Supporting automatic recovery in offloaded distributed programming models through MPI-3 techniques

In this paper we describe the design of fault tolerance capabilities for general-purpose offload semantics, based on the OmpSs programming model. Using ParaStation MPI, a production MPI-3.1 implementation, we explore the features that, being standard compliant, an MPI stack must support to provide the necessary fault tolerance guarantees, based on MPI's dynamic process management. Our results, including synthetic benchmarks and applications, reveal low runtime overhead and efficient recovery, demonstrating that the existing MPI standard provided us with sufficient mechanisms to implement an effective and efficient fault-tolerant solution.This research received funding from the European Community’s 7th Framework Programme via the DEEP-ER project under Grant Agreement no. 610476. This work has also been supported by the Spanish Ministry of Science and Innovation (contract TIN2012-34557) and by Generalitat de Catalunya (contracts 2014-SGR-1051 and 2014-SGR-1272). Antonio J. Peña is cofinanced by the Spanish Ministry of Economy and Competitiveness under Juan de la Cierva fellowship number IJCI-2015-23266. The authors thank Jorge Bell´on, from BSC, for his technical support with the Nanos++ internals.Peer ReviewedPostprint (author's final draft

Improving Patients' Adherence to Physical Activity in Diabetes Mellitus: A Review

Regular physical activity (PA) is a key element in the prevention and management of type 2 diabetes mellitus (T2DM). Participation in regular PA improves blood glucose control and can prevent or delay T2DM and its complications, along with positively affecting lipids, blood pressure, cardiovascular events, mortality, and quality of life. However, most people with T2DM are not active and show poor adherence. This paper reviews the possible barriers to PA and strategies to improve the adherence to PA. Based on the currently available literature, it is concluded that self-efficacy and social support from family, friends, and health care providers play the important role in adoption and maintenance of regular PA. Here we also highlight some new modern and innovative interventions that facilitate exercise participation and improve the adherence

Allocation-Internal Co-Scheduling - Interaction and Orchestration of Multiple Concurrent MPI Sessions

Heading towards exascale, the challenges for process management with respect to flexibility and efficiency grow accordingly. Running more than one application simultaneously on a node can be the solution for better resource utilization. However, this approach of co-scheduling can also be the way to go for gaining a degree of flexibility with respect to process management that can enable some kind of interactivity even in the domain of high-performance computing. This chapter gives an introduction into such co-scheduling policies for running multiple MPI sessions concurrently and interactively within a single user allocation. The chapter initially introduces a taxonomy for classifying the different characteristics of such a flexible process management, and discusses actual manifestations thereof during the course of the reading. In doing so, real world examples are motivated and presented by means of ParaStation MPI, a high-performance MPI library supplemented by a complete framework comprising a scalable and dynamic process manager. In particular, four scheduling policies, implemented in ParaStation MPI, are detailed and evaluated by applying a benchmarking tool that has especially been developed for measuring interactivity and dynamicity metrics of job schedulers and process managers for high-performance computing

The DEEP Project - Pursuing Cluster-Computing in the Many-Core Era

Homogeneous cluster architectures dominating high-performance computing (HPC) today are challenged, in particular when thinking about reaching Exascale by the end of the decade, by heterogeneous approaches utilizing accelerator elements. The DEEP (Dynamical Exascale Entry Platform) project aims for implementing a novel architecture for high-performance computing consisting of two components - a standard HPC Cluster and a cluster of many-core processors called Booster. In order to make the adaptation of application codes to this Cluster-Booster architecture as seamless as possible, DEEP provides a complete programming environment. It integrates the offloading functionality given by the MPI standard with an abstraction layer based on the task-based OmpSs programming paradigm. This paper presents the DEEP project with an emphasis on the DEEP programming environment

Supporting automatic recovery in offloaded distributed programming models through MPI-3 techniques

In this paper we describe the design of fault tolerance capabilities for general-purpose offload semantics, based on the OmpSs programming model. Using ParaStation MPI, a production MPI-3.1 implementation, we explore the features that, being standard compliant, an MPI stack must support to provide the necessary fault tolerance guarantees, based on MPI's dynamic process management. Our results, including synthetic benchmarks and applications, reveal low runtime overhead and efficient recovery, demonstrating that the existing MPI standard provided us with sufficient mechanisms to implement an effective and efficient fault-tolerant solution.This research received funding from the European Community’s 7th Framework Programme via the DEEP-ER project under Grant Agreement no. 610476. This work has also been supported by the Spanish Ministry of Science and Innovation (contract TIN2012-34557) and by Generalitat de Catalunya (contracts 2014-SGR-1051 and 2014-SGR-1272). Antonio J. Peña is cofinanced by the Spanish Ministry of Economy and Competitiveness under Juan de la Cierva fellowship number IJCI-2015-23266. The authors thank Jorge Bell´on, from BSC, for his technical support with the Nanos++ internals.Peer Reviewe