Using cloud infrastructure to facilitate data collection and conversion of HLA diagnostic data for the 18th International HLA and Immunogenetics Workshop

The International HLA and Immunogenetics Workshop (IHIW) is a recurring gathering of researchers, technologists and clinicians where participants contribute to collaborative projects with a variety of goals, and come to consensus on definitions and standards for representing HLA and immunogenic determinants. The collaborative and international nature of these workshops, combined with the multifaceted goals of several specific workshop components, necessitates the collection and curation of a wide assortment of data, as well as an adaptable platform for export and analysis. With the aim of ensuring data quality and creation of reusable datasets, specific standards and nomenclature conventions are continuously being developed, and are an integral part of IHIW. Here we present the 18th IHIW Database, a purpose-built and extensible cloud-based file repository and web application for collecting and analyzing project-specific data. This platform is based on open-source software and uses established HLA data standards and web technologies to facilitate de-centralized data repository ownership, reduce duplicated efforts, and promote continuity for future IHIWs

From preemptive to non-preemptive speed-scaling scheduling

We are given a set of jobs, each one specified by its release date, its deadline and its processing volume (work), and a single (or a set of) speed-scalable processor(s). We adopt the standard model in speed-scaling in which if a processor runs at speed s then the energy consumption is s α units of energy per time unit, where α > 1. Our goal is to find a schedule respecting the release dates and the deadlines of the jobs so that the total energy consumption is minimized. While most previous works have studied the preemptive case of the problem, where a job may be interrupted and resumed later, we focus on the non-preemptive case where once a job starts its execution, it has to continue until its completion without any interruption. As the preemptive case is known to be polynomially solvable for both the single-processor and the multiprocessor case, we explore the idea of transforming an optimal preemptive schedule to a non-preemptive one. We prove that the preemptive optimal solution does not preserve enough of the structure of the non-preemptive optimal solution, and more precisely that the ratio between the energy consumption of an optimal non-preemptive schedule and the energy consumption of an optimal preemptive schedule can be very large even for the single-processor case. Then, we focus on some interesting families of instances: (i) equal-work jobs on a single-processor, and (ii) agreeable instances in the multiprocessor case. In both cases, we propose constant factor approximation algorithms. In the latter case, our algorithm improves the best known algorithm of the literature. Finally, we propose a (non-constant factor) approximation algorithm for general instances in the multiprocessor case. © 2013 Springer-Verlag Berlin Heidelberg

From preemptive to non-preemptive speed-scaling scheduling

We are given a set of jobs, each one specified by its release date, its deadline and its processing volume (work), and a single (or a set of) speed-scalable processor(s). We adopt the standard model in speed-scaling in which if a processor runs at speed s then the energy consumption is sα units of energy per time unit, where α>1 is a small constant. Our goal is to find a schedule respecting the release dates and the deadlines of the jobs so that the total energy consumption to be minimized. While most previous works have studied the preemptive case of the problem, where a job may be interrupted and resumed later, we focus on the non-preemptive case where once a job starts its execution, it has to continue until its completion without any interruption. As the preemptive case is known to be polynomially solvable for both the single-processor and the multiprocessor case, we explore the idea of transforming an optimal preemptive schedule to a non-preemptive one. We prove that the preemptive optimal solution does not preserve enough of the structure of the non-preemptive optimal solution, and more precisely that the ratio between the energy consumption of an optimal non-preemptive schedule and the energy consumption of an optimal preemptive schedule can be very large even for the single-processor case. Then, we focus on some interesting families of instances: (i) equal-work jobs on a single-processor, and (ii) agreeable instances in the multiprocessor case. In both cases, we propose constant factor approximation algorithms. In the latter case, our algorithm improves the best known algorithm of the literature. Finally, we propose a (non-constant factor) approximation algorithm for general instances in the multiprocessor case. © 2014 Elsevier B.V. All rights reserved