R2cl is a proof of concept translator software that converts R or S language into Common Lisp with minimal features.
The R2cl compiler is a proof of concept translator that can seamlessly translate languages from R or S into Common Lisp. This software enables a massive increase in speed, with over 1000 times faster processing. It produces code that is equivalent to FORTRAN, Ada, or C. The installation process of R2cl requires the installation of CMU Common Lisp and R, both of which are usually included in most Linux distributions. Once installed, users can begin the process by going through the terminal and using the command "cd R2cl make."
R is a free software project that provides an implementation of the S language, which is typically used for statistical processing. Although R boasts a vast library of statistical functions, it needs an engine operating under an "infinite memory" model to execute, becoming slow as a result. Varying the language results in a dynamic execution engine. Expressive capabilities make straighforward implementations busy, slow and requires piecework of particular nature to compile to code as fast as FORTRAN.
On the other hand, Lisp, a language that uses the same execution model as R, is even more general and includes extensive features of macro and object orientation. The two main currents of Lisp include Scheme, known for simplicity and reductionism, and Common Lisp, an ISO standard that prioritizes efficient compilation. A complete translation is not an easy feat to achieve, and it requires an interpretation engine and the "infinite memory" machine combined with the generated code. However, it is still possible to compile parts of code as fast as FORTRAN based on the available capability of the efficient compiler featured in the CMU Common Lisp.
Since the semantics of R is a reductionist subset of the semantics of Scheme, translation of R to Scheme is easy, especially as the free implementation engine is actually a Scheme engine. The semantics of CommonLisp, on the other hand, are probably a superset of Scheme, which shows promise for easy translation of R. The available efficient compiler makes this project an interesting venture, especially with applications where speed is a necessity.
Many R applications do not require high speed, but some require massive processing times. Complete porting of R on CommonLisp is a vast project, but it is essential in enabling R users to meet the demands of applications that require not only statistical processing but also high-speed.
R is a free software project that provides an implementation of the S language, which is typically used for statistical processing. Although R boasts a vast library of statistical functions, it needs an engine operating under an "infinite memory" model to execute, becoming slow as a result. Varying the language results in a dynamic execution engine. Expressive capabilities make straighforward implementations busy, slow and requires piecework of particular nature to compile to code as fast as FORTRAN.
On the other hand, Lisp, a language that uses the same execution model as R, is even more general and includes extensive features of macro and object orientation. The two main currents of Lisp include Scheme, known for simplicity and reductionism, and Common Lisp, an ISO standard that prioritizes efficient compilation. A complete translation is not an easy feat to achieve, and it requires an interpretation engine and the "infinite memory" machine combined with the generated code. However, it is still possible to compile parts of code as fast as FORTRAN based on the available capability of the efficient compiler featured in the CMU Common Lisp.
Since the semantics of R is a reductionist subset of the semantics of Scheme, translation of R to Scheme is easy, especially as the free implementation engine is actually a Scheme engine. The semantics of CommonLisp, on the other hand, are probably a superset of Scheme, which shows promise for easy translation of R. The available efficient compiler makes this project an interesting venture, especially with applications where speed is a necessity.
Many R applications do not require high speed, but some require massive processing times. Complete porting of R on CommonLisp is a vast project, but it is essential in enabling R users to meet the demands of applications that require not only statistical processing but also high-speed.
What's New
Version 0.1: N/A