Implementing a concurrent programming language such as Java by means of a translator to an existing language is attractive as it provides portability over all platforms supported by the host language and reduces development time—as many low-level tasks can be delegated to the host compiler. The C and C++ programming languages are popular choices for many language implementations due to the availability of efficient compilers on a wide range of platforms. For garbage-collected languages, however, they are not a perfect match as no support is provided for accurately discovering pointers to heap-allocated data on thread stacks. We evaluate several previously published techniques and propose a new mechanism, lazy pointer stacks, for performing accurate garbage collection in such uncooperative environments. We implemented the new technique in the Ovm Java virtual machine with our own Java-to-C-C++ compiler using GCC as a back-end compiler. Our extensive experimental results confirm that lazy pointer stacks outperform existing approaches: we provide a speedup of 4.5p over Henderson's accurate collector with a 17p increase in code size. Accurate collection is essential in the context of real-time systems, we thus validate our approach with the implementation of a real-time concurrent garbage collection algorithm. Copyright © 2009 John Wiley & Sons, Ltd.

A preliminary version of this work was presented at the 16th International Conference on Compiler Construction (CC 2007), part of the Joint European Conferences on Theory and Practice of Software (ETAPS 2007), March 26–30, 2007, Braga, Portugal.

/pdf/accurate-garbage-collection-in-uncooperative-environments-2haq8wvsl3.pdf

Accurate garbage collection in uncooperative environments revisited

Survey: Survey of fault tolerant techniques for grid

Current fault tolerance protocols are not sufficiently scalable for the exascale era. The most-widely used method, coordinated checkpointing, places enormous demands on the I/O subsystem and imposes frequent synchronizations. Uncoordinated protocols use message logging which introduces message rate limitations or undesired memory and storage requirements to hold payload and event logs. In this paper we propose a combination of several techniques, namely coordinated checkpointing, optimistic message logging, and a protocol that glues them together. This combination eliminates some of the drawbacks of each individual approach and proves to be an alternative for many types of exascale applications. We evaluate performance and scaling characteristics of this combination using simulation and a partial implementation. While not a universal solution, the combined protocol is suitable for a large range of existing and future applications that use coordinated checkpointing and enhances their scalability.

https://cfwebprod.sandia.gov/cfdocs/CompResearch/docs/MLogging.pdf

Alleviating scalability issues of checkpointing protocols

Most large systems such as HPC/cloud computing clusters and data centers are built from commercial off-the-shelf components. System logs are usually the main source of choice to gain insights into the system issues. Therefore, mining logs to diagnose anomalies has been an active research area. Due to the lack of organization and semantic consistency in commodity PC clusters' logs, what constitutes a fault or an error is subjective and thus building an automatic failure prediction model from log messages is hard. In this paper we sidestep the difficulty by asking a different question: Given the concomitant system log messages of a running job, can we predict the job's remaining time? We adopt Hidden Markov Model (HMM) coupled with frequency analysis to achieve this. Our HMM approach can predict 75% of jobs' remaining times with an error of less than 200 seconds.

https://blogs.ubc.ca/karthik/files/2013/05/rsda2013.pdf

Predicting job completion times using system logs in supercomputing clusters

A variety of research problems exist that require considerable time and computational resources to solve. Attempting to solve these problems produces long-running applications that require a reliable and trustworthy system upon which they can be executed. Cluster systems provide an excellent environment upon which to run these applications because of their low cost to performance ratio; however, due to being created using commodity components they are prone to failures. This report surveyed and reviewed the issues currently relating to providing fault tolerance for long-running applications. Several fault tolerance approaches were investigated; however, it was found that rollback-recovery provides a favourable approach for user applications in cluster systems. Two facilities are required to provide fault tolerance using rollback-recovery: checkpointing and recovery. It was shown here that a multitude of work has been done for enhancing checkpointing; however, the intricacies of providing recovery have been neglected. The problems associated with providing recovery include; providing transparent and autonomic recovery, selecting appropriate recovery computers, and maintaining a consistent observable behaviour when an application fails. Copyright © 2009 John Wiley & Sons, Ltd.

A survey and review of the current state of rollback-recovery for cluster systems

Recent advances in checkpoint/recovery systems

Handle everyday research tasks with reliable, citation-backed results

Your personal Research Agent to handle research tasks with citation-backed results

Popular Tasks used by Researchers

How can I help with your research?

Meet SciSpace

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

Fernandes

Author Tools

Chat about Author

Papers

Recent advances in checkpoint/recovery systems