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Rosalia Christodoulopoulou

dblp:46/2272 · DBLP profile ↗
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2ranked-venue papers
2as first author
0since 2021 · last 2006
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Systems, architecture and hardware · 2 · 2 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer architecture, parallel and distributed computing, and storage systems
2 papers
Distributed systems · 36% Hardware reliability and fault tolerance · 28% High-performance computing · 22%

Topics — the 5 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Distributed systems
fault tolerance
0.122006
Fast and transparent recovery for continuous availability of cluster-based servers · PPoPP 2006
Dynamic Data Replication: An Approach to Providing Fault-Tolerant Shared Memory Clusters · HPCA 2003
Hardware reliability and fault tolerance › reconfiguration
fault-tolerant reconfiguration
0.112006
Fast and transparent recovery for continuous availability of cluster-based servers · PPoPP 2006
High-performance computing › cluster computing
server cluster
0.112006
Fast and transparent recovery for continuous availability of cluster-based servers · PPoPP 2006
Memory systems › virtual memory management
shared virtual memory
0.012003
Dynamic Data Replication: An Approach to Providing Fault-Tolerant Shared Memory Clusters · HPCA 2003
Hardware reliability and fault tolerance › system reliability
server reliability
0.012006
Fast and transparent recovery for continuous availability of cluster-based servers · PPoPP 2006

Methods — techniques the papers use, named apart from their topics

fine-grained failure reconfiguration · 0.1dynamic data replication · 0.1replication · 0.0
YearPublicationVenuePosition
2006 Fast and transparent recovery for continuous availability of cluster-based servers
abstract
Recently there has been renewed interest in building reliable servers that support continuous application operation. Besides maintaining system state consistent after a failure, one of the main challenges in achieving continuous operation is to provide fast reconfiguration. The complexity of the failure reconfiguration mechanisms employed and their overheads depend on the type of platform that is being used as a server and the types of applications that need to be supported. In this paper we focus on providing support for shared-memory applications running on clusters of commodity nodes and interconnects. Achieving continuous operation for shared memory applications on clusters presents two main challenges. (a) The fault tolerance mechanisms employed should be transparent to applications and should have low overhead during failure-free execution. (b) When failures occur, reconfiguration should occur with minimum application disruption without requiring the full recovery of the failed node.In this work we examine in detail the latter, i.e., (b), the failure reconfiguration path. We use a previously developed system [8] that achieves (a) by using dynamic replication of data to the memories of multiple nodes of the system during execution. We examine in detail how the runtime system can achieve minimum application interruption, when failures occur. We present the design and implementation of FineFRC (Fine-grained Failure Recon guration on Clusters), a runtime system for achieving continuous operation of shared memory applications on commodity clusters without requiring application instrumentation or human intervention. We present results using a working, 16-processor system that achieves sub-second failure reconfiguration times.
Rosalia Christodoulopoulou, Kaloian Manassiev, Angelos Bilas, Cristiana Amza
PPoPP1
2003 Dynamic Data Replication: An Approach to Providing Fault-Tolerant Shared Memory Clusters
abstract
A challenging issue in today's server systems is to transparently deal with failures and application-imposed requirements for continuous operation. In this paper we address this problem in shared virtual memory (SVM) clusters at the programming abstraction layer. We design extensions to an existing SVM protocol that has been tuned for low-latency, high-bandwidth interconnects and SMP nodes and we achieve reliability through dynamic replication of application shared data and protocol information. Our extensions allow us to tolerate single (or multiple, but not simultaneous) node failures. We implement our extensions on a state-of-the-art cluster and we evaluate the common, failure-free case. We find that, although the complexity of our protocol is substantially higher than its failure-free counterpart, by taking advantage of architectural features of modern systems our approach imposes low overhead and can be employed for transparently dealing with system failures.
Rosalia Christodoulopoulou, Angelos Bilas
HPCA1