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 Below are archived releases for RAPIDS Accelerator for Apache Spark.
 
+## Release v23.12.1
+### Hardware Requirements:
+
+The plugin is tested on the following architectures:
+
+	GPU Models: NVIDIA V100, T4, A10/A100, L4 and H100 GPUs
+
+### Software Requirements:
+
+	OS: Ubuntu 20.04, Ubuntu 22.04, CentOS 7, or Rocky Linux 8
+
+	NVIDIA Driver*: R470+
+
+	Runtime: 
+		Scala 2.12, 2.13
+		Python, Java Virtual Machine (JVM) compatible with your spark-version. 
+
+		* Check the Spark documentation for Python and Java version compatibility with your specific 
+		Spark version. For instance, visit `https://spark.apache.org/docs/3.4.1` for Spark 3.4.1.
+
+	Supported Spark versions:
+		Apache Spark 3.2.0, 3.2.1, 3.2.2, 3.2.3, 3.2.4
+		Apache Spark 3.3.0, 3.3.1, 3.3.2, 3.3.3
+		Apache Spark 3.4.0, 3.4.1
+		Apache Spark 3.5.0
+	
+	Supported Databricks runtime versions for Azure and AWS:
+		Databricks 10.4 ML LTS (GPU, Scala 2.12, Spark 3.2.1)
+		Databricks 11.3 ML LTS (GPU, Scala 2.12, Spark 3.3.0)
+		Databricks 12.2 ML LTS (GPU, Scala 2.12, Spark 3.3.2)
+	
+	Supported Dataproc versions:
+		GCP Dataproc 2.0
+		GCP Dataproc 2.1
+	
+	Supported Dataproc Serverless versions:
+		Spark runtime 1.1 LTS
+
+*Some hardware may have a minimum driver version greater than R470. Check the GPU spec sheet
+for your hardware's minimum driver version.
+
+*For Cloudera and EMR support, please refer to the
+[Distributions](https://docs.nvidia.com/spark-rapids/user-guide/latest/faq.html#which-distributions-are-supported) section of the FAQ.
+
+### RAPIDS Accelerator's Support Policy for Apache Spark
+The RAPIDS Accelerator maintains support for Apache Spark versions available for download from [Apache Spark](https://spark.apache.org/downloads.html)
+
+### Download RAPIDS Accelerator for Apache Spark v23.12.1
+- **Scala 2.12:**
+  - [RAPIDS Accelerator for Apache Spark 23.12.1 - Scala 2.12 jar](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/23.12.1/rapids-4-spark_2.12-23.12.1.jar)
+  - [RAPIDS Accelerator for Apache Spark 23.12.1 - Scala 2.12 jar.asc](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/23.12.1/rapids-4-spark_2.12-23.12.1.jar.asc)
+
+- **Scala 2.13:**
+  - [RAPIDS Accelerator for Apache Spark 23.12.1 - Scala 2.13 jar](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.13/23.12.1/rapids-4-spark_2.13-23.12.1.jar)
+  - [RAPIDS Accelerator for Apache Spark 23.12.1 - Scala 2.13 jar.asc](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.13/23.12.1/rapids-4-spark_2.13-23.12.1.jar.asc)
+
+This package is built against CUDA 11.8. It is tested on V100, T4, A10, A100, L4 and H100 GPUs with 
+CUDA 11.8 through CUDA 12.0.
+
+### Verify signature
+* Download the [PUB_KEY](https://keys.openpgp.org/search?q=sw-spark@nvidia.com).
+* Import the public key: `gpg --import PUB_KEY`
+* Verify the signature for Scala 2.12 jar:
+    `gpg --verify rapids-4-spark_2.12-23.12.1.jar.asc rapids-4-spark_2.12-23.12.1.jar`
+* Verify the signature for Scala 2.13 jar:
+    `gpg --verify rapids-4-spark_2.13-23.12.1.jar.asc rapids-4-spark_2.13-23.12.1.jar`
+
+The output of signature verify:
+
+	gpg: Good signature from "NVIDIA Spark (For the signature of spark-rapids release jars) <sw-spark@nvidia.com>"
+
+### Release Notes
+New functionality and performance improvements for this release include:
+* Introduced support for chunked reading of ORC files.
+* Enhanced support for additional time zones and added stack function support.
+* Enhanced performance for join and aggregation operations.
+* Kernel optimizations have been implemented to improve Parquet read performance.
+* RAPIDS Accelerator also built and tested with Scala 2.13.
+* Last version to support Pascal-based Nvidia GPUs; discontinued in the next release.
+* Introduced support for parquet Legacy rebase mode (spark.sql.parquet.datetimeRebaseModeInRead=LEGACY and spark.sql.parquet.int96RebaseModeInRead=LEGACY)
+* Introduced support for Percentile function.
+* Delta lake 2.3 support.
+* Qualification and Profiling tool:
+	* Profiling Tool now processes Spark Driver log for GPU runs, enhancing feature analysis.
+	* Auto-tuner recommendations include AQE settings for optimized performance.
+	* New configurations in Profiler for enabling off-default features: udfCompiler, incompatibleDateFormats, hasExtendedYearValues.
+
+For a detailed list of changes, please refer to the
+[CHANGELOG](https://github.com/NVIDIA/spark-rapids/blob/main/CHANGELOG.md).
+
 ## Release v23.12.0
 ### Hardware Requirements: