cuda_memory_stats: Returns a dictionary of CUDA memory allocator statistics for...

View source: R/cuda.R

cuda_memory_statsR Documentation

Returns a dictionary of CUDA memory allocator statistics for a given device.

Description

The return value of this function is a dictionary of statistics, each of which is a non-negative integer.

Usage

cuda_memory_stats(device = cuda_current_device())

cuda_memory_summary(device = cuda_current_device())

Arguments

device

Integer value of the CUDA device to return capabilities of.

Core statistics

  • "allocated.all,large_pool,small_pool.current,peak,allocated,freed": number of allocation requests received by the memory allocator.

  • "allocated_bytes.all,large_pool,small_pool.current,peak,allocated,freed": amount of allocated memory.

  • "segment.all,large_pool,small_pool.current,peak,allocated,freed": number of reserved segments from cudaMalloc().

  • "reserved_bytes.all,large_pool,small_pool.current,peak,allocated,freed": amount of reserved memory.

  • "active.all,large_pool,small_pool.current,peak,allocated,freed": number of active memory blocks.

  • "active_bytes.all,large_pool,small_pool.current,peak,allocated,freed": amount of active memory.

  • "inactive_split.all,large_pool,small_pool.current,peak,allocated,freed": number of inactive, non-releasable memory blocks.

  • "inactive_split_bytes.all,large_pool,small_pool.current,peak,allocated,freed": amount of inactive, non-releasable memory.

For these core statistics, values are broken down as follows.

Pool type:

  • all: combined statistics across all memory pools.

  • large_pool: statistics for the large allocation pool (as of October 2019, for size >= 1MB allocations).

  • small_pool: statistics for the small allocation pool (as of October 2019, for size < 1MB allocations).

Metric type:

  • current: current value of this metric.

  • peak: maximum value of this metric.

  • allocated: historical total increase in this metric.

  • freed: historical total decrease in this metric.

Additional metrics

  • "num_alloc_retries": number of failed cudaMalloc calls that result in a cache flush and retry.

  • "num_ooms": number of out-of-memory errors thrown.


torch documentation built on June 10, 2022, 1:06 a.m.