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| * Sparse numerical linear algebra | 1. Josh Kantor: Sparse numerical linear algebra |
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| * Pippenger's Algorithm for multivariate polynomial evaluation | * Tom Boothby: [http://cr.yp.to/papers/pippenger.pdf Pippenger's Algorithm] for multivariate polynomial evaluation |
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| * | * [:days3/sprints/exactlinalg: William Stein: Optimized exact sparse and dense linear algebra (especially for computing modular forms)] * David Harvey (+ possibly Martin Albrecht): multithreaded polynomial arithmetic in FLINT * David Roe: p-adics (extension fields) (David Harvey would like to help with this) * Tom Boothby: 3d object arithmetic / integration with tachyon * David Harvey: would like to experiment further with speeding up object construction == NOTE == It would be very good to do the following for each sprint project (on a separate page linked to from above). 1. create a specific detailed realistic list of goals. 2. list every possible problem they can think of that might cause problems for (a) 3. how many people are needed to do a) 4. background reading material that sprinters should look at (this could be papers or source code). 5. list anything else that could go wrong, and ways to deal with it. |
Sage Days 3 Coding Sprints
List your ideas for coding sprints here.
- Josh Kantor: Sparse numerical linear algebra
Tom Boothby: [http://cr.yp.to/papers/pippenger.pdf Pippenger's Algorithm] for multivariate polynomial evaluation
- [:days3/sprints/exactlinalg: William Stein: Optimized exact sparse and dense linear algebra (especially for computing modular forms)]
- David Harvey (+ possibly Martin Albrecht): multithreaded polynomial arithmetic in FLINT
- David Roe: p-adics (extension fields) (David Harvey would like to help with this)
- Tom Boothby: 3d object arithmetic / integration with tachyon
- David Harvey: would like to experiment further with speeding up object construction
NOTE
It would be very good to do the following for each sprint project (on a separate page linked to from above).
- create a specific detailed realistic list of goals.
- list every possible problem they can think of that might cause problems for (a)
- how many people are needed to do a)
- background reading material that sprinters should look at (this could be papers or source code).
- list anything else that could go wrong, and ways to deal with it.