Azure Synapse Analytics
An Azure analytics service that brings together data integration, enterprise data warehousing, and big data analytics. Previously known as Azure SQL Data Warehouse.
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How to enable hardware accelleration on Azure Synapse spark pools
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Bailey
0
Reputation points
I recently had my vGPU quota increased but unsure how I can utilize it.
In Azure portal, I don't see any options for hardware acceleration, nor is there an option to change node family and view GPU node sizes.
I realize this may be due to feature deprecation (when will Azure stop this?), are there any options to enable this?
Thank you and may God have mercy on Azure users.
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J N S S Kasyap 80 Reputation points Microsoft Vendor2025-02-21T02:58:33.95+00:00 Hi @Bailey
Thanks for posting your query!
Unfortunately, GPU-accelerated Spark pools in Azure Synapse Analytics have indeed been deprecated. According to Microsoft’s documentation and updates, the GPU-accelerated preview was tied to specific Apache Spark runtimes (notably Spark 3.1 and 3.2), and these have been retired.
The increased vGPU quota won’t translate to Synapse Spark pools because the framework to utilize GPUs within them has been phased out.
In the Azure Synapse portal, there is no option to select GPU-backed nodes for Spark pools, as GPU support for Spark pools has been deprecated.
There isn't an official timeline for complete discontinuation, as the feature is already considered retired. The key point is that this feature is no longer active, and Azure is not planning to reintroduce GPU support for Spark pools in Synapse.
If you want to use GPUs for Spark workloads, I suggest Azure Databricks as the primary alternative. Databricks has excellent support for GPU clusters (you can select the GPU-enabled nodes) and is tightly integrated with Spark.
I hope this information helps. Please do let us know if you have any further queries.
Kindly consider upvoting the comment if the information provided is helpful. This can assist other community members in resolving similar issues.
Thank you.
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