# ElasticSearch on giant compute nodes
**URL:** https://discuss.elastic.co/t/elasticsearch-on-giant-compute-nodes/343183
**Category:** Elasticsearch
**Created:** [September 16, 2023, 9:10pm UTC](https://discuss.elastic.co/t/elasticsearch-on-giant-compute-nodes/343183 "2023-09-16T21:10:30Z")
**Posts on this page:** 2
**Page:** 1
### Author:  [@Don\_Boscow](https://discuss.elastic.co/u/Don_Boscow)
#### Post date: [September 16, 2023, 9:10pm UTC](https://discuss.elastic.co/t/elasticsearch-on-giant-compute-nodes/343183/1 "2023-09-16T21:10:30Z")
The standard paradigm which I see is usually recommended for ES (mainly for query purpose) is a collection or cluster of nodes - the nodes being typically SSD, the RAM usually recommended as 64 GB, with shard size not exceeding 50 GB, and the overall node storage not more than 4 TB.
However, we have a scenario where we have supercomputers with large nodes in it - for example, one supercomputer has 39 nodes, each node having a powerful CPU (Intel Xeon Cascade Lake, 24 core, 2.8 GHz), say 768 GB of RAM, 480 GB of SSD.
Suppose 10 of them are made into a cluster. Thus the combined storage becomes around 5 TB. How well can this cluster perform for search queries, including latency? Does this setup work, or will it be a bad idea?
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### Author:  [@system](https://discuss.elastic.co/u/system)
#### Post date: [October 14, 2023, 9:10pm UTC](https://discuss.elastic.co/t/elasticsearch-on-giant-compute-nodes/343183/2 "2023-10-14T21:10:32Z")
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