Impact of the Consistency Model on Checkpointing of Distributed Shared Memory

In this report, we consider the impact of the consistency model on checkpointing and rollback algorithms for distributed shared memory. In particular, we consider specific implementations of four consistency models for distributed shared memory, namely, linearizability, sequential consistency, causal consistency and eventual consistency, and develop checkpointing and rollback algorithms that can be integrated into the implementations of the consistency models. Our results empirically demonstrate that the mechanisms used to implement stronger consistency models lead to simpler or more efficient checkpointing algorithms

A survey of checkpointing algorithms for parallel and distributed computers

Checkpoint is defined as a designated place in a program at which normal processing is interrupted specifically to preserve the status information necessary to allow resumption of processing at a later time. Checkpointing is the process of saving the status information. This paper surveys the algorithms which have been reported in the literature for checkpointing parallel/distributed systems. It has been observed that most of the algorithms published for checkpointing in message passing systems are based on the seminal article by Chandy and Lamport. A large number of articles have been published in this area by relaxing the assumptions made in this paper and by extending it to minimise the overheads of coordination and context saving. Checkpointing for shared memory systems primarily extend cache coherence protocols to maintain a consistent memory. All of them assume that the main memory is safe for storing the context. Recently algorithms have been published for distributed shared memory systems, which extend the cache coherence protocols used in shared memory systems. They however also include methods for storing the status of distributed memory in stable storage. Most of the algorithms assume that there is no knowledge about the programs being executed. It is however felt that in development of parallel programs the user has to do a fair amount of work in distributing tasks and this information can be effectively used to simplify checkpointing and rollback recovery

A Generic Checkpoint-Restart Mechanism for Virtual Machines

It is common today to deploy complex software inside a virtual machine (VM). Snapshots provide rapid deployment, migration between hosts, dependability (fault tolerance), and security (insulating a guest VM from the host). Yet, for each virtual machine, the code for snapshots is laboriously developed on a per-VM basis. This work demonstrates a generic checkpoint-restart mechanism for virtual machines. The mechanism is based on a plugin on top of an unmodified user-space checkpoint-restart package, DMTCP. Checkpoint-restart is demonstrated for three virtual machines: Lguest, user-space QEMU, and KVM/QEMU. The plugins for Lguest and KVM/QEMU require just 200 lines of code. The Lguest kernel driver API is augmented by 40 lines of code. DMTCP checkpoints user-space QEMU without any new code. KVM/QEMU, user-space QEMU, and DMTCP need no modification. The design benefits from other DMTCP features and plugins. Experiments demonstrate checkpoint and restart in 0.2 seconds using forked checkpointing, mmap-based fast-restart, and incremental Btrfs-based snapshots

Network Multicomputing Using Recoverable Distributed Shared Memory

A network multicomputer is a multiprocessor in which the processors are connected by general-purpose networking technology, in contrast to current distributed memory multiprocessors where a dedicated special-purpose interconnect is used. The advent of high-speed general-purpose networks provides the impetus for a new look at the network multiprocessor model, by removing the bottleneck of current slow networks. However, major software issues remain unsolved. It is pointed out that a convenient machine abstraction must be developed that hides from the application programmer low-level details such as message passing or machine failures. Use is made of distributed shared memory as a programming abstraction, and rollback recovery through consistent checkpointing to provide fault tolerance. Measurements of the authors' implementations of distributed shared memory and consistent checkpointing show that these abstractions can be implemented efficientl

ReSHAPE: A Framework for Dynamic Resizing and Scheduling of Homogeneous Applications in a Parallel Environment

Applications in science and engineering often require huge computational resources for solving problems within a reasonable time frame. Parallel supercomputers provide the computational infrastructure for solving such problems. A traditional application scheduler running on a parallel cluster only supports static scheduling where the number of processors allocated to an application remains fixed throughout the lifetime of execution of the job. Due to the unpredictability in job arrival times and varying resource requirements, static scheduling can result in idle system resources thereby decreasing the overall system throughput. In this paper we present a prototype framework called ReSHAPE, which supports dynamic resizing of parallel MPI applications executed on distributed memory platforms. The framework includes a scheduler that supports resizing of applications, an API to enable applications to interact with the scheduler, and a library that makes resizing viable. Applications executed using the ReSHAPE scheduler framework can expand to take advantage of additional free processors or can shrink to accommodate a high priority application, without getting suspended. In our research, we have mainly focused on structured applications that have two-dimensional data arrays distributed across a two-dimensional processor grid. The resize library includes algorithms for processor selection and processor mapping. Experimental results show that the ReSHAPE framework can improve individual job turn-around time and overall system throughput.Comment: 15 pages, 10 figures, 5 tables Submitted to International Conference on Parallel Processing (ICPP'07