[DOCS] Add release note for SystemDS 2.1.0

Refer: https://s.apache.org/systemds-2.1.0-release-notes-mail-list-discussion
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+---
+layout: page
+title: SystemDS 2.1.0 Release Notes
+description: Project Release Notes
+group: nav-right
+---
+<!--
+{% comment %}
+Licensed to the Apache Software Foundation (ASF) under one or more
+contributor license agreements.  See the NOTICE file distributed with
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+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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+{% endcomment %}
+-->
+
+<section class="full-stripe full-stripe--subpage-header clear-header">
+  <div class="ml-container ml-container--horizontally-center">
+    <div class="col col-12 content-group content-group--center-content content-group--center-align">
+      <h1>{{ site.data.project.name }} 2.1.0 Release Notes</h1>
+    </div>
+  </div>
+</section>
+
+<section class="full-stripe full-stripe--alternate">
+  <div class="ml-container">
+    <div class="col col-12 content-group content-group--medium-bottom-margin" markdown="1">
+
+## Release notes for SystemDS 2.1.0
+
+SystemDS 2.1 is a minor release. This release contains major improvements
+to existing features, a large number of fixes, and some experimental
+features to better support the end-to-end data science lifecycle.
+In addition to that, this is the last release with Java 8 and Spark 2.x.
+
+The major changes (compared to SystemDS 2.0) include
+
+- Federated Backend: Extended operations and built-ins to support various
+workflows and algorithms. Extended parameter server for federated training
+of Neural Networks.
+- A wealth of new and improved built-in functions including support for
+string operations, time-series analysis, data cleaning, grid search
+hyperparameter tuning, multi-threaded feature transformations.
+- Better support for Eval and list data structure.
+- Various performance improvements in SystemDS' local, distributed, and
+native runtimes.
+- Python API: Source functionality to allow arbitrary DML script,
+auto-generated Python API for all built-in functions,  list support
+allowing Pytonic access and manipulation of lazily evaluated DML elements,
+multi return continuation, allowing continued execution past calls to
+builtin functions.
+- GPU Backend: Various performance improvements and fixes, cuda code
+refactor, cuda code generation [experimental].
+- Lineage Tracing and Reuse: Initial support for federated and GPU
+backends, new hybrid lineage deduplication and reuse of compressed lineage
+DAGs, lineage cache benefits estimator, improved cache eviction logic.
+- Usability: Better Log4j integration, debug flag to reduce error logging,
+support for remote debugging.
+- Miscellaneous Improvements: Improved documentation, better testing,
+streamlined release process.