Memory Handling (GNU MPFR 4.2.1)
Description: How to install and use GNU MPFR, a library for reliable multiple precision floating-point arithmetic, version 4.2.1.

### 4.7 Memory Handling

MPFR functions may create caches, e.g., when computing constants such as Pi, either because the user has called a function like `mpfr_const_pi` directly or because such a function was called internally by the MPFR library itself to compute some other function. When more precision is needed, the value is automatically recomputed; a minimum of 10% increase of the precision is guaranteed to avoid too many recomputations.

MPFR functions may also create thread-local pools for internal use to avoid the cost of memory allocation. The pools can be freed with `mpfr_free_pool` (but with a default MPFR build, they should not take much memory, as the allocation size is limited).

At any time, the user can free various caches and pools with `mpfr_free_cache` and `mpfr_free_cache2`. It is strongly advised to free thread-local caches before terminating a thread, and all caches before exiting when using tools like ‘`valgrind`’ (to avoid memory leaks being reported).

MPFR allocates its memory either on the stack (for temporary memory only) or with the same allocator as the one configured for GMP: see Section “Custom Allocation” in GNU MP. This means that the application must make sure that data allocated with the current allocator will not be reallocated or freed with a new allocator. So, in practice, if an application needs to change the allocator with `mp_set_memory_functions`, it should first free all data allocated with the current allocator: for its own data, with `mpfr_clear`, etc.; for the caches and pools, with `mpfr_mp_memory_cleanup` in all threads where MPFR is potentially used. This function is currently equivalent to `mpfr_free_cache`, but `mpfr_mp_memory_cleanup` is the recommended way in case the allocation method changes in the future (for instance, one may choose to allocate the caches for floating-point constants with `malloc` to avoid freeing them if the allocator changes). Developers should also be aware that MPFR may also be used indirectly by libraries, so that libraries based on MPFR should provide a clean-up function calling `mpfr_mp_memory_cleanup` and/or warn their users about this issue.

Note: For multithreaded applications, the allocator must be valid in all threads where MPFR may be used; data allocated in one thread may be reallocated and/or freed in some other thread.

MPFR internal data such as flags, the exponent range, the default precision, and the default rounding mode are either global (if MPFR has not been compiled as thread safe) or per-thread (thread-local storage, TLS). The initial values of TLS data after a thread is created entirely depend on the compiler and thread implementation (MPFR simply does a conventional variable initialization, the variables being declared with an implementation-defined TLS specifier).

Writers of libraries using MPFR should be aware that the application and/or another library used by the application may also use MPFR, so that changing the exponent range, the default precision, or the default rounding mode may have an effect on this other use of MPFR since these data are not duplicated (unless they are in a different thread). Therefore any such value changed in a library function should be restored before the function returns (unless the purpose of the function is to do such a change). Writers of software using MPFR should also be careful when changing such a value if they use a library using MPFR (directly or indirectly), in order to make sure that such a change is compatible with the library.