Applicability

Product	Supported
Atlas 350 Accelerator Card	√
Atlas A3 training product/Atlas A3 inference product	√
Atlas A2 training product/Atlas A2 inference product	√
Atlas 200I/500 A2 inference product	☓
Atlas inference product	√
Atlas training product	√

For Atlas A2 training product/Atlas A2 inference product, only the Atlas 800T A2 training server, Atlas 900 A2 PoD cluster basic unit, and Atlas 200T A2 Box16 heterogeneous subrack are supported.

For the Atlas inference products, only the Atlas 300I Duo inference card is supported.

Function

Sets a gradient segmentation strategy in a collective communication group based on the proportion of gradient data to implement AllReduce fusion and optimize the collective communication performance.

Prototype

def set_split_strategy_by_size(dataSizeList, group="hccl_world_group")

Parameters

Parameter	Input/Output	Description
dataSizeList	Input	A list. List of gradient parameter data volume percentages. The index ID list of the gradient must be non-negative, and the total percentage of the gradient data volume sequence must be 100. A maximum of eight gradient segments are supported. For example, if the model has 150 MB gradient data and needs to be divided into three segments: 90 MB, 30 MB, and 30 MB, set dataSizeList to [60, 20, 20].
group	Input	A string containing a maximum of 128 bytes, including the end character. Group name, which can be a user-defined value or hccl_world_group. Defaults to hccl_world_group.

Parameter

Input/Output

Description

dataSizeList

Input

A list.

List of gradient parameter data volume percentages.

The index ID list of the gradient must be non-negative, and the total percentage of the gradient data volume sequence must be 100.
A maximum of eight gradient segments are supported.
For example, if the model has 150 MB gradient data and needs to be divided into three segments: 90 MB, 30 MB, and 30 MB, set dataSizeList to [60, 20, 20].

group

Input

A string containing a maximum of 128 bytes, including the end character.

Group name, which can be a user-defined value or hccl_world_group. Defaults to hccl_world_group.

Returns

None

Constraints

The caller rank must be within the range defined by the group argument passed to this API call. Otherwise, the API call fails.
When the backward gradient segmentation policy is set based on both the gradient data volume percentage and the gradient index ID, the setting result based on the gradient data volume percentage is preferred.
If you do not call the gradient segmentation API to set the segmentation policy, the default backward gradient segmentation policy is used.
Default segmentation strategy: The optimal segmentation location of ResNet-50 is as follows: ResNet-50 is divided into two segments based on the gradient data size. The data size of the first segment is 96.54%, and that of the second segment is 3.46%.

Call Example

from hccl.split.api import *
set_split_strategy_by_size([60, 20, 20], "group")