MBrace: large-scale programming with F#
In this tutorial we will demonstrate MBrace, an F# open source framework for large-scale distributed computation and data processing. MBrace introduces a new programming model for declaring computation and managing distributed data based on monads (a.k.a. computation expressions) and provides an elastic, fault tolerant, multitasking cluster infrastructure for cloud services such as Windows Azure.
Using an example-led approach we will demonstrate the various features of the MBrace programming model including the monadic combinators Cloud.Parallel and Cloud.Choice, used to create powerful distributed workflows, distributed (ML style) ref cells and cloud sequences (distributed collections), used to store and process large scale data. Each aspect of the programming model will be introduced through simple examples with one main driving example - that of an efficient map-reduce - being iteratively improved by audience participation as new MBrace features are demonstrated.
At the end of the tutorial, the participants will have learned how existing functional programming idioms and patterns can be applied with MBrace to easily solve difficult problems of large scale computation and data processing, such as developing map-reduce or k-means algorithms, using distributed algebraic data structures, or even creating generic reusable libraries of these.
Gian Ntzik (Imperial College London/Nessos)
Gian is a PhD student in Imperial College London. When not researching in program reasoning and formal verification and developing new program logics for file systems, he collaborates with the gang at Nessos on MBrace, an open source framework for distributed/cloud computing and big data.
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