# Indexing vector data and force-merging
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Once you've created a GPU-accelerated vector index on your domain or collection, you can add vector data and optimize your index using standard OpenSearch operations. GPU-acceleration automatically enhances both indexing performance and force-merge operations, making it faster to build and maintain large-scale vector search applications without requiring changes to your existing workflows.

## Indexing vector data
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Index vector data as you normally would. The GPU-acceleration automatically applies to indexing and force-merge operations. The following example demonstrates how to add vector documents to your index using the [bulk](https://docs.opensearch.org/latest/api-reference/document-apis/bulk/#index) API. Each document contains a vector field with numerical values and associated text content:

```
POST _bulk
{"index": {"_index": "my-vector-index"}}
{"vector_field": [0.1, 0.2, 0.3, ...], "text": "Sample document 1"}
{"index": {"_index": "my-vector-index"}}
{"vector_field": [0.4, 0.5, 0.6, ...], "text": "Sample document 2"}
```

### Force-merge operations
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GPU-acceleration also applies to [force-merge](https://docs.opensearch.org/latest/api-reference/index-apis/force-merge/) operations, which can significantly reduce the time required to optimize vector indexes. Note that force-merge operations aren't supported on collections. The following example demonstrates how to optimize your vector index by consolidating all segments into a single segment:

```
POST my-vector-index/_forcemerge?max_num_segments=1
```