Theory of linear and integer programming
Theory of linear and integer programming
ACM Transactions on Database Systems (TODS)
A data locality optimizing algorithm
PLDI '91 Proceedings of the ACM SIGPLAN 1991 conference on Programming language design and implementation
Some efficient solutions to the affine scheduling problem: I. One-dimensional time
International Journal of Parallel Programming
Compiler optimizations for improving data locality
ASPLOS VI Proceedings of the sixth international conference on Architectural support for programming languages and operating systems
The Organization of Computations for Uniform Recurrence Equations
Journal of the ACM (JACM)
Efficient and extensible algorithms for multi query optimization
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Code Generation in the Polyhedral Model Is Easier Than You Think
Proceedings of the 13th International Conference on Parallel Architectures and Compilation Techniques
QPipe: a simultaneously pipelined relational query engine
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
Semi-automatic composition of loop transformations for deep parallelism and memory hierarchies
International Journal of Parallel Programming
Cooperative scans: dynamic bandwidth sharing in a DBMS
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
A practical automatic polyhedral parallelizer and locality optimizer
Proceedings of the 2008 ACM SIGPLAN conference on Programming language design and implementation
Improving data locality by chunking
CC'03 Proceedings of the 12th international conference on Compiler construction
The DataPath system: a data-centric analytic processing engine for large data warehouses
Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
Overview of sciDB: large scale array storage, processing and analysis
Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
isl: an integer set library for the polyhedral model
ICMS'10 Proceedings of the Third international congress conference on Mathematical software
The polyhedral model is more widely applicable than you think
CC'10/ETAPS'10 Proceedings of the 19th joint European conference on Theory and Practice of Software, international conference on Compiler Construction
Polyhedral code generation in the real world
CC'06 Proceedings of the 15th international conference on Compiler Construction
Just-in-time compilation for SQL query processing
Proceedings of the VLDB Endowment
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Big array analytics is becoming indispensable in answering important scientific and business questions. Most analysis tasks consist of multiple steps, each making one or multiple passes over the arrays to be analyzed and generating intermediate results. In the big data setting, I/O optimization is a key to efficient analytics. In this paper, we develop a framework and techniques for capturing a broad range of analysis tasks expressible in nested-loop forms, representing them in a declarative way, and optimizing their I/O by identifying sharing opportunities. Experiment results show that our optimizer is capable of finding execution plans that exploit nontrivial I/O sharing opportunities with significant savings.