Optimizing egalitarian performance in the side-effects model of colocation for data center resource management

In data centers, up to dozens of tasks are colocated on a single physical machine. Machines are used more efficiently, but tasks' performance deteriorates, as colocated tasks compete for shared resources. As tasks are heterogeneous, the resulting performance dependencies are complex. In our previous work [18] we proposed a new combinatorial optimization model that uses two parameters of a task - its size and its type - to characterize how a task influences the performance of other tasks allocated to the same machine. In this paper, we study the egalitarian optimization goal: maximizing the worst-off performance. This problem generalizes the classic makespan minimization on multiple processors (P||Cmax). We prove that polynomially-solvable variants of multiprocessor scheduling are NP-hard and hard to approximate when the number of types is not constant. For a constant number of types, we propose a PTAS, a fast approximation algorithm, and a series of heuristics. We simulate the algorithms on instances derived from a trace of one of Google clusters. Algorithms aware of jobs' types lead to better performance compared with algorithms solving P||Cmax. The notion of type enables us to model degeneration of performance caused by using standard combinatorial optimization methods. Types add a layer of additional complexity. However, our results - approximation algorithms and good average-case performance - show that types can be handled efficiently.Comment: Author's version of a paper published in Euro-Par 2017 Proceedings, extends the published paper with addtional results and proof

Neural population tuning links visual cortical anatomy to human visual perception.

The anatomy of cerebral cortex is characterized by two genetically independent variables, cortical thickness and cortical surface area, that jointly determine cortical volume. It remains unclear how cortical anatomy might influence neural response properties and whether such influences would have behavioral consequences. Here, we report that thickness and surface area of human early visual cortices exert opposite influences on neural population tuning with behavioral consequences for perceptual acuity. We found that visual cortical thickness correlated negatively with the sharpness of neural population tuning and the accuracy of perceptual discrimination at different visual field positions. In contrast, visual cortical surface area correlated positively with neural population tuning sharpness and perceptual discrimination accuracy. Our findings reveal a central role for neural population tuning in linking visual cortical anatomy to visual perception and suggest that a perceptually advantageous visual cortex is a thinned one with an enlarged surface area

Random walk with barriers: Diffusion restricted by permeable membranes

Restrictions to molecular motion by barriers (membranes) are ubiquitous in biological tissues, porous media and composite materials. A major challenge is to characterize the microstructure of a material or an organism nondestructively using a bulk transport measurement. Here we demonstrate how the long-range structural correlations introduced by permeable membranes give rise to distinct features of transport. We consider Brownian motion restricted by randomly placed and oriented permeable membranes and focus on the disorder-averaged diffusion propagator using a scattering approach. The renormalization group solution reveals a scaling behavior of the diffusion coefficient for large times, with a characteristically slow inverse square root time dependence. The predicted time dependence of the diffusion coefficient agrees well with Monte Carlo simulations in two dimensions. Our results can be used to identify permeable membranes as restrictions to transport in disordered materials and in biological tissues, and to quantify their permeability and surface area.Comment: 8 pages, 3 figures; origin of dispersion clarified, refs adde

Preface

Preface - The second International Conference on Mathematical Modeling in Physical Sciences (IC-MSQUARE) took place at Prague, Czech Republic, from Sunday 1 September to Thursday 5 September 2013

The Frequency of Visually Induced Gamma-Band Oscillations Depends on the Size of Early Human Visual Cortex

The structural and functional architecture of the human brain is characterized by considerable variability, which has consequences for visual perception. However, the neurophysiological events mediating the relationship between interindividual differences in cortical surface area and visual perception have, until now, remained unknown. Here, we show that the retinotopically defined surface areas of central V1 and V2 are correlated with the peak frequency of visually induced oscillations in the gamma band, as measured with magnetoencephalography. Gamma-band oscillations are thought to play an important role in visual processing. We propose that individual differences in macroscopic gamma frequency may be attributed to interindividual variability in the microscopic architecture of visual cortex

Clonality and evolutionary history of rhabdomyosarcoma.

To infer the subclonality of rhabdomyosarcoma (RMS) and predict the temporal order of genetic events for the tumorigenic process, and to identify novel drivers, we applied a systematic method that takes into account germline and somatic alterations in 44 tumor-normal RMS pairs using deep whole-genome sequencing. Intriguingly, we find that loss of heterozygosity of 11p15.5 and mutations in RAS pathway genes occur early in the evolutionary history of the PAX-fusion-negative-RMS (PFN-RMS) subtype. We discover several early mutations in non-RAS mutated samples and predict them to be drivers in PFN-RMS including recurrent mutation of PKN1. In contrast, we find that PAX-fusion-positive (PFP) subtype tumors have undergone whole-genome duplication in the late stage of cancer evolutionary history and have acquired fewer mutations and subclones than PFN-RMS. Moreover we predict that the PAX3-FOXO1 fusion event occurs earlier than the whole genome duplication. Our findings provide information critical to the understanding of tumorigenesis of RMS

Effective Connectivity within Human Primary Visual Cortex Predicts Interindividual Diversity in Illusory Perception

Visual perception depends strongly on spatial context. A classic example is the tilt illusion where the perceived orientation of a central stimulus differs from its physical orientation when surrounded by tilted spatial contexts. Here we show that such contextual modulation of orientation perception exhibits trait-like interindividual diversity that correlates with interindividual differences in effective connectivity within human primary visual cortex. We found that the degree to which spatial contexts induced illusory orientation perception, namely, the magnitude of the tilt illusion, varied across healthy human adults in a trait-like fashion independent of stimulus size or contrast. Parallel to contextual modulation of orientation perception, the presence of spatial contexts affected effective connectivity within human primary visual cortex between peripheral and foveal representations that responded to spatial context and central stimulus, respectively. Importantly, this effective connectivity from peripheral to foveal primary visual cortex correlated with interindividual differences in the magnitude of the tilt illusion. Moreover, this correlation with illusion perception was observed for effective connectivity under tilted contextual stimulation but not for that under iso-oriented contextual stimulation, suggesting that it reflected the impact of orientation-dependent intra-areal connections. Our findings revealed an interindividual correlation between intra-areal connectivity within primary visual cortex and contextual influence on orientation perception. This neurophysiological-perceptual link provides empirical evidence for theoretical proposals that intra-areal connections in early visual cortices are involved in contextual modulation of visual perception