A first report on the A<sup>#</sup> compiler

Watt, Stephen M.; Broadbery, Peter; Dooley, Samuel S.; Iglio, Pietro; Morrison, Scott C.; Steinbach, Jonathan M.; Sutor, Robert S.

doi:10.1145/190347.190356

Cited by 22 publications

(17 citation statements)

References 11 publications

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“…(1) The definition of common object interfaces has been studied extensively in the context of computer algebra (Musser, 1975;Abdali et al, 1986;Jenks and Sutor, 1992;Monagan, 1993;Watt et al, 1994). The Standard Template Library of C++ (Musser and Saini, 1996) is an example from main-stream programming.…”

Section: Generic Programmingmentioning

confidence: 99%

Challenges of Symbolic Computation: My Favorite Open Problems

Kaltofen

2000

Journal of Symbolic Computation

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To Bobby F. Caviness on the occasion of his 60th birthdayThe success of the symbolic mathematical computation discipline is striking. The theoretical advances have been continuous and significant: Gröbner bases, the Risch integration algorithm, integer lattice basis reduction, hypergeometric summation algorithms, etc. From the beginning in the early 1960s, it has been the tradition of our discipline to create software that makes our ideas readily available to scientists, engineers, and educators: SAC-1, Reduce, Macsyma, etc. The commercial viability of our system products is proven by Maple and Mathematica.Today's user communities of symbolic computation systems are diverse: educators, engineers, stock market analysts, etc. The mathematics and computer science in the design and implementation of our algorithms are sophisticated. The research challenges in symbolic computation at the close of the twentieth century are formidable.I state my favorite eight open problems in symbolic computation. They range from problems in symbolic/numeric computing, symbolic algorithm synthesis, to system component construction. I have worked on seven of my problems and borrowed one from George Collins. I present background to each of my problems and a clear-cut test that evaluates whether a proposed attack has solved one of my problems. An additional ninth open problem by Rob Corless and David Jeffrey on complex function semantics is given in an appendix.

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Section: Generic Programmingmentioning

confidence: 99%

Challenges of Symbolic Computation: My Favorite Open Problems

Kaltofen

2000

Journal of Symbolic Computation

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“…We are investigating the possibility of incorporating the CMM in the run-time support used by FOAM (Watt et al, 1994b), the intermediate language of A# (Watt et al, 1994), a language for symbolic algebra. FOAM itself is implemented by translation into C code which uses a run-time support which includes a totally conservative garbage collector.…”

Section: Related and Future Workmentioning

confidence: 99%

Memory Mangement in the PoSSo Solver

Attardi

Flagella

1996

Journal of Symbolic Computation

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A uniform general purpose garbage collector may not always provide optimal performance. Sometimes an algorithm exhibits a predictable pattern of memory usage that could be exploited, delaying as much as possible the intervention of the collector. This requires a collector whose strategy can be customized to the need of an algorithm. We present a dynamic memory management framework which allows such customization, while preserving the convenience of automatic collection in the normal case. The Customizable Memory Management (CMM) organizes memory in multiple heaps, each one encapsulating a particular storage discipline. The default heap for collectable objects uses the technique of mostly copying garbage collection, providing good performance and memory compaction. Customization of the collector is achieved through object orientation by specialising the collector methods for each heap class. We describe how the CMM has been exploited in the implementation of the Buchberger algorithm, by using a special heap for temporary objects created during polynomial reduction. The solution drastically reduces the overall cost of memory allocation in the algorithm.

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“…Scratchpad later evolved into the Axiom system [1,24]. In the A# project [39,38], later renamed into Aldor, the language and compiler were redesigned from scratch and further purified.…”

Section: Introduction Motivation For a New Languagementioning

confidence: 99%

Overview of the Mathemagix Type System

Hoeven

2014

Computer Mathematics

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The goal of the Mathemagix project is to develop a new and free software for computer algebra and computer analysis, based on a strongly typed and compiled language. In this paper, we focus on the underlying type system of this language, which allows for heavy overloading, including parameterized overloading with parameters in so called "categories". The exposition is informal and aims at giving the reader an overview of the main concepts, ideas and differences with existing languages. In a forthcoming paper, we intend to describe the formal semantics of the type system in more details.

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A first report on the A^# compiler

Cited by 22 publications

References 11 publications

Challenges of Symbolic Computation: My Favorite Open Problems

Challenges of Symbolic Computation: My Favorite Open Problems

Memory Mangement in the PoSSo Solver

Overview of the Mathemagix Type System

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A first report on the A# compiler

Cited by 22 publications

References 11 publications

Challenges of Symbolic Computation: My Favorite Open Problems

Challenges of Symbolic Computation: My Favorite Open Problems

Memory Mangement in the PoSSo Solver

Overview of the Mathemagix Type System

Contact Info

Product

Resources

About

A first report on the A^# compiler