Is APL really processing arrays?
ACM SIGAPL APL Quote Quad
Content analysis of APL defined functions
APL '75 Proceedings of seventh international conference on APL
A software high performance APL interpreter
APL '79 Proceedings of the international conference on APL: part 1
Program analysis and code generation in an APL/370 compiler
IBM Journal of Research and Development
An APL/370 compiler and some performance comparisons with APL interpreter and FORTRAN
APL '86 Proceedings of the international conference on APL
Field results with the APL compiler
APL '86 Proceedings of the international conference on APL
On performance and space usage improvements for parallelized compiled APL code
APL '91 Proceedings of the international conference on APL '91
APL '93 Proceedings of the international conference on APL
Efficiency in the APL environment—a full arsenal for attacking CPU hogs
APL '85 Proceedings of the international conference on APL: APL and the future
Improving APL performance with custom written auxiliary processors
APL '85 Proceedings of the international conference on APL: APL and the future
An introduction to STSC's APL compiler
APL '85 Proceedings of the international conference on APL: APL and the future
A translator system for the MATLAB language: Research Articles
Software—Practice & Experience
Efficient Map Portrayal Using a General-Purpose Query Language
DEXA '09 Proceedings of the 20th International Conference on Database and Expert Systems Applications
Accelerating computationally intensive queries on massive earth science data: (system demonstration)
Proceedings of the EDBT/ICDT 2011 Workshop on Array Databases
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An analysis of the execution of several simple APL statements illustrates that interpretive overhead in the form of setup time is awesome, and is on the order of 100 times as much as the per-element time. Comparison with an experimental compiler for APL illustrates that the setup time can often be eliminated or reduced greatly, producing code fragments that are more than 300 times as fast in favorable cases. Further work on the compiler should make some compiled code fragments about 500 times as fast as interpreted programs in favorable cases. In less favorable cases, performance improvements of a factor of two are commonplace. Many opportunities remain to improve the performance in such cases. A production compiler based on this work might allow use of APL to solve problems that in the past have been prohibitively expensive for APL solution.