Re: [eigen] Custom memory allocation for SparseMatrix?

[Christoph Hertzberg <chtz@xxxxxxxxxxxxxxxxxxxxxxxx>]

C++ allows to globally overwrite new/delete like this:

  void* operator new (size_t size) {
    void *p=your_custom_malloc(size);
    // throw if malloc failed:
    if (p==0)  throw std::bad_alloc();
    return p;
  }
  void operator delete (void *p) {
    your_custom_free(p);
  }

But that would affect every new/delete.

If you don't want that, I guess there is no easy solution at the moment 
without changing the CompressedStorage class. An overly complicated 
alternative would be to work on custom-allocated Map<SparseMatrix>.

Would you like to change all SparseMatrix, or do you need to decide for 
each matrix where it shall be allocated (i.e., via a template parameter, 
such as in the std-containers)?

Furthermore, do you want the same for dynamic dense matrices? Then this 
BZ entry is related:
http://eigen.tuxfamily.org/bz/show_bug.cgi?id=166

Christoph



On 2016-04-15 13:22, Ola Røer Thorsen wrote:
> Hi,
>
> I'm using Eigen 3.2 on a STM32F7 arm mcu. Quite successfully so far!
>
> The memory on this device is separated into two parts, where there is some
> Tightly-Coupled Memory (64k) that we use for the stack and statically
> initialized variables. This memory is significantly faster to use compared
> with the normal memory.
>
> I want to use a sparse matrix for a calculation. As far as I can see
> SparseMatrix uses regular memory allocation from the heap (new/delete). In
> my case, this uses the regular "slow" memory. It runs ok, but I know there
> is much gain in using the DTCM memory.
>
> Is there some trivial way to make SparseMatrix use a custom allocator? I
> guess one alternative is to modify my version of Eigen so that the
> CompressedStorage class does something else than normal, but it would be
> nice not having to modify Eigen itself.
>
> Best regards,
> Ola Røer Thorsen

--
 Dipl. Inf., Dipl. Math. Christoph Hertzberg

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