AdcMemory

class libadcc.AdcMemory

Bases: pybind11_builtins.pybind11_object

Class controlling the memory allocations for adcc ADC calculations. Python binding to libadcc::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. the number of blocks handled simultaneously in a tensor contraction.

max_memory

Return the max_memory parameter value to which the class was initialised.

pagefile_directory

Return the pagefile_directory value: 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

Return the pagefile_directory value: Note: This value is only meaningful if allocator != “standard”

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.