Application-level Fault Tolerance and Resilience in HPC Applications

Programa Oficial de Doutoramento en Investigación en Tecnoloxías da Información. 524V01[Resumo] As necesidades computacionais das distintas ramas da ciencia medraron enormemente nos últimos anos, o que provocou un gran crecemento no rendemento proporcionado polos supercomputadores. Cada vez constrúense sistemas de computación de altas prestacións de maior tamaño, con máis recursos hardware de distintos tipos, o que fai que as taxas de fallo destes sistemas tamén medren. Polo tanto, o estudo de técnicas de tolerancia a fallos eficientes é indispensábel para garantires que os programas científicos poidan completar a súa execución, evitando ademais que se dispare o consumo de enerxía. O checkpoint/restart é unha das técnicas máis populares. Sen embargo, a maioría da investigación levada a cabo nas últimas décadas céntrase en estratexias stop-and-restart para aplicacións de memoria distribuída tralo acontecemento dun fallo-parada. Esta tese propón técnicas checkpoint/restart a nivel de aplicación para os modelos de programación paralela roáis populares en supercomputación. Implementáronse protocolos de checkpointing para aplicacións híbridas MPI-OpenMP e aplicacións heteroxéneas baseadas en OpenCL, en ámbolos dous casos prestando especial coidado á portabilidade e maleabilidade da solución. En canto a aplicacións de memoria distribuída, proponse unha solución de resiliencia que pode ser empregada de forma xenérica en aplicacións MPI SPMD, permitindo detectar e reaccionar a fallos-parada sen abortar a execución. Neste caso, os procesos fallidos vólvense a lanzar e o estado da aplicación recupérase cunha volta atrás global. A maiores, esta solución de resiliencia optimizouse implementando unha volta atrás local, na que só os procesos fallidos volven atrás, empregando un protocolo de almacenaxe de mensaxes para garantires a consistencia e o progreso da execución. Por último, propónse a extensión dunha librería de checkpointing para facilitares a implementación de estratexias de recuperación ad hoc ante conupcións de memoria. En moitas ocasións, estos erros poden ser xestionados a nivel de aplicación, evitando desencadear un fallo-parada e permitindo unha recuperación máis eficiente.[Resumen] El rápido aumento de las necesidades de cómputo de distintas ramas de la ciencia ha provocado un gran crecimiento en el rendimiento ofrecido por los supercomputadores. Cada vez se construyen sistemas de computación de altas prestaciones mayores, con más recursos hardware de distintos tipos, lo que hace que las tasas de fallo del sistema aumenten. Por tanto, el estudio de técnicas de tolerancia a fallos eficientes resulta indispensable para garantizar que los programas científicos puedan completar su ejecución, evitando además que se dispare el consumo de energía. La técnica checkpoint/restart es una de las más populares. Sin embargo, la mayor parte de la investigación en este campo se ha centrado en estrategias stop-and-restart para aplicaciones de memoria distribuida tras la ocurrencia de fallos-parada. Esta tesis propone técnicas checkpoint/restart a nivel de aplicación para los modelos de programación paralela más populares en supercomputación. Se han implementado protocolos de checkpointing para aplicaciones híbridas MPI-OpenMP y aplicaciones heterogéneas basadas en OpenCL, prestando en ambos casos especial atención a la portabilidad y la maleabilidad de la solución. Con respecto a aplicaciones de memoria distribuida, se propone una solución de resiliencia que puede ser usada de forma genérica en aplicaciones MPI SPMD, permitiendo detectar y reaccionar a fallosparada sin abortar la ejecución. En su lugar, se vuelven a lanzar los procesos fallidos y se recupera el estado de la aplicación con una vuelta atrás global. A mayores, esta solución de resiliencia ha sido optimizada implementando una vuelta atrás local, en la que solo los procesos fallidos vuelven atrás, empleando un protocolo de almacenaje de mensajes para garantizar la consistencia y el progreso de la ejecución. Por último, se propone una extensión de una librería de checkpointing para facilitar la implementación de estrategias de recuperación ad hoc ante corrupciones de memoria. Muchas veces, este tipo de errores puede gestionarse a nivel de aplicación, evitando desencadenar un fallo-parada y permitiendo una recuperación más eficiente.[Abstract] The rapid increase in the computational demands of science has lead to a pronounced growth in the performance offered by supercomputers. As High Performance Computing (HPC) systems grow larger, including more hardware components of different types, the system's failure rate becomes higher. Efficient fault tolerance techniques are essential not only to ensure the execution completion but also to save energy. Checkpoint/restart is one of the most popular fault tolerance techniques. However, most of the research in this field is focused on stop-and-restart strategies for distributed-memory applications in the event of fail-stop failures. Thís thesis focuses on the implementation of application-level checkpoint/restart solutions for the most popular parallel programming models used in HPC. Hence, we have implemented checkpointing solutions to cope with fail-stop failures in hybrid MPI-OpenMP applications and OpenCL-based programs. Both strategies maximize the restart portability and malleability, ie., the recovery can take place on machines with different CPU / accelerator architectures, and/ or operating systems, and can be adapted to the available resources (number of cores/accelerators). Regarding distributed-memory applications, we propose a resilience solution that can be generally applied to SPMD MPI programs. Resilient applications can detect and react to failures without aborting their execution upon fail-stop failures. Instead, failed processes are re-spawned, and the application state is recovered through a global rollback. Moreover, we have optimized this resilience proposal by implementing a local rollback protocol, in which only failed processes rollback to a previous state, while message logging enables global consistency and further progress of the computation. Finally, we have extended a checkpointing library to facilitate the implementation of ad hoc recovery strategies in the event of soft errors) caused by memory corruptions. Many times, these errors can be handled at the software-Ievel, tIms, avoiding fail-stop failures and enabling a more efficient recovery

Exascale machines require new programming paradigms and runtimes

Extreme scale parallel computing systems will have tens of thousands of optionally accelerator-equiped nodes with hundreds of cores each, as well as deep memory hierarchies and complex interconnect topologies. Such Exascale systems will provide hardware parallelism at multiple levels and will be energy constrained. Their extreme scale and the rapidly deteriorating reliablity of their hardware components means that Exascale systems will exhibit low mean-time-between-failure values. Furthermore, existing programming models already require heroic programming and optimisation efforts to achieve high efficiency on current supercomputers. Invariably, these efforts are platform-specific and non-portable. In this paper we will explore the shortcomings of existing programming models and runtime systems for large scale computing systems. We then propose and discuss important features of programming paradigms and runtime system to deal with large scale computing systems with a special focus on data-intensive applications and resilience. Finally, we also discuss code sustainability issues and propose several software metrics that are of paramount importance for code development for large scale computing systems

Reliable massively parallel symbolic computing : fault tolerance for a distributed Haskell

As the number of cores in manycore systems grows exponentially, the number of failures is also predicted to grow exponentially. Hence massively parallel computations must be able to tolerate faults. Moreover new approaches to language design and system architecture are needed to address the resilience of massively parallel heterogeneous architectures. Symbolic computation has underpinned key advances in Mathematics and Computer Science, for example in number theory, cryptography, and coding theory. Computer algebra software systems facilitate symbolic mathematics. Developing these at scale has its own distinctive set of challenges, as symbolic algorithms tend to employ complex irregular data and control structures. SymGridParII is a middleware for parallel symbolic computing on massively parallel High Performance Computing platforms. A key element of SymGridParII is a domain specific language (DSL) called Haskell Distributed Parallel Haskell (HdpH). It is explicitly designed for scalable distributed-memory parallelism, and employs work stealing to load balance dynamically generated irregular task sizes. To investigate providing scalable fault tolerant symbolic computation we design, implement and evaluate a reliable version of HdpH, HdpH-RS. Its reliable scheduler detects and handles faults, using task replication as a key recovery strategy. The scheduler supports load balancing with a fault tolerant work stealing protocol. The reliable scheduler is invoked with two fault tolerance primitives for implicit and explicit work placement, and 10 fault tolerant parallel skeletons that encapsulate common parallel programming patterns. The user is oblivious to many failures, they are instead handled by the scheduler. An operational semantics describes small-step reductions on states. A simple abstract machine for scheduling transitions and task evaluation is presented. It defines the semantics of supervised futures, and the transition rules for recovering tasks in the presence of failure. The transition rules are demonstrated with a fault-free execution, and three executions that recover from faults. The fault tolerant work stealing has been abstracted in to a Promela model. The SPIN model checker is used to exhaustively search the intersection of states in this automaton to validate a key resiliency property of the protocol. It asserts that an initially empty supervised future on the supervisor node will eventually be full in the presence of all possible combinations of failures. The performance of HdpH-RS is measured using five benchmarks. Supervised scheduling achieves a speedup of 757 with explicit task placement and 340 with lazy work stealing when executing Summatory Liouville up to 1400 cores of a HPC architecture. Moreover, supervision overheads are consistently low scaling up to 1400 cores. Low recovery overheads are observed in the presence of frequent failure when lazy on-demand work stealing is used. A Chaos Monkey mechanism has been developed for stress testing resiliency with random failure combinations. All unit tests pass in the presence of random failure, terminating with the expected results

A Portable and Adaptable Fault Tolerance Solution for Heterogeneous Applications

[Abstract] Heterogeneous systems have increased their popularity in recent years due to the high performance and reduced energy consumption capabilities provided by using devices such as GPUs or Xeon Phi accelerators. This paper proposes a checkpoint-based fault tolerance solution for heterogeneous applications, allowing them to survive fail-stop failures in the host CPU or in any of the accelerators used. Besides, applications can be restarted changing the host CPU and/or the accelerator device architecture, and adapting the computation to the number of devices available during recovery. The proposed solution is built combining CPPC (ComPiler for Portable Checkpointing), an application-level checkpointing tool, and HPL (Heterogeneous Programming Library), a library that facilitates the development of OpenCL-based applications. Experimental results show the low overhead introduced by the proposal and prove its portability and adaptability benefits.This research was supported by the Ministry of Economy and Competitiveness of Spain and FEDER funds of the EU (Projects TIN2013-42148-P, TIN2016-75845-P and the predoctoral Grant of Nuria Losada Ref. BES-2014-068066), by EU under the COST Program Action IC1305, Network for Sustainable Ultrascale Computing (NESUS), and by the Galician Government (Xunta de Galicia) and FEDER funds of the EU under the Consolidation Program of Competitive Research (Ref. GRC2013/055)Xunta de Galicia; GRC 2013/05

CPPC: a compiler‐assisted tool for portable checkpointing of message‐passing applications

This is the peer reviewed version of the following article: Rodríguez, G. , Martín, M. J., González, P. , Touriño, J. and Doallo, R. (2010), CPPC: a compiler‐assisted tool for portable checkpointing of message‐passing applications. Concurrency Computat.: Pract. Exper., 22: 749-766. doi:10.1002/cpe.1541, which has been published in final form at https://doi.org/10.1002/cpe.1541. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions.[Abstract] With the evolution of high‐performance computing toward heterogeneous, massively parallel systems, parallel applications have developed new checkpoint and restart necessities. Whether due to a failure in the execution or to a migration of the application processes to different machines, checkpointing tools must be able to operate in heterogeneous environments. However, some of the data manipulated by a parallel application are not truly portable. Examples of these include opaque state (e.g. data structures for communications support) or diversity of interfaces for a single feature (e.g. communications, I/O). Directly manipulating the underlying ad hoc representations renders checkpointing tools unable to work on different environments. Portable checkpointers usually work around portability issues at the cost of transparency: the user must provide information such as what data need to be stored, where to store them, or where to checkpoint. CPPC (ComPiler for Portable Checkpointing) is a checkpointing tool designed to feature both portability and transparency. It is made up of a library and a compiler. The CPPC library contains routines for variable level checkpointing, using portable code and protocols. The CPPC compiler helps to achieve transparency by relieving the user from time‐consuming tasks, such as data flow and communications analyses and adding instrumentation code. This paper covers both the operation of the CPPC library and its compiler support. Experimental results using benchmarks and large‐scale real applications are included, demonstrating usability, efficiency, and portability.Miniesterio de Educación y Ciencia; TIN2007‐67537‐C03Xunta de Galicia; 2006/

Analysis of Performance-impacting Factors on Checkpointing Frameworks: The CPPC Case Study

This is a post-peer-review, pre-copyedit version of an article published in The Computer Journal. The final authenticated version is available online at: https://doi.org/10.1093/comjnl/bxr018[Abstract] This paper focuses on the performance evaluation of Compiler for Portable Checkpointing (CPPC), a tool for the checkpointing of parallel message-passing applications. Its performance and the factors that impact it are transparently and rigorously identified and assessed. The tests were performed on a public supercomputing infrastructure, using a large number of very different applications and showing excellent results in terms of performance and effort required for integration into user codes. Statistical analysis techniques have been used to better approximate the performance of the tool. Quantitative and qualitative comparisons with other rollback-recovery approaches to fault tolerance are also included. All these data and comparisons are then discussed in an effort to extract meaningful conclusions about the state-of-the-art and future research trends in the rollback-recovery field.Minsiterio de Ciencia e Innovación; TIN2010-1673

Toward Message Passing Failure Management

As machine sizes have increased and application runtimes have lengthened, research into fault tolerance has evolved alongside. Moving from result checking, to rollback recovery, and to algorithm based fault tolerance, the type of recovery being performed has changed, but the programming model in which it executes has remained virtually static since the publication of the original Message Passing Interface (MPI) Standard in 1992. Since that time, applications have used a message passing paradigm to communicate between processes, but they could not perform process recovery within an MPI implementation due to limitations of the MPI Standard. This dissertation describes a new protocol using the exiting MPI Standard called Checkpoint-on-Failure to perform limited fault tolerance within the current framework of MPI, and proposes a new platform titled User Level Failure Mitigation (ULFM) to build more complete and complex fault tolerance solutions with a true fault tolerant MPI implementation. We will demonstrate the overhead involved in using these fault tolerant solutions and give examples of applications and libraries which construct other fault tolerance mechanisms based on the constructs provided in ULFM