# Operations¶

Like MPI collective operations, NCCL collective operations have to be called for each rank (hence CUDA device) to form a complete collective operation. Failure to do so will result in other ranks waiting indefinitely.

## AllReduce¶

The AllReduce operation is performing reductions on data (for example, sum, max) across devices and writing the result in the receive buffers of every rank.

The AllReduce operation is rank-agnostic. Any reordering of the ranks will not affect the outcome of the operations.

AllReduce starts with independent arrays Vk of N values on each of K ranks and ends with identical arrays S of N values, where S[i] = V0[i]+V1[i]+…+Vk-1[i], for each rank k.

Related links: `ncclAllReduce()`

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## Broadcast¶

The Broadcast operation copies an N-element buffer on the root rank to all ranks.

Important note: The root argument is one of the ranks, not a device number, and is therefore impacted by a different rank to device mapping.

Related links: `ncclBroadcast()`

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## Reduce¶

The Reduce operation is performing the same operation as AllReduce, but writes the result only in the receive buffers of a specified root rank.

Important note : The root argument is one of the ranks (not a device number), and is therefore impacted by a different rank to device mapping.

Note: A Reduce, followed by a Broadcast, is equivalent to the AllReduce operation.

Related links: `ncclReduce()`

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## AllGather¶

In the AllGather operation, each of the K processors aggregates N values from every processor into an output of dimension K*N. The output is ordered by rank index.

The AllGather operation is impacted by a different rank or device mapping since the ranks determine the data layout.

Note: Executing ReduceScatter, followed by AllGather, is equivalent to the AllReduce operation.

Related links: `ncclAllGather()`

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## ReduceScatter¶

The ReduceScatter operation performs the same operation as the Reduce operation, except the result is scattered in equal blocks among ranks, each rank getting a chunk of data based on its rank index.

The ReduceScatter operation is impacted by a different rank or device mapping since the ranks determine the data layout.

Related links: `ncclReduceScatter()`