On Thu, 14 Mar 2019 at 21:19, Aaron Meurer wrote:
>
> I agree. The biggest challenge with symbolic matrices is expression
> blow up. In some cases it is unavoidable, for instance, symbolic
> eigenvalues/eigenvectors use the symbolic solutions to polynomials,
> which are complicated in the general
I have added case study for the performance issue i am working on.
https://github.com/sympy/sympy/wiki/GSoC-2019-Application-SHIKSHA-RAWAT-:-Benchmarks-and-performance
Please review the proposal and suggest changes.
I have not completed the implementation plans. But i will add that part too
by ton
I am currently trying to improve the performance in the PR
https://github.com/sympy/sympy/pull/16509
To complete my gsoc proposal should i write the way i am trying to improve
the performance and how i have planned to proceed ?
Because the idea of benchmarking and performance mainly involves tryi
Okay, i have continued the discussion on the issue itself.
On Sat, Mar 30, 2019 at 12:06 AM Aaron Meurer wrote:
> On Fri, Mar 29, 2019 at 12:07 PM Shiksha Rawat
> wrote:
> >
> > Thank you for the replies.
> >
> > As suggested by Aaron , I figured out ways to fix the performance of
> https://git
On Fri, Mar 29, 2019 at 12:07 PM Shiksha Rawat wrote:
>
> Thank you for the replies.
>
> As suggested by Aaron , I figured out ways to fix the performance of
> https://github.com/sympy/sympy/issues/16249.
> One of the easy way is to disable _find_localzeros
> The function is creating a set of non
Thank you for the replies.
As suggested by Aaron , I figured out ways to fix the performance of
https://github.com/sympy/sympy/issues/16249.
One of the easy way is to disable _find_localzeros
The function is creating a set of non-minimal(non-maximal) numbers and to
identify these it is making comp
We have a benchmark repository that is run periodically:
https://github.com/sympy/sympy_benchmarks
I recommend starting there. You can find a number of regressions that can
be investigated.
Jason
moorepants.info
+01 530-601-9791
On Wed, Mar 27, 2019 at 5:17 PM Aaron Meurer wrote:
> I agree wi
I agree with Oscar. I would also add that it's usually not trivial to
determine where the bottlenecks are in SymPy. So I would write more
about how you intend to profile the code.
Perhaps it would be useful to take an existing thing that is slow in
SymPy (you can use the performance issue label as
This looks like good work to do. I don't know how these applications
are evaluated but my thought if I was reviewing this would be that it
seems quite vague. This would probably be a more enticing proposal if
it had some specific suggestions of changes that would speed things
up.
I can tell you no
https://github.com/sympy/sympy/wiki/GSoC-2019-Application-SHIKSHA-RAWAT-:-Benchmarks-and-performance
I have designed a proposal for Benchmarks and Perfromance idea, though it
is not complete yet.
Can Jason Moore, Aaron and Oscar please review that and suggest changes?
On Tue, Mar 19, 2019 at 11
I did further digging on the idea mentioned by Jason Moore.
*Figuring out the main bottlenecks for sympy *: The best way to figure out
these bottlenecks would be to designing a typical problem for each module
for example mass spring damper for physics and computing time taken by
sympy to give the
I am really interested in taking up that idea. Can you suggest where or how
should I start from because up till now I was just focusing on the physics
module and benchmarks related to it?
I am still trying to find how could we optimize matrix operations.
On Fri, Mar 15, 2019 at 8:46 PM Jason Moor
The mechanics speedup idea is really just a narrow version of the profiling
and benchmarking idea (focuses on just a couple of packages). Maybe a
proposal that focuses on figuring out the main bottlenecks for sympy,
creating benchmarks for them, and then improving performance is a good
proposal ide
I agree. The biggest challenge with symbolic matrices is expression
blow up. In some cases it is unavoidable, for instance, symbolic
eigenvalues/eigenvectors use the symbolic solutions to polynomials,
which are complicated in the general case for n > 2.
One thing I meant by "overhead" is that if t
(Replying on-list)
On Thu, 14 Mar 2019 at 20:37, Alan Bromborsky wrote:
>
> Since most pc these days have multiple cores and threads what not use
> parallel algorithyms. For honesty I must state I have a vested interest
> since I have a pc with a threadripper cpu with 16 cores and 32 threads.
P
ince currently I am having my mid sems. I will respond
>> asap once I read it.
>>
>>
>>
>> Sent from Mail <https://go.microsoft.com/fwlink/?LinkId=550986> for
>> Windows 10
>>
>>
>>
>> *From: *Jason Moore
>> *Sent: *14 March 2019 22
>>
>>
>>
>> From: Jason Moore
>> Sent: 14 March 2019 22:56
>> To: sympy@googlegroups.com
>> Subject: Re: [sympy] Gsoc Project idea " Efficient Equation
>> ofMotionGenerationwith Python" discussion.
>>
>>
>>
>>
*To: *sympy@googlegroups.com
> *Subject: *Re: [sympy] Gsoc Project idea " Efficient Equation
> ofMotionGenerationwith Python" discussion.
>
>
>
> Work to speed up matrix algorithms given assumptions on matrices would
> help.
>
>
>
> Jason
>
> moorepa
Give me 2 days since currently I am having my mid sems. I will respond asap
once I read it.
Sent from Mail for Windows 10
From: Jason Moore
Sent: 14 March 2019 22:56
To: sympy@googlegroups.com
Subject: Re: [sympy] Gsoc Project idea " Efficient Equation
ofMotionGenerationwith Python"
19 matches
Mail list logo
