Add Crystal Language, deepstreamHub, dynamorio and WRF files.

content/opensource_packages/Crystal-Language.md

@@ -0,0 +1,30 @@
+---
+name: Crystal Language
+category: OS & Languages
+description: Crystal is a programming language designed for efficiency and performance, with a syntax similar to Ruby.
+download_url: https://github.com/crystal-lang/crystal/releases
+works_on_arm: true
+supported_minimum_version:
+    version_number: 0.20.0
+    release_date: 2016/11/22
+
+
+optional_info:
+    homepage_url: https://crystal-lang.org/
+    support_caveats:
+    alternative_options:
+    getting_started_resources:
+        arm_content:
+        partner_content:
+        official_docs: https://crystal-lang.org/reference/1.12/getting_started/index.html
+    arm_recommended_minimum_version:
+        version_number:
+        release_date:
+
+
+optional_hidden_info:
+    release_notes__supported_minimum: https://github.com/crystal-lang/crystal/releases/tag/0.20.0
+    release_notes__recommended_minimum:
+    other_info:
+
+---

content/opensource_packages/deepstreamHub.md

@@ -0,0 +1,30 @@
+---
+name: DeepstreamHub
+category: Messaging/Comms
+description: DeepstreamHub is a platform designed to handle real-time data streams, enabling applications to process and react to data instantly.
+download_url: https://github.com/deepstreamIO/deepstream.io/releases
+works_on_arm: true
+supported_minimum_version:
+    version_number: v6.0.0
+    release_date: 2021/12/13
+
+
+optional_info:
+    homepage_url: https://deepstreamhub.com/
+    support_caveats:
+    alternative_options:
+    getting_started_resources:
+        arm_content:
+        partner_content:
+        official_docs: https://deepstreamhub.com/tutorials/getting-started/node/
+    arm_recommended_minimum_version:
+        version_number:
+        release_date:
+
+
+optional_hidden_info:
+    release_notes__supported_minimum:
+    release_notes__recommended_minimum:
+    other_info: Linux/ARM64 release notes are not available. Installation and testing are done via the [tar archive](https://github.com/deepstreamIO/deepstream.io/releases/tag/v6.0.0).
+
+---

content/opensource_packages/dynamorio.md

@@ -0,0 +1,30 @@
+---
+name: DynamoRio
+category: Runtimes
+description: DynamoRIO is a dynamic binary instrumentation tool that provides a runtime code manipulation system.
+download_url: https://github.com/DynamoRIO/dynamorio/releases
+works_on_arm: true
+supported_minimum_version:
+    version_number: 7.0.0-RC1
+    release_date: 2017/02/04
+
+
+optional_info:
+    homepage_url: https://dynamorio.org/
+    support_caveats:
+    alternative_options:
+    getting_started_resources:
+        arm_content: https://community.arm.com/arm-community-blogs/b/high-performance-computing-blog/posts/emulating-sve-on-armv8-using-dynamorio-and-armie
+        partner_content:
+        official_docs: https://dynamorio.org/page_user_docs.html
+    arm_recommended_minimum_version:
+        version_number:
+        release_date:
+
+
+optional_hidden_info:
+    release_notes__supported_minimum: https://github.com/DynamoRIO/dynamorio/releases/tag/release_7_0_0_rc1
+    release_notes__recommended_minimum:
+    other_info:
+
+---

content/opensource_packages/wrf.md

@@ -1,12 +1,12 @@
 ---
-name: Weather Research & Forecasting Model (WRF)
+name: Weather Research and Forecasting (WRF)
 category: HPC
-description: The Weather Research & Forcasting Model is a state of the art mesoscale numerical weather prediction system. It is designed for operational forecasting applications and atmospheric research.
+description: Weather Research and Forecasting (WRF) model is a numerical weather prediction (NWP) system designed for both atmospheric research and operational forecasting applications.
 download_url: https://github.com/wrf-model/WRF/releases
 works_on_arm: true
 supported_minimum_version:
-    version_number: 3.9.1.1
-    release_date: 2020/08/17
+    version_number: v4.2.2
+    release_date: 2021/01/15
 
 
 optional_info:
@@ -15,15 +15,16 @@ optional_info:
     alternative_options:
     getting_started_resources:
         arm_content: https://community.arm.com/arm-community-blogs/b/high-performance-computing-blog/posts/bringing-wrf-up-to-speed-with-arm-neoverse
-        partner_content: 
-        official_docs: 
+        partner_content: https://aws.amazon.com/blogs/hpc/numerical-weather-prediction-on-aws-graviton2/
+        official_docs: https://www.mmm.ucar.edu/models/wrf/support
     arm_recommended_minimum_version:
         version_number:
         release_date:
 
+
 optional_hidden_info:
     release_notes__supported_minimum: 
     release_notes__recommended_minimum:
-    other_info: No release notes found before v4, but proven to work in the Arm blog linked in Arm content.
+    other_info: AArch64 support was added in the PR(https://github.com/wrf-model/WRF/pull/1301). The PR got merged in Dec 2020 and the next release after the merge is v4.2.2. Tested v4.2.2(https://github.com/wrf-model/WRF/releases/tag/v4.2.2) version and it works on AArch64.
 
 ---