AdcMemory¶
-
class
libadcc.
AdcMemory
¶ Bases:
pybind11_builtins.pybind11_object
Class controlling the memory allocations for adcc ADC calculations. Python binding to
adcc::AdcMemory
.Attributes Summary
allocator
Return the allocator to which the class is initialised. contraction_batch_size
Get or set the batch size for contraction, i.e. max_memory
Return the max_memory parameter value to which the class was initialised. pagefile_directory
Note: This value is only meaningful if allocator != “standard” tensor_block_size
Return the tensor_block_size parameter. Methods Summary
initialise
(self, arg0, arg1, arg2, arg3)Initialise the adcc memory management. Attributes Documentation
-
allocator
¶ Return the allocator to which the class is initialised.
-
contraction_batch_size
¶ Get or set the batch size for contraction, i.e. the number of blocks handled simultaneously in a tensor contraction.
-
max_memory
¶ Return the max_memory parameter value to which the class was initialised. Note: This value is only a meaningful upper bound if allocator != “standard”
-
pagefile_directory
¶ Note: This value is only meaningful if allocator != “standard”
Type: Return the pagefile_directory value
-
tensor_block_size
¶ Return the tensor_block_size parameter.
Methods Documentation
-
initialise
(self: libadcc.AdcMemory, arg0: str, arg1: int, arg2: int, arg3: str) → None¶ Initialise the adcc memory management.
@param max_memory Estimate for the maximally employed memory @param tensor_block_size This parameter roughly has the meaning
of how many indices are handled together on operations. A good value is 16 for most nowaday CPU cachelines.- @param pagefile_prefix Directory prefix for storing temporary
- cache files.
- @param allocator The allocator to be used. Valid values are “libxm”,
- “libvmm”, “standard” and “default”, where “default” uses a default chosen from the first three.
-