Advanced compiler optimizations for supercomputers
Communications of the ACM - Special issue on parallelism
Automatic translation of FORTRAN programs to vector form
ACM Transactions on Programming Languages and Systems (TOPLAS)
High-level semantic optimization of numerical codes
ICS '99 Proceedings of the 13th international conference on Supercomputing
A unified semantic approach for the vectorization and parallelization of generalized reductions
ICS '89 Proceedings of the 3rd international conference on Supercomputing
A case for source-level transformations in MATLAB
Proceedings of the 2nd conference on Domain-specific languages
Optimizing compilers for modern architectures: a dependence-based approach
Optimizing compilers for modern architectures: a dependence-based approach
MaJIC: compiling MATLAB for speed and responsiveness
PLDI '02 Proceedings of the ACM SIGPLAN 2002 Conference on Programming language design and implementation
Array form representation of idiom recognition system for numerical programs
Proceedings of the 2001 conference on APL: an arrays odyssey
High Performance Compilers for Parallel Computing
High Performance Compilers for Parallel Computing
Reducing and Vectorizing Procedures for Telescoping Languages
International Journal of Parallel Programming
An algebraic array shape inference system for MATLAB®
ACM Transactions on Programming Languages and Systems (TOPLAS)
Computing array shapes in MATLAB
LCPC'01 Proceedings of the 14th international conference on Languages and compilers for parallel computing
Static reuse distances for locality-based optimizations in MATLAB
Proceedings of the 24th ACM International Conference on Supercomputing
McFLAT: a profile-based framework for MATLAB loop analysis and transformations
LCPC'10 Proceedings of the 23rd international conference on Languages and compilers for parallel computing
Optimizing MATLAB through just-in-time specialization
CC'10/ETAPS'10 Proceedings of the 19th joint European conference on Theory and Practice of Software, international conference on Compiler Construction
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Matlab is a matrix-processing language that offers very efficient built-in operations for data organized in arrays. However Matlab operation is slow when the program accesses data through interpreted loops. Often during the development of a Matlab application writing loop-based code is more intuitive than crafting the data organization into arrays. Furthermore, many Matlab users do not command the linear algebra expertise necessary to write efficient code. Thus loop-based Matlab coding is a fairly common practice. This paper presents a tool that automatically converts loop-based Matlab code into equivalent array-based form and built-in Matlab constructs. Arraybased code is produced by checking the input and output dimensions of equations within loops, and by transposing terms when necessary to generate correct code. This paper also describes an extensible loop pattern database that allows user-defined patterns to be discovered and replaced by more efficient Matlab routines that perform the same computation. The safe conversion of loop-based into more efficient array-based code is made possible by the introduction of a new abstract representation for dimensions.