Scalable Techniques for Fault Tolerant High Performance Computing

As the number of processors in today’s parallel systems continues to grow, the mean-time-to-failure of these systems is becoming significantly shorter than the execu- tion time of many parallel applications. It is increasingly important for large parallel applications to be able to continue to execute in spite of the failure of some components in the system. Today’s long running scientific applications typically tolerate failures by checkpoint/restart in which all process states of an application are saved into stable storage periodically. However, as the number of processors in a system increases, the amount of data that need to be saved into stable storage increases linearly. Therefore, the classical checkpoint/restart approach has a potential scalability problem for large parallel systems. In this research, we explore scalable techniques to tolerate a small number of process failures in large scale parallel computing. The goal of this research is to develop scalable fault tolerance techniques to help to make future high performance computing appli- cations self-adaptive and fault survivable. The fundamental challenge in this research is scalability. To approach this challenge, this research (1) extended existing diskless checkpointing techniques to enable them to better scale in large scale high performance computing systems; (2) designed checkpoint-free fault tolerance techniques for linear al- gebra computations to survive process failures without checkpoint or rollback recovery; (3) developed coding approaches and novel erasure correcting codes to help applications to survive multiple simultaneous process failures. The fault tolerance schemes we introduce in this dissertation are scalable in the sense that the overhead to tolerate a failure of a fixed number of processes does not increase as the number of total processes in a parallel system increases. Two prototype examples have been developed to demonstrate the effectiveness of our techniques. In the first example, we developed a fault survivable conjugate gradi- ent solver that is able to survive multiple simultaneous process failures with negligible overhead. In the second example, we incorporated our checkpoint-free fault tolerance technique into the ScaLAPACK/PBLAS matrix-matrix multiplication code to evaluate the overhead, survivability, and scalability. Theoretical analysis indicates that, to sur- vive a fixed number of process failures, the fault tolerance overhead (without recovery) for matrix-matrix multiplication decreases to zero as the total number of processes (as- suming a fixed amount of data per process) increases to infinity. Experimental results demonstrate that the checkpoint-free fault tolerance technique introduces surprisingly low overhead even when the total number of processes used in the application is small

Parallel simulation techniques for telecommunication network modelling

In this thesis, we consider the application of parallel simulation to the performance modelling of telecommunication networks. A largely automated approach was first explored using a parallelizing compiler to speed up the simulation of simple models of circuit-switched networks. This yielded reasonable results for relatively little effort compared with other approaches. However, more complex simulation models of packet- and cell-based telecommunication networks, requiring the use of discrete event techniques, need an alternative approach. A critical review of parallel discrete event simulation indicated that a distributed model components approach using conservative or optimistic synchronization would be worth exploring. Experiments were therefore conducted using simulation models of queuing networks and Asynchronous Transfer Mode (ATM) networks to explore the potential speed-up possible using this approach. Specifically, it is shown that these techniques can be used successfully to speed-up the execution of useful telecommunication network simulations. A detailed investigation has demonstrated that conservative synchronization performs very well for applications with good look ahead properties and sufficient message traffic density and, given such properties, will significantly outperform optimistic synchronization. Optimistic synchronization, however, gives reasonable speed-up for models with a wider range of such properties and can be optimized for speed-up and memory usage at run time. Thus, it is confirmed as being more generally applicable particularly as model development is somewhat easier than for conservative synchronization. This has to be balanced against the more difficult task of developing and debugging an optimistic synchronization kernel and the application models

Distributed Simulation of High-Level Algebraic Petri Nets

In the field of Petri nets, simulation is an essential tool to validate and evaluate models. Conventional simulation techniques, designed for their use in sequential computers, are too slow if the system to simulate is large or complex. The aim of this work is to search for techniques to accelerate simulations exploiting the parallelism available in current, commercial multicomputers, and to use these techniques to study a class of Petri nets called high-level algebraic nets. These nets exploit the rich theory of algebraic specifications for high-level Petri nets: Petri nets gain a great deal of modelling power by representing dynamically changing items as structured tokens whereas algebraic specifications turned out to be an adequate and flexible instrument for handling structured items. In this work we focus on ECATNets (Extended Concurrent Algebraic Term Nets) whose most distinctive feature is their semantics which is defined in terms of rewriting logic. Nevertheless, ECATNets have two drawbacks: the occultation of the aspect of time and a bad exploitation of the parallelism inherent in the models. Three distributed simulation techniques have been considered: asynchronous conservative, asynchronous optimistic and synchronous. These algorithms have been implemented in a multicomputer environment: a network of workstations. The influence that factors such as the characteristics of the simulated models, the organisation of the simulators and the characteristics of the target multicomputer have in the performance of the simulations have been measured and characterised. It is concluded that synchronous distributed simulation techniques are not suitable for the considered kind of models, although they may provide good performance in other environments. Conservative and optimistic distributed simulation techniques perform well, specially if the model to simulate is complex or large - precisely the worst case for traditional, sequential simulators. This way, studies previously considered as unrealisable, due to their exceedingly high computational cost, can be performed in reasonable times. Additionally, the spectrum of possibilities of using multicomputers can be broadened to execute more than numeric applications

Simulation of packet and cell-based communication networks

This thesis investigates, using simulation techniques, the practical aspects of implementing a novel mobility protocol on the emerging Broadband Integrated Services Digital Network standard. The increasing expansion of telecommunications networks has meant that the demand for simulation has increased rapidly in recent years; but conventional simulators are slow and developments in the communications field are outstripping the ability of sequential uni-processor simulators. Newer techniques using distributed simulation on a multi-processor network are investigated in an attempt to make a cell-level simulation of a non-trivial B.-I.S.D.N. network feasible. The current state of development of the Asynchronous Transfer Mode standard, which will be used to implement a B.-I.S.D.N., is reviewed and simulation studies of the Orwell Slotted Ring protocol were made in an attempt to devise a simpler model for use in the main simulator. The mobility protocol, which uses a footprinting technique to simplify hand- offs by distributing information about a connexion to surrounding base stations, was implemented on the simulator and found to be functional after a few 'special case' scenarios had been catered for

On-demand distributed image processing over an adaptive Campus-Grid

This thesis explores how scientific applications, which are based upon short jobs (seconds and minutes) can capitalize upon the idle workstations of a Campus-Grid. These resources are donated on a voluntary basis, and consequently, the Campus-Grid is constantly adapting and the availability of workstations changes. Typically, to utilize these resources a Condor system or equivalent would be used. However, such systems are designed with different trade-offs and incentives in mind and therefore do not provide intrinsic support for short jobs. The motivation for creating a provisioning scenario for short jobs is that Image Processing, as well as other areas of scientific analysis, are typically composed of short running jobs, but still require parallel solutions. Much of the literature in this area comments on the challenges of performing such analysis efficiently and effectively even when dedicated resources are in use. The main challenges are: latency and scheduling penalties, granularity and the potential for very short jobs. A volunteer Grid retains these challenges but also adds further challenges. These can be summarized as: unpredictable re source availability and longevity, multiple machine owners and administrators who directly affect the operating environment. Ultimately, this creates the requirement for well conceived and effective fault management strategies. However, these are typically not in place to enable transparent fault-free job administration for the user. This research demonstrates that these challenges are answerable, and that in doing so opportunistically sourced Campus-Grid resources can host disparate applications constituted of short running jobs, of as little as one second in length. This is demonstrated by the significant improvements in performance when the system presented here was compared to a well established Condor system. Here, improvements are increased job efficiency from 60–70% to 95%–100%, up to a 99% reduction in application makespan and up to a 13000% increase in the efficiency of resource utilization. The Condor pool in use is approximately 1,600 workstations distributed across 27 administrative domains of Cardiff University. The application domain of this research is Matlab-based image processing, and the application area used to demonstrate the approach is the analysis of Magnetic Resonance Imagery (MRI). However, the presented approach is generalizable to any application domain with similar characteristics