Merge pull request #855 from ArmDeveloperEcosystem/main

Ecosystem Dashboard: Add New AI, ML, Media, and Developer Tools

Author: ranimandepudi

content/commercial_packages/canonical-ceph.md

@@ -1,21 +1,21 @@
 ---
-name: Canonical's Distribution of Kubernetes (CDK)
+name: Canonical Kubernetes
 vendor: Canonical
 category: Containers and Orchestration
-description: Canonical's Distribution of Kubernetes (CDK) is Canonical’s fully upstream, secure, and automated Kubernetes distribution, designed for easy deployment and maintenance across bare metal, public clouds, and edge environments. It enables rapid access to upstream features, hassle-free cluster management, and long-term stability for production-grade container orchestration.
+description: Canonical Kubernetes is Canonical’s fully upstream, secure, and automated Kubernetes distribution, designed for easy deployment and maintenance across bare metal, public clouds, and edge environments. It enables rapid access to upstream features, hassle-free cluster management, and long-term stability for production-grade container orchestration.
 product_url: https://ubuntu.com/kubernetes
 works_on_arm: true
-release_date_on_arm: 2018/11/01
+release_date_on_arm: 2024/12/20
 
 
 optional_info:
     homepage_url: https://ubuntu.com/kubernetes
     support_caveats:
     alternative_options:
     getting_started_resources:
-        official_docs: https://ubuntu.com/kubernetes/install
+        official_docs: https://documentation.ubuntu.com/canonical-kubernetes/latest/
         arm_content:
-        vendor_announcement: https://canonical.com/blog/canonicals-distribution-of-kubernetes-supported-on-arm-architecture
+        vendor_announcement: https://documentation.ubuntu.com/canonical-kubernetes/release-1.32/charm/reference/versions/1.32/
 
 
 optional_hidden_info:

content/commercial_packages/cdk.md

@@ -0,0 +1,22 @@
+---
+name: Questa One Sim
+vendor: Siemens
+category: EDA
+description: Questa One Sim is a high-performance, multi-language functional verification simulator for ASIC, SoC, and FPGA designs, providing unified simulation, coverage, debug, and advanced verification technologies to accelerate coverage closure and improve verification productivity.
+product_url: https://eda.sw.siemens.com/en-US/ic/questa-one/simulation/questa-one-sim/
+works_on_arm: true
+release_date_on_arm: 2019/10/08
+ 
+ 
+optional_info:
+    homepage_url: https://eda.sw.siemens.com/en-US/ic/questa-one/simulation/questa-one-sim/
+    support_caveats:
+    alternative_options:
+    getting_started_resources:
+        official_docs:
+        arm_content:
+        vendor_announcement: https://news.siemens.com/en-us/siemens-mentor-boosts-64-bit-arm-based-server-platform-arm-architecture-support-for-questa-simulation-tools/
+optional_hidden_info:
+    other_info:
+
+---

content/commercial_packages/questa-one-sim.md

@@ -0,0 +1,31 @@
+---
+name: Albumentations
+category: AI/ML
+description: Albumentations is an open-source image augmentation library that helps improve computer vision models by efficiently applying rich, flexible transformations during training.
+download_url: https://pypi.org/project/albumentations/#history
+works_on_arm: true
+supported_minimum_version:
+    version_number: 0.0.2
+    release_date: 2018/06/28
+ 
+ 
+optional_info:
+    homepage_url: https://albumentations.ai/
+    support_caveats:
+    alternative_options:
+    getting_started_resources:
+        official_docs: https://albumentations.ai/docs/
+        arm_content:
+        partner_content:
+    arm_recommended_minimum_version:
+        version_number:
+        release_date:
+        reference_content:
+        rationale:
+ 
+optional_hidden_info:
+    release_notes__supported_minimum:
+    release_notes__recommended_minimum:
+    other_info: The release notes for the initial Linux/Arm64 support isn't available. Albumentations version on Pypi, 0.0.2, can be installed for Arm with pip, and python version 3.7.
+ 
+---

content/commercial_packages/questa_advance_simulator.md

@@ -0,0 +1,31 @@
+---
+name: Canonical Ceph
+category: Storage
+description: Charmed Ceph (Canonical Ceph) is an open-source, software-defined storage solution that delivers scalable object, block, and file storage on commodity hardware, with simplified deployment and lifecycle management using Canonical’s Juju charms.
+download_url: https://ubuntu.com/ceph/install
+works_on_arm: true
+supported_minimum_version:
+    version_number: Jewel (10.2.x)
+    release_date: 2016/10/17
+ 
+ 
+optional_info:
+    homepage_url: https://ubuntu.com/ceph
+    support_caveats:
+    alternative_options:
+    getting_started_resources:
+        official_docs: https://ubuntu.com/ceph/docs
+        arm_content:
+        partner_content:
+    arm_recommended_minimum_version:
+        version_number:
+        release_date:
+        reference_content:
+        rationale:
+ 
+optional_hidden_info:
+    release_notes__supported_minimum: https://canonical.com/blog/canonical-and-arm-collaborate-on-openstack
+    release_notes__recommended_minimum:
+    other_info: Jewel (10.2.x) was the stable version of Ceph active at the time of the October 17, 2016 announcement linked above. This reference indicates the availability of Canonical’s commercial support for Charmed Ceph on Arm64.
+ 
+---

content/opensource_packages/albumentations.md

@@ -0,0 +1,31 @@
+---
+name: CUDA Core Compute Libraries (CCCL)
+category: Compilers/Tools
+description: CUDA Core Compute Libraries (CCCL) is a unified collection of CUDA C++ libraries (Thrust, CUB, and libcudacxx) that provides high-performance parallel algorithms, low-level GPU primitives, and standard C++ abstractions for CUDA development.
+download_url: https://github.com/NVIDIA/cccl/releases
+works_on_arm: true
+supported_minimum_version:
+    version_number: 0.3.0
+    release_date: 2025/10/14
+ 
+ 
+optional_info:
+    homepage_url: https://nvidia.github.io/cccl/
+    support_caveats:
+    alternative_options:
+    getting_started_resources:
+        official_docs: https://github.com/NVIDIA/cccl#getting-started
+        arm_content:
+        partner_content:
+    arm_recommended_minimum_version:
+        version_number:
+        release_date:
+        reference_content:
+        rationale:
+ 
+optional_hidden_info:
+    release_notes__supported_minimum: https://github.com/NVIDIA/cccl/releases/tag/python-0.3.0
+    release_notes__recommended_minimum:
+    other_info:
+ 
+---

content/opensource_packages/canonical-ceph.md

@@ -0,0 +1,31 @@
+---
+name: Chiaki-ng
+category: Gaming
+description: Chiaki-ng is an open-source PlayStation Remote Play client that allows users to stream and play PS4/PS5 games on desktop platforms with improved features over the original Chiaki project.
+download_url: https://github.com/streetpea/chiaki-ng/releases
+works_on_arm: true
+supported_minimum_version:
+    version_number: 1.9.3
+    release_date: 2024/12/13
+ 
+ 
+optional_info:
+    homepage_url: https://streetpea.github.io/chiaki-ng/
+    support_caveats:
+    alternative_options:
+    getting_started_resources:
+        official_docs: https://streetpea.github.io/chiaki-ng/setup/installation/
+        arm_content:
+        partner_content:
+    arm_recommended_minimum_version:
+        version_number:
+        release_date:
+        reference_content:
+        rationale:
+ 
+optional_hidden_info:
+    release_notes__supported_minimum: https://github.com/streetpea/chiaki-ng/releases/tag/v1.9.3
+    release_notes__recommended_minimum:
+    other_info:
+ 
+---

content/opensource_packages/cccl.md

@@ -0,0 +1,31 @@
+---
+name: CuCIM
+category: AI/ML
+description: CuCIM is an open-source, CUDA-based image processing and computer vision library that provides GPU-accelerated primitives for multidimensional scientific and biomedical imaging workflows.
+download_url: https://github.com/rapidsai/cucim/releases
+works_on_arm: true
+supported_minimum_version:
+    version_number: 23.12.00
+    release_date: 2023/12/06
+ 
+ 
+optional_info:
+    homepage_url: https://docs.rapids.ai/api/cucim/stable/
+    support_caveats:
+    alternative_options:
+    getting_started_resources:
+        official_docs: https://github.com/rapidsai/cucim#install-cucim
+        arm_content:
+        partner_content:
+    arm_recommended_minimum_version:
+        version_number: 25.10.00
+        release_date: 2025/10/08
+        reference_content: https://github.com/rapidsai/cucim/blob/main/CHANGELOG.md#cucim-251000-8-oct-2025
+        rationale: In this release, two variants of the libcucim package were added, one with libcufile and one without libcufile to relax dependency for old CTK 12 on Arm.
+ 
+optional_hidden_info:
+    release_notes__supported_minimum: https://github.com/rapidsai/cucim/blob/main/CHANGELOG.md#cucim-231200-6-dec-2023
+    release_notes__recommended_minimum:
+    other_info:
+ 
+---

content/opensource_packages/chiaki-ng.md

@@ -0,0 +1,31 @@
+---
+name: CUDA-Python
+category: Languages and Frameworks
+description: CUDA Python is a collection of Python libraries and DSLs that provide direct, high-level and low-level access to NVIDIA CUDA APIs, enabling GPU programming, parallel algorithms, and profiling from Python.
+download_url: https://github.com/NVIDIA/cuda-python/releases
+works_on_arm: true
+supported_minimum_version:
+    version_number: 11.5.0
+    release_date: 2021/10/21
+ 
+ 
+optional_info:
+    homepage_url: https://nvidia.github.io/cuda-python/latest/
+    support_caveats:
+    alternative_options:
+    getting_started_resources:
+        official_docs: https://nvidia.github.io/cuda-python/cuda-bindings/latest/install.html
+        arm_content:
+        partner_content:
+    arm_recommended_minimum_version:
+        version_number:
+        release_date:
+        reference_content:
+        rationale:
+ 
+optional_hidden_info:
+    release_notes__supported_minimum:
+    release_notes__recommended_minimum:
+    other_info: The release notes for the initial Linux/Arm64 support isn't available. Cuda-python provides official manylinux Aarch64 wheels starting from version 11.5.0, indicating Linux Arm64 support. Users should validate functionality against their target CUDA driver, toolkit, and GPU platform. Please see [this](https://pypi.org/project/cuda-python/11.5.0/#files).
+ 
+---