Concept

Mach (kernel)

Related publications (35)

Quantum Chemistry Meets Machine Learning

Alberto Fabrizio, Benjamin André René Meyer, Raimon Fabregat I De Aguilar-Amat

In this account, we demonstrate how statistical learning approaches can be leveraged across a range of different quantum chemical areas to transform the scaling, nature, and complexity of the problems that we are tackling. Selected examples illustrate the ...

SWISS CHEMICAL SOC2019

Advancing the State of Network Switch ASIC Offloading in the Linux Kernel

Andy Roulin

Modern data-center network operating systems rely on proprietary user-space daemons wrapping SDKs from switch vendors. Linux-based variants of these operating systems have benefited from increasing and simplified dataplane offloading support in recent year ...

2018

Evolving Takagi-Sugeno model based on online Gustafson-Kessel algorithm and kernel recursive least square method

Soroosh Shafieezadeh Abadeh

In this paper, we introduce an evolving system utilizing sparse weighted kernel least square as local models and online Gustafson-Kessel clustering algorithm for structure identification. Our proposed online clustering algorithm forms elliptical clusters w ...

2016

The IX Operating System: Combining Low Latency, High Throughput, and Efficiency in a Protected Dataplan

Edouard Bugnion, Christos Kozyrakis, Georgios Prekas, Mia Primorac, Ana Klimovic

The conventional wisdom is that aggressive networking requirements, such as high packet rates for small messages and μs-scale tail latency, are best addressed outside the kernel, in a user-level networking stack. We present ix, a dataplane operating system ...

Association for Computing Machinery2016

A Sparse Reformulation of the Green's Function Formalism Allows Efficient Simulations of Morphological Neuron Models

Marc-Oliver Gewaltig, Willem Anna Mark Wybo, Benjamin Torben-Nielsen, Daniele Boccalini

We prove that when a class of partial differential equations, generalized from the cable equation, is defined on tree graphs and the inputs are restricted to a spatially discrete, well chosen set of points, the Green's function (GF) formalism can be rewrit ...

Massachusetts Institute of Technology Press2015

A Probabilistic Kernel Method for Human Mobility Prediction with Smartphones

Daniel Gatica-Perez

Human mobility prediction is an important problem which has a large num- ber of applications, especially in context-aware services. This paper presents a study on location prediction using smartphone data, in which we address mod- eling and application asp ...

2015

The Movement Error Rate for Evaluation of Machine Learning Methods for sEMG-based Hand Movement Classification

Barbara Caputo

There has been increasing interest in applying learning algorithms to improve the dexterity of myoelectric prostheses. In this work, we present a large-scale benchmark evaluation on the second iteration of the publicly released NinaPro database, which cont ...

2014

Rebasing I/O for Scientific Computing: Leveraging Storage Class Memory in an IBM BlueGene/Q Supercomputer

Felix Schürmann, Pramod Shivaji Kumbhar, Miguel Angel Gila Arrondo, Davide Tacchella, Alessandro Curioni, Fabien Jonathan Delalondre, John Anthony Biddiscombe, Peter Morjan, Blake Fitch, Bernard Metzler, Lars Schneidenbach, Robert Germain

Storage class memory is receiving increasing attention for use in HPC systems for the acceleration of intensive IO operations. We report a particular instance using SLC FLASH memory integrated with an IBM BlueGene/Q supercomputer at scale (Blue Gene Active ...

Springer2014

IX: A Protected Dataplane Operating System for High Throughput and Low Latency

Edouard Bugnion, Christos Kozyrakis, Georgios Prekas, Ana Klimovic

The conventional wisdom is that aggressive networking requirements, such as high packet rates for small messages and microsecond-scale tail latency, are best addressed outside the kernel, in a user-level networking stack. We present IX, a dataplane operati ...

USENIX2014

Fast O(1) Bilateral Filtering Using Trigonometric Range Kernels

Michaël Unser, Daniel Sage, Kunal Narayan Chaudhury

It is well known that spatial averaging can be realized (in space or frequency domain) using algorithms whose complexity does not scale with the size or shape of the filter. These fast algorithms are generally referred to as constant-time or O(1) algorithm ...

IEEE2011

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