore, the asymptotic behavior is investigated by using the {\it Random Dynamical Systems theory}. In particular, we shall show that the global mild solution generates a random dynamical system that, under an appropriate smallness condition for the time lag, have associated a random attractor

Separating Topological Noise from Features Using Persistent Entropy

Topology is the branch of mathematics that studies shapes and maps among them. From the algebraic definition of topology a new set of algorithms have been derived. These algorithms are identified with “computational topology” or often pointed out as Topological Data Analysis (TDA) and are used for investigating high-dimensional data in a quantitative manner. Persistent homology appears as a fundamental tool in Topological Data Analysis. It studies the evolution of k−dimensional holes along a sequence of simplicial complexes (i.e. a filtration). The set of intervals representing birth and death times of k−dimensional holes along such sequence is called the persistence barcode. k−dimensional holes with short lifetimes are informally considered to be topological noise, and those with a long lifetime are considered to be topological feature associated to the given data (i.e. the filtration). In this paper, we derive a simple method for separating topological noise from topological features using a novel measure for comparing persistence barcodes called persistent entropy.Ministerio de Economía y Competitividad MTM2015-67072-