ML grid programming with ConCert

Grid computing has become increasingly popular with the growth of the Internet, especially in large-scale scientific computation. Computational Grids are characterized by their scale, their heterogeneity, and their unreliability, making the creation of Grid software quite a challenge. Security concerns make the deployment of Grid infrastructure similarly daunting. We argue that functional programming techniques, both wellknown and new, make an excellent practical foundation for Grid computing. We present a prototype Grid framework called ConCert built entirely in Standard ML which allows for the trustless dissemination of Grid programs through the use of certified code. The framework is fault-tolerant and relatively easy to implement, owing to a simplified network abstraction. This network abstraction is tedious to program for directly, so we present a high level ML-like language Grid/ML and a compiler Hemlock for the language. Categories and Subject Descriptors D.3.2 [Programming ...

• Type: Conference
• Year: 2006
• Where: ML
• Authors: Tom Murphy VII
• Keywords: Grid, Grid Computing, Machine Learning, ML 2006, Prototype Grid Framework