4. Occupancy Calculator Python Interface — NsightCompute 13.2 documentation
Description: Nsight Compute Occupancy Calculator Python Interface
Keywords: Occupancy Calculator Python Interface

# 4. Occupancy Calculator Python Interface

## 4.1. Introduction

NVIDIA Nsight Compute features a Python-based interface for performing occupancy calculations and analysis for kernels on NVIDIA GPUs. These APIs are designed to help developers understand and optimize the utilization of GPU resources to achieve better performance for their kernel.

The module is called `ncu_occupancy` and works on any Python version from 3.7 1. It can be found in the `extras/python` directory of your NVIDIA Nsight Compute package.

1

  On Linux machines you will also need a GNU-compatible libc and `libgcc_s.so`.

## 4.2. API Reference

This documents the content of the `ncu_occupancy` package which can be found in the `extras/python` directory of your NVIDIA Nsight Compute installation.

class ncu_occupancy.OccupancyCalculator

  Provide methods to calculate occupancy and analyze ways to improve it, for a given GPU.

  Parameters

    - computeCapabilityMajor (`int`) – The major compute capability version of the GPU.

    - computeCapabilityMinor (`int`) – The minor compute capability version of the GPU.

  Returns

    An instance of the occupancy calculator.

  Return type

    `OccupancyCalculator`

  get_occupancy_limiters(occupancy_parameters: ncu_occupancy.OccupancyParameters) → list

    Get the occupancy limiters for the given occupancy parameters.

    Parameters

      occupancy_parameters (`OccupancyParameters`) – The input parameters for the occupancy calculation.

    Returns

      `list` of `OccupancyLimiter`

  get_optimal_occupancy(occupancy_parameters: ncu_occupancy.OccupancyParameters, occupancy_variable_list: list = [<OccupancyVariable.THREADS_PER_BLOCK: 0>]) → dict

    Get the optimal occupancy configuration.

    Optimal occupancy is calculated by varying input occupancy variable values while keeping other occupancy variable values constant. If no input occupancy variable list provided then `OccupancyVariable.THREADS_PER_BLOCK` will be considered by default.

    Parameters

      - occupancy_parameters (`OccupancyParameters`) – The input parameters for the occupancy calculation.

      - occupancy_variable_list (`list` of `OccupancyVariable`, optional) – The list of occupancy variables to consider for optimal occupancy calculation. Only up to two occupancy variables can be specified. (default: `OccupancyVariable.THREADS_PER_BLOCK`)

    Returns

      The optimal occupancy configuration. The dictionary contains the following key-value pairs:

        - ’optimal_occupancy’: (`float`) The optimal occupancy.

        - ’occupancy_variable_config’:

            - For single occupancy variable input: `list` of `tuple` of ranges.

            - For two occupancy variables input: `list` of `tuple` of value combinations. The `tuple` contains the values in the same order as the input occupancy variable list.

    Return type

      `dict`

  get_resource_utilization(occupancy_parameters: ncu_occupancy.OccupancyParameters) → dict

    Get the resource utilization for the given occupancy parameters.

    Parameters

      occupancy_parameters (`OccupancyParameters`) – The input parameters for the occupancy calculation.

    Returns

      Resource utilization. The dictionary contains the following key-value pairs:

        - ’sm_occupancy’ : (`float`) The occupancy of the SMs.

        - ’allocated_blocks’ : (`int`) The number of allocated blocks out of the total possible blocks per SM.

        - ’resource_utilization’(`dict`) The resource utilization for each resource i.e. threads, registers, shared memory. The resource utilization dictionary contains the following key-value pairs:
            - ’<resource name>’: (`dict`) The resource utilization for the resource. The resource utilization dictionary contains the following key-value pairs:

                - ’resource_per_block’: (`int`) The resource utilized per block.

                - ’unused_resource_count’: (`int`) The unused resource count per SM.

                - ’unallocated_blocks’: (`int`) The number of unallocated blocks per SM.

    Return type

      `dict`

  get_sm_occupancy(occupancy_parameters: ncu_occupancy.OccupancyParameters) → float

    Calculate the occupancy of the SMs for the given occupancy parameters.

    Parameters

      occupancy_parameters (`OccupancyParameters`) – The input parameters for the occupancy calculation.

    Returns

      The occupancy of the SMs.

    Return type

      `float`

class ncu_occupancy.OccupancyLimiter

  Enum representing the occupancy limiters.

  REGISTERS

    Register usage is the occupancy limiter.

  SHARED_MEMORY

    Shared memory usage is the occupancy limiter.

  BLOCKS

    Block size is the occupancy limiter.

  BARRIERS

    Barrier usage is the occupancy limiter.

class ncu_occupancy.OccupancyParameters

  OccupancyParameters is a `dataclass` that holds configuration parameters for occupancy calculations.

  shared_mem_size

    Shared memory size configuration (bytes). (default: 0)

    Type

      int

  threads_per_block

    Number of threads per block. (default: 256)

    Type

      int

  registers_per_thread

    Number of registers per thread. (default: 32)

    Type

      int

  shared_mem_per_block

    Shared memory (bytes) per block. (default: 2048)

    Type

      int

  num_block_barriers

    Number of block barriers. (default: 1)

    Type

      int

class ncu_occupancy.OccupancyVariable

  Enum representing the occupancy variables.

  THREADS_PER_BLOCK

    Threads per block.

  REGISTERS_PER_THREAD

    Registers per thread.

  SHARED_MEMORY_PER_BLOCK

    Shared memory per block.

  BLOCK_BARRIERS

    Block barriers.

ncu_occupancy.get_gpu_data(major: int, minor: int) → dict

  Get the GPU data for the given compute capability version.

  Parameters

    - major (`int`) – The major compute capability version of the GPU.

    - minor (`int`) – The minor compute capability version of the GPU.

  Returns

    The GPU data for the given compute capability version. The dictionary contains the following key-value pairs:

      - ’cc_major’: (`int`) The major compute capability version of the GPU.

      - ’cc_minor’: (`int`) The minor compute capability version of the GPU.

      - ’sm_version’: (`str`) The SM version of the GPU.

      - ’chip_family’: (`str`) The chip family of the GPU.

      - ’threads_per_warp’: (`int`) The number of threads per warp.

      - ’max_warps_per_sm’: (`int`) The number of warps per SM.

      - ’max_threads_per_sm’: (`int`) The number of threads per SM.

      - ’max_thread_blocks_per_sm’: (`int`) The number of thread blocks per SM.

      - ’block_barriers_per_sm’: (`int`) The number of block barriers per SM.

      - ’smem_per_sm’: (`int`) The shared memory (bytes) per SM.

      - ’max_shared_mem_per_block’: (`int`) The maximum shared memory (bytes) per block.

      - ’registers_per_sm’: (`int`) The registers per SM.

      - ’max_regs_per_block’: (`int`) The maximum registers per block.

      - ’max_regs_per_thread’: (`int`) The maximum registers per thread.

      - ’reg_allocation_unit_size’: (`int`) The register allocation unit size.

      - ’reg_allocation_granularity’: (`str`) The register allocation granularity.

      - ’shared_mem_allocation_unit_size’: (`int`) The shared memory allocation unit size.

      - ’warps_allocation_granularity’: (`str`) The warp allocation granularity.

      - ’max_thread_block_size’: (`int`) The maximum thread block size.

      - ’shared_mem_size_configs’: (`list` of `int`) The shared memory size configurations (bytes).

      - ’warp_reg_allocation_granularities’: (`list` of `int`) The warp register allocation granularities.

  Return type

    `dict`