You are provided with the abstract of a scientific paper and the abstracts of the papers it references. Your task is to write a Related Work section for the main paper. This section should concisely summarize and integrate the key points from the cited abstracts, reflecting how they relate to the main paper's contributions and context. In your summary, use numerical citation markers like [1], [2], etc., to refer to the corresponding papers.

Main Abstract:
The work reported in this paper is motivated towards validating an alternative approach for fault tolerance over traditional methods like checkpointing that constrain efficacious fault tolerance. Can agent intelligence be used to achieve fault tolerant parallel computing systems? If so, "What agent capabilities are required for fault tolerance?", "What parallel computational tasks can benefit from such agent capabilities?" and "How can agent capabilities be implemented for fault tolerance?" need to be addressed. Cognitive capabilities essential for achieving fault tolerance through agents are considered. Parallel reduction algorithms are identified as a class of algorithms that can benefit from cognitive agent capabilities. The Message Passing Interface is utilized for implementing an intelligent agent based approach. Preliminary results obtained from the experiments validate the feasibility of an agent based approach for achieving fault tolerance in parallel computing systems.

Cited Abstract(s):
[1]: Fault tolerant MPI (FTMPI) enables fault tolerance to the MPICH, an open source GPL licensed implementation of MPI standard by Argonne National Laboratory's Mathematics and Computer Science Division. FTMPI is a transparent fault-tolerant environment, based on synchronous checkpointing and restarting mechanism. FTMPI relies on non-multithreaded single process checkpointing library to synchronously checkpoint an application process. Global replicated system controller and cluster node specific node controller monitors and controls check pointing and recovery activities of all MPI applications within the cluster. This work details the architecture to provide fault tolerance mechanism for MPI based applications running on clusters and the performance of NAS parallel benchmarks and parallelized medium range weather forecasting models, P-T80 and P-TI26. The architecture addresses the following issues also: Replicating system controller to avoid single point of failure. Ensuring consistency of checkpoint files based on distributed two phase commit protocol, and robust fault detection hierarchy.
In [1] , fault tolerant MPI comprising a replicated system controller, a node controller and checkpoint server tested on a parallelized weather model is introduced. The fault tolerant version is designed to address single point failures, ensure consistency of checkpoint files and robustness of fault detection hierarchy.