Abstract. The number of processors embedded on high performance computing platforms is growing daily to satisfy users desire for solving larger and more complex problems. Parallel runtime environments have to support and adapt to the underlying libraries and hardware which require a high degree of scalability in dynamic environments. This paper presents the design of a scalable and fault tolerant protocol for supporting parallel runtime environment communications. The protocol is designed to support transmission of messages across multiple nodes with in a self-healing topology to protect against recursive node and process failures. A formal protocol verification has validated the protocol for both the normal and failure cases. We have implemented multiple routing algorithms for the protocol and concluded that the variant rulebased routing algorithm yields the best overall results for damaged and incomplete topologies. 1

The growth in the number of generally available, distributed, heterogeneous computing systems places increasing importance on the development of user-friendly tools that enable application developers to efficiently use these resources. Open MPI provides support for several aspects of heterogeneity within a single, open-source MPI implementation. Through careful abstractions, heterogeneous support maintains efficient use of uniform computational platforms. We describe Open MPI’s architecture for heterogeneous network and processor support. A key design features of this implementation is the transparency to the application developer while maintaining very high levels of performance. This is demonstrated with the results of several numerical experiments. 1.

Abstract Scalable and fault tolerant runtime environments are needed to support and adapt to the underlying libraries and hardware which require a high degree of scalability in dynamic large-scale environments. This paper presents a self-healing network (SHN) for supporting scalable and fault-tolerant runtime environments. The SHN is designed to support transmission of messages across multiple nodes while also protecting against recursive node and process failures. It will automatically recover itself after a failure occurs. SHN is implemented on top of a scalable fault-tolerant protocol (SFTP). The experimental results show that both the latest multicast and broadcast routing algorithms used in SHN are faster than the original SFTP routing algorithms.

Abstract: Many tools that target parallel and distributed environments must co-locate a set of daemons with the distributed processes of the target application. However, efficient and portable deployment of these daemons on large scale systems is an unsolved problem. We overcome this gap with LaunchMON, a scalable, robust, portable, secure, and general purpose infrastructure for launching tool daemons. Its API allows tool builders to identify all processes of a target job, launch daemons on the relevant nodes and control daemon interaction. Our results show that Launch-MON scales to very large daemon counts and substantially enhances performance over existing ad hoc mechanisms. 1

Abstract. Parallel programming models on large-scale systems require a scalable system for managing the processes that make up the execution of a parallel program. The process-management system must be able to launch millions of processes quickly when starting a parallel program and must provide mechanisms for the processes to exchange the information needed to enable them communicate with each other. MPICH2 and its derivatives achieve this functionality through a carefully defined interface, called PMI, that allows different process managers to interact with the MPI library in a standardized way. In this paper, we describe the features and capabilities of PMI. We describe both PMI-1, the current generation of PMI used in MPICH2 and all its derivatives, as well as PMI-2, the second-generation of PMI that eliminates various shortcomings in PMI-1. Together with the interface itself, we also describe a reference implementation for both PMI-1 and PMI-2 in a new processmanagement framework within MPICH2, called Hydra, and compare their performance in running MPI jobs with thousands of processes. 1

Abstract—The future of high performance computing, as being currently foretold, will gravitate toward hundreds of thousands to million node machines, harnessing the computing power of billions of cores. While the hardware part is well covered, the software infrastructure at that scale is vague. However, no matter what the infrastructure will be, efficiently running parallel applications on such large machines will require optimized runtime environments that are scalable and resilient. More particularly, considering a future where Message Passing Interface (MPI) remains a major programming paradigm, the MPI implementations will have to seamlessly adapt to launching and managing large scale applications on resources several levels of magnitude larger than today. In this paper, we present a modified version of the Open MPI runtime that has been adapted towards a scalability goal. We evaluate the performance and compare it with two widely used runtime systems: the default version of Open MPI and MPICH2; using various underlying launching systems. The performance evaluation demonstrates a significant improvement over the state of the art. We also discuss the basic requirements for an exascale-ready parallel runtime. I.

The growth in the number of generally available, distributed, heterogeneous computing systems places increasing importance on the development of user-friendly tools that enable application developers to efficiently use these resources. Open MPIprovides supportfor several aspects of heterogeneity within a single, open-source MPI implementation. Through careful abstractions, heterogeneous support maintains efficient use of uniform computational platforms. We describe Open MPI's architecture for heterogeneous network and processor support. A key design features of this implementation is the transparency to the application developer while maintaining very high levels of performance. This is demonstrated with the results ofseveral numerical experiments. 1.

iii To my parents, who never let me lose sight of my goals.

Abstract — The Scalable Tools Communication Infrastructure (STCI) is an open source collaborative effort intended to provide high-performance, scalable, resilient, and portable communications and process control services for a wide variety of user and system tools. STCI is aimed specifically at tools for ultrascale computing and uses a component architecture to simplify tailoring the infrastructure to a wide range of scenarios. This paper describes STCI’s design philosophy, the various components that will be used to provide an STCI implementation for a range of ultrascale platforms, and a range of tool types. These include tools supporting parallel run-time environments, such as MPI, parallel application correctness tools and performance analysis tools, as well as system monitoring and management tools. I.

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