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

In torch: Tensors and Neural Networks with 'GPU' Acceleration

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 May 29, 2024, 9:54 a.m.