Enable Recording of Memory Allocation Stack Traces — cuda_record_memory

Enables recording of stack traces associated with memory allocations, allowing users to identify the source of memory allocation in CUDA snapshots.

Usage

cuda_record_memory_history(
  enabled,
  context = "all",
  stacks = "all",
  max_entries = 1
)

Arguments

enabled

Character or NULL. Controls memory history recording. Options:

NULL: Disable recording of memory history.
"state": Record currently allocated memory information.
"all": Record the history of all allocation and free events (default).

context

Character or NULL. Controls traceback recording. Options:

NULL: Do not record any tracebacks.
"state": Record tracebacks for currently allocated memory.
"alloc": Record tracebacks for allocation events.
"all": Record tracebacks for both allocation and free events (default).

stacks

Character. Defines the stack trace frames to include. Options:

"all": Include all frames (default).

max_entries

Integer. The maximum number of allocation/free events to retain.

Value

None; function invoked for side effects.

Details

Alongside tracking stack traces for each current allocation and free event, this function can also keep a historical log of all allocation and free events.

Use cuda_memory_snapshot() to retrieve recorded information. Visualization can be performed using pytorch.org/memory_viz.

Examples

if (torch_is_installed()) {
if (FALSE) { # \dontrun{
cuda_record_memory_history(enabled = 'all', context = 'all', stacks = 'all', max_entries = 10000)
} # }
}