@booklet {,
	title = {XaaS: Acceleration as a Service to Enable Productive High-Performance Cloud Computing},
	year = {2024},
	month = {2024-01},
	publisher = {arXiv},
	abstract = {HPC and Cloud have evolved independently, specializing their innovations into performance or productivity. Acceleration as a Service (XaaS) is a recipe to empower both fields with a shared execution platform that provides transparent access to computing resources, regardless of the underlying cloud or HPC service provider. Bridging HPC and cloud advancements, XaaS presents a unified architecture built on performance-portable containers. Our converged model concentrates on low-overhead, high-performance communication and computing, targeting resource-intensive workloads from climate simulations to machine learning. XaaS lifts the restricted allocation model of Function-as-a-Service (FaaS), allowing users to benefit from the flexibility and efficient resource utilization of serverless while supporting long-running and performance-sensitive workloads from HPC.},
	url = {https://arxiv.org/abs/2401.04552},
	author = {Torsten Hoefler and Marcin Copik and Pete Beckman and Andrew Jones and Ian Foster and Manish Parashar and Daniel Reed and Matthias Troyer and Thomas Schulthess and Dan Ernst and Jack Dongarra}
}
@techreport {872,
	title = {Practical Scalable Consensus for Pseudo-Synchronous Distributed Systems: Formal Proof},
	journal = {Innovative Computing Laboratory Technical Report},
	number = {ICL-UT-15-01},
	year = {2015},
	month = {2015-04},
	author = {Thomas Herault and Aurelien Bouteiller and George Bosilca and Marc Gamell and Keita Teranishi and Manish Parashar and Jack Dongarra}
}
@conference {889,
	title = {Practical Scalable Consensus for Pseudo-Synchronous Distributed Systems},
	booktitle = {The International Conference for High Performance Computing, Networking, Storage and Analysis (SC15)},
	year = {2015},
	month = {2015-11},
	publisher = {ACM},
	organization = {ACM},
	address = {Austin, TX},
	abstract = {The ability to consistently handle faults in a distributed environment requires, among a small set of basic routines, an agreement algorithm allowing surviving entities to reach a consensual decision between a bounded set of volatile resources. This paper presents an algorithm that implements an Early Returning Agreement (ERA) in pseudo-synchronous systems, which optimistically allows a process to resume its activity while guaranteeing strong progress. We prove the correctness of our ERA algorithm, and expose its logarithmic behavior, which is an extremely desirable property for any algorithm which targets future exascale platforms. We detail a practical implementation of this consensus algorithm in the context of an MPI library, and evaluate both its efficiency and scalability through a set of benchmarks and two fault tolerant scientific applications.},
	author = {Thomas Herault and Aurelien Bouteiller and George Bosilca and Marc Gamell and Keita Teranishi and Manish Parashar and Jack Dongarra}
}
@inproceedings {icl:98,
	title = {Experiments with Scheduling Using Simulated Annealing in a Grid Environment},
	journal = {Grid Computing - GRID 2002, Third International Workshop},
	volume = {2536},
	year = {2002},
	month = {2002-11},
	pages = {232-242},
	publisher = {Springer},
	address = {Baltimore, MD},
	keywords = {grads},
	author = {Asim YarKhan and Jack Dongarra},
	editor = {Manish Parashar}
}
@inproceedings {icl:187,
	title = {Overview of GridRPC: A Remote Procedure Call API for Grid Computing},
	journal = {Proceedings of the Third International Workshop on Grid Computing},
	year = {2002},
	month = {2002-01},
	pages = {274-278},
	author = {Keith Seymour and Hidemoto Nakada and Satoshi Matsuoka and Jack Dongarra and Craig Lee and Henri Casanova},
	editor = {Manish Parashar}
}
