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Roadmap addition (#22235)

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Added ORT 1.20 roadmap
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src/routes/components/header.svelte
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@ -46,6 +46,7 @@
<li>
<p class="hover:bg-primary focus:bg-primary">Community</p>
<ul class="p-2">
<li><a class="hover:bg-primary focus:bg-primary" href={pathvar + '/roadmap'}>Roadmap</a></li>
<li><a class="hover:bg-primary focus:bg-primary" href={pathvar + '/events'}>Events</a></li>
<li><a class="hover:bg-primary focus:bg-primary" href={pathvar + '/testimonials'}>Testimonials</a></li>
<li>
@ -93,6 +94,7 @@
<details class="z-[1]">
<summary class="hover:bg-primary focus:bg-primary">Community</summary>
<ul class="p-2">
<li><a class="hover:bg-primary focus:bg-primary" href={pathvar + '/roadmap'}>Roadmap</a></li>
<li><a class="hover:bg-primary focus:bg-primary" href={pathvar + '/events'}>Events</a></li>
<li><a class="hover:bg-primary focus:bg-primary" href={pathvar + '/testimonials'}>Testimonials</a></li>
<li>

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src/routes/roadmap/+page.svelte Normal file
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<div class="container mx-auto px-8">
<h1 class="text-3xl">ONNX Runtime Release Roadmap</h1>
<p>
ONNX Runtime is released on a quarterly basis. Patch releases are published between major
releases as necessary.
</p>
<div class="flex justify-center my-4">
<div class="stats stats-vertical md:stats-horizontal shadow rounded-sm">
<div class="stat">
<div class="stat-figure">
<svg
class="stroke-success"
xmlns="http://www.w3.org/2000/svg"
width="32"
height="32"
viewBox="0 0 24 24"
fill="none"
stroke="#000000"
stroke-width="2"
stroke-linecap="round"
stroke-linejoin="round"><polyline points="20 6 9 17 4 12" /></svg
>
</div>
<div class="stat-title">Previous release</div>
<div class="stat-value text-success">1.19.2</div>
<div class="stat-desc">Release date: 9/4/2024</div>
</div>
<div class="stat">
<div class="stat-figure text-secondary">
<svg
xmlns="http://www.w3.org/2000/svg"
width="24"
height="24"
class="stroke-warning"
viewBox="0 0 24 24"
fill="none"
stroke-width="2"
stroke-linecap="round"
stroke-linejoin="round"
><circle cx="12" cy="12" r="3" /><path
d="M19.4 15a1.65 1.65 0 0 0 .33 1.82l.06.06a2 2 0 0 1 0 2.83 2 2 0 0 1-2.83 0l-.06-.06a1.65 1.65 0 0 0-1.82-.33 1.65 1.65 0 0 0-1 1.51V21a2 2 0 0 1-2 2 2 2 0 0 1-2-2v-.09A1.65 1.65 0 0 0 9 19.4a1.65 1.65 0 0 0-1.82.33l-.06.06a2 2 0 0 1-2.83 0 2 2 0 0 1 0-2.83l.06-.06a1.65 1.65 0 0 0 .33-1.82 1.65 1.65 0 0 0-1.51-1H3a2 2 0 0 1-2-2 2 2 0 0 1 2-2h.09A1.65 1.65 0 0 0 4.6 9a1.65 1.65 0 0 0-.33-1.82l-.06-.06a2 2 0 0 1 0-2.83 2 2 0 0 1 2.83 0l.06.06a1.65 1.65 0 0 0 1.82.33H9a1.65 1.65 0 0 0 1-1.51V3a2 2 0 0 1 2-2 2 2 0 0 1 2 2v.09a1.65 1.65 0 0 0 1 1.51 1.65 1.65 0 0 0 1.82-.33l.06-.06a2 2 0 0 1 2.83 0 2 2 0 0 1 0 2.83l-.06.06a1.65 1.65 0 0 0-.33 1.82V9a1.65 1.65 0 0 0 1.51 1H21a2 2 0 0 1 2 2 2 2 0 0 1-2 2h-.09a1.65 1.65 0 0 0-1.51 1z"
/></svg
>
</div>
<div class="font-bold underline">In-Progress Release</div>
<div class="stat-value text-warning">1.20</div>
<div class="stat-desc">Release date: 10/30/2024</div>
</div>
<div class="stat">
<div class="stat-figure text-primary">
<svg
xmlns="http://www.w3.org/2000/svg"
fill="none"
viewBox="0 0 24 24"
class="stroke-primary"
width="28"
height="28"
>
<path
stroke-linecap="round"
stroke-linejoin="round"
stroke-width="2"
d="M6 2h12M6 22h12M8 2v6l4 4-4 4v6M16 2v6l-4 4 4 4v6"
/>
</svg>
</div>
<div class="stat-title">Next release</div>
<div class="stat-value text-primary">1.21</div>
<div class="stat-desc">Release date: Feb. 2025</div>
</div>
</div>
</div>
<h2 class="text-xl font-bold mt-2">Announcements</h2>
<p class="font-thin">
<strong>All ONNX Runtime Training packages have been deprecated.</strong> ORT 1.19.2 was the last
release for which onnxruntime-training (PyPI), onnxruntime-training-cpu (PyPI), Microsoft.ML.OnnxRuntime.Training
(Nuget), onnxruntime-training-c (CocoaPods), onnxruntime-training-objc (CocoaPods), and onnxruntime-training-android
(Maven Central) were published. ONNX Runtime packages will stop supporting Python 3.8 and Python
3.9. This decision aligns with NumPy Python version support. To continue using ORT with Python 3.8
and Python 3.9, you can use ORT 1.19.2 and earlier.
</p>
<h2 class="text-xl font-bold mt-2">New Packages</h2>
<p class="font-thin">We are planning to start releasing the following packages:</p>
<ul class="list-disc ml-8">
<li>Maven package with Android support for QNN EP</li>
<li>CocoaPods package with Mac / iOS support for ORT GenAI</li>
</ul>
<h2 class="text-xl font-bold mt-2">Versioning Updates</h2>
<p class="font-thin">
We are planning to upgrade ONNX Runtime support for the following (where the first value is the
highest version previously supported and the second value is the version support that will be
added in ORT 1.20):
</p>
<ul class="list-disc ml-8">
<li>ONNX 1.16.1 --> 1.17.0</li>
<li>TensorRT 10.2 --> 10.4</li>
<li>DirectML 1.15.1 --> 1.15.2</li>
</ul>
<h2 class="text-xl font-bold mt-2">Major Updates</h2>
<p class="font-thin">
In addition to various bug fixes and performance improvements, ORT 1.20 will include the
following major updates:
</p>
<ul class="list-disc ml-8">
<li>Add MultiLoRA support.</li>
<li>Improve CPU FP16 and INT4 performance.</li>
<li>
Increase GenAI API model support, including Whisper, Phi-3.5-vision multi-frame, and more.
</li>
<li>Publish Phi-3.5 ONNX model variants to Hugging Face.</li>
<li>
Expand mobile support to include GPU EP and FP16 support for CoreML EP and XNNPACK kernels.
</li>
<li>Add Apple support for AI Toolkit for VS Code.</li>
</ul>
<h2 class="text-xl font-bold mt-2">Feature Requests</h2>
<p class="font-thin">
To request new ONNX Runtime features to be included in a future release, please submit a feature
request through <a
href="https://github.com/microsoft/onnxruntime/issues/new?assignees=&labels=feature+request&projects=&template=07-feature_request.yml&title=%5BFeature+Request%5D+"
class="text-blue-600 underline">GitHub Issues</a
>
or through
<a
href="https://github.com/microsoft/onnxruntime/discussions/new?category=ideas-feature-requests"
class="text-blue-600 underline">GitHub Discussions</a
>.
</p>
<p class="font-thin">To ensure that your request is addressed as quickly as possible, please:</p>
<ul class="list-disc ml-8">
<li>Include a detailed title.</li>
<li>
Provide as much detail as possible in the body of your request (e.g., use case for the
feature, the platform(s) or EP(s) this feature is needed for, etc.).
</li>
<li>
Apply a label corresponding to the appropriate ONNX Runtime area (e.g., "platform:mobile",
"platform:web", "ep:CUDA", etc.) if you know it.
</li>
</ul>
<p class="font-thin">
<em>Note: All timelines and features listed on this page are subject to change.</em>
</p>
<div class="divider"></div>
<h2 class="text-xl font-bold mt-2">ONNX Runtime 1.20</h2>
<p class="font-thin">
<strong>Tentative release date:</strong> 10/30/2024
</p>
<div class="join join-vertical w-full p-2">
<!-- Announcements Section -->
<div class="collapse collapse-arrow join-item border-base-300 border">
<input type="checkbox" name="announcements" />
<div class="collapse-title text-xl font-bold">Announcements</div>
<div class="collapse-content">
<p class="font-thin">
<strong>All ONNX Runtime Training packages have been deprecated.</strong> ORT 1.19.2 was the
last release for which onnxruntime-training (PyPI), onnxruntime-training-cpu (PyPI), Microsoft.ML.OnnxRuntime.Training
(Nuget), onnxruntime-training-c (CocoaPods), onnxruntime-training-objc (CocoaPods), and onnxruntime-training-android
(Maven Central) were published. ONNX Runtime packages will stop supporting Python 3.8 and Python
3.9. This decision aligns with NumPy Python version support. To continue using ORT with Python
3.8 and Python 3.9, you can use ORT 1.19.2 and earlier.
</p>
</div>
</div>
<!-- Build System & Packages Section -->
<div class="collapse collapse-arrow join-item border-base-300 border">
<input type="checkbox" name="build" />
<div class="collapse-title text-xl font-bold">Build System & Packages</div>
<div class="collapse-content">
<ul class="list-disc ml-8">
<li>Upgrade ONNX support from 1.16.1 to 1.17.0.</li>
<li>Add Python 3.12 support for Windows ARM64.</li>
<li>Add vcpkg support.</li>
<li>
Digitally sign DLLs in Maven build.
</li>
</ul>
</div>
</div>
<!-- Core Section -->
<div class="collapse collapse-arrow join-item border-base-300 border">
<input type="checkbox" name="core" />
<div class="collapse-title text-xl font-bold">Core</div>
<div class="collapse-content">
<ul class="list-disc ml-8">
<li>Add MultiLoRA support.</li>
<li>
Improve ThreadPool to spend less time busy waiting.
</li>
<li>Improve memory utilization, particularly related to external weights.</li>
<li>Improve partitioning.</li>
</ul>
</div>
</div>
<!-- Performance Section -->
<div class="collapse collapse-arrow join-item border-base-300 border">
<input type="checkbox" name="performance" />
<div class="collapse-title text-xl font-bold">Performance</div>
<div class="collapse-content">
<ul class="list-disc ml-8">
<li>Add FP16 SLM model support on CPU.</li>
<li>Add INT4 quantized embedding support on CPU and CUDA.</li>
</ul>
</div>
</div>
<!-- EPs Section -->
<div class="collapse collapse-arrow join-item border-base-300 border">
<input type="checkbox" name="eps" />
<div class="collapse-title text-xl font-bold">EPs</div>
<div class="collapse-content">
<h3 class="text-lg font-semibold">TensorRT</h3>
<ul class="list-disc ml-8">
<li>Upgrade TensorRT support from 10.2 to 10.4.</li>
<li>Enable DDS, including performance fixes for NMS.</li>
</ul>
<h3 class="text-lg font-semibold">QNN</h3>
<ul class="list-disc ml-8">
<li>Add HTP shared weights context binary.</li>
<li>Add runtime support for HTP shared weights in multiple ORT sessions.</li>
<li>Add efficient mode support.</li>
</ul>
<h3 class="text-lg font-semibold">OpenVINO</h3>
<ul class="list-disc ml-8">
<li>Add context generation memory optimizations.</li>
<li>Add efficient mode support.</li>
</ul>
<h3 class="text-lg font-semibold">DirectML</h3>
<ul class="list-disc ml-8">
<li>Upgrade DirectML support from 1.15.1 to 1.15.2.</li>
</ul>
</div>
</div>
<!-- Mobile Section -->
<div class="collapse collapse-arrow join-item border-base-300 border">
<input type="checkbox" name="mobile" />
<div class="collapse-title text-xl font-bold">Mobile</div>
<div class="collapse-content">
<ul class="list-disc ml-8">
<li>
Add Android QNN support, including a pre-build package, performance improvements, and
Phi-3 model support.
</li>
<li>Add GPU EP support for ORT Mobile.</li>
<li>Add FP16 support for CoreML EP and XNNPACK kernels.</li>
</ul>
</div>
</div>
<!-- Web Section -->
<div class="collapse collapse-arrow join-item border-base-300 border">
<input type="checkbox" name="web" />
<div class="collapse-title text-xl font-bold">Web</div>
<div class="collapse-content">
<ul class="list-disc ml-8">
<li>Add quantized embedding support.</li>
<li>
Add on-demand weight loading support, which offloads wasm32 heap and enables
8B-parameter LLM models.
</li>
<li>
Add support for wasm64 through a custom build (will not be included in released
packages).
</li>
<li>Add GQA support.</li>
<li>Improve performance for integrated Intel GPU.</li>
<li>Add support for Opset 21, including Reshape, Shape, and Gelu.</li>
</ul>
</div>
</div>
<!-- GenAI Section -->
<div class="collapse collapse-arrow join-item border-base-300 border">
<input type="checkbox" name="genai" />
<div class="collapse-title text-xl font-bold">GenAI</div>
<div class="collapse-content">
<ul class="list-disc ml-8">
<li>Add continuous decoding support, including chat mode and system prompt caching.</li>
<li>Introduce MultiLoRA API.</li>
<li>Add Whisper model support.</li>
<li>Add Phi-3.5-vision multi-frame model support.</li>
<li>Add Phi-3.5 and Llama-3.1 model support on Qualcomm NPU.</li>
<li>Introduce packages for Mac/iOS.</li>
</ul>
</div>
</div>
<!-- Extensions Section -->
<div class="collapse collapse-arrow join-item border-base-300 border">
<input type="checkbox" name="extensions" />
<div class="collapse-title text-xl font-bold">Extensions</div>
<div class="collapse-content">
<ul class="list-disc ml-8">
<li>Improve performance profiling and optimize tokenization.</li>
<li>Increase multi-modal model support, including more kernel attributes.</li>
<li>Add Unigram tokenization model support.</li>
<li>Remove OpenCV dependency from C API build.</li>
</ul>
</div>
</div>
</div>
</div>