GSoC Progress - Week 1
Programming · GSoC · SymPyHi again, this post contains the first report of my GSoC progress, even though it's week 2.
Progress
I have completed the UnivariatePolynomial implementation in PR 454, the PR is reviewed and merged. This SymEngine class can handle univariate polynomials and can handle all the basic polynomial manipulation.
The current functionality of UnivariatePolynomial are:
* two constructors of UnivariatePolynomial class, one using a dict of degree to coefficient and other is using a dense vector of coefficients. Note that this implementation is sparse.
* printing, same output pattern as that of SymPy
* from_dict which returns the appropriate Basic type on passing the dict
* dict_add_term to add a new term to the dict
* max_coef(), diff(), eval() as the name suggests
* some bool check funtions to check specific cases like is_zero(), is_one(), etc.
* also the add, sub, neg and mul functions.
What I learnt here was having a testing environment setup first speeds up the process of implementation and things go in the right direction.
Report
The UnivariatePolynomial uses std::map, I plan to switch to std::unordered_map or other specialized data structures before benchmarking the class and comparing speeds so that we get a decent speed.
The, to be implemented, multivariate class will be called Polynomial. Note that two classes are high level, because they can take part in SymPy expressions.
The plan is to implement lower level classes with various data structures, as well as using Piranha. These lower level classes do not use RCP at all, thus they could be faster for some applications. The user could then call specialized classes if needed for a given application (if we implement any).
Targets for Week 2 and Week 3
First aim is to use the already implemented polynomials in rings in SymEngine, look at the expand2b benchmark and try to speed it up by:
* Making use of Piranha int
* Using Kronecker packing for exponents
If we get satisfactory speed, we wrap it in Polynomial class. This can further be optimized using our very own class Integer, where in it we switch between int and mpzclass automatically (we should use it everywhere in SymEngine instead of mpzclass) and hashmap in future.
Tasks
* have an option of Piranha in cmake
* code for packing exponents into machine int64
* try to use Piranha's integer to see how it performs
If time permits
* Implement faster hashmap this weekend with Shivam
That's all for now. Catch you next week.
Adiós