Accurate Inter-Transaction Dependency Tracking for Repairable DBMS

2007 ◽  
Author(s):  
Shweta Bajpai ◽  
Alexey Smirnov ◽  
Tzi-cker Chiueh
Keyword(s):  
Dependency Tracking

Run-time dependency tracking in data centers

2010 ◽  
Author(s):  
Sangameshwar Patil ◽  
Guruprasad Aphale ◽  
Ankit Mehrotra ◽  
Harrick Vin ◽  
Rahul Kelkar
Keyword(s):  
Data Centers ◽  
Time Dependency ◽  
Dependency Tracking ◽  
Run Time

Optimistic distributed simulation based on transitive dependency tracking

1997 ◽  
Vol 27 (1) ◽  
pp. 90-97
Author(s):  
Om P. Damani ◽  
Yi-Min Wang ◽  
Vijay K. Garg
Keyword(s):  
Distributed Simulation ◽  
Simulation Based ◽  
Dependency Tracking

INCREMENTAL TRANSITIVE DEPENDENCY TRACKING IN DISTRIBUTED COMPUTATIONS

1996 ◽  
Vol 06 (03) ◽  
pp. 427-435 ◽  
Author(s):  
CLAUDE JARD ◽  
GUY-VINCENT JOURDAN
Keyword(s):  
Distributed Systems ◽  
Arbitrary Subset ◽  
Causal Dependency ◽  
Tracking Technique ◽  
Distributed Computations ◽  
Dependency Tracking ◽  
Observable Event ◽  
Direct Dependency

The notion of causal dependency between events in distributed systems plays a central role in reasoning about distributed program behaviours [14]. Different techniques have been designed to track these dependencies during execution. We suggest a new incremental transitive dependency tracking technique. Once the transitive dependencies are recorded for an observable event, the dependency tracking cost can be reduced by propagating only future dependencies beyond that event. Furthermore, in contrast with the direct dependency tracking technique already proposed in the literature, our technique allows to compute the dependencies among an arbitrary subset of observable events. This gives an interesting filtering capability.

scholarly journals BioShake: a Haskell EDSL for bioinformatics workflows

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e7223 ◽  
Author(s):  
Justin Bedő
Keyword(s):  
Parallel Execution ◽  
Reproducible Research ◽  
Domain Specific Language ◽  
Bioinformatics Analyses ◽  
Specific Language ◽  
Domain Specific ◽  
Link Type ◽  
Dependency Tracking ◽  
Bioinformatics Workflows

Typical bioinformatics analyses comprise of long running computational workflows. An important part of reproducible research is the management and execution of these workflows to allow robust execution and to minimise errors. BioShake is an embedded domain specific language in Haskell for specifying and executing computational workflows for bioinformatics that significantly reduces the possibility of errors occurring. Unlike other workflow frameworks, BioShake raises many properties to the type level allowing the correctness of a workflow to be statically checked during compilation, catching errors before any lengthy execution process. BioShake builds on the Shake build tool to provide robust dependency tracking, parallel execution, reporting, and resumption capabilities. Finally, BioShake abstracts execution so that jobs can either be executed directly or submitted to a cluster. BioShake is available at http://github.com/PapenfussLab/bioshake.

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