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github-bot pushed a commit to branch asf-site
in repository https://gitbox.apache.org/repos/asf/tvm-site.git
The following commit(s) were added to refs/heads/asf-site by this push:
new d71ae2c7c7 Build at Tue Oct 21 20:52:30 UTC 2025
d71ae2c7c7 is described below
commit d71ae2c7c7f118c58376d9534a4fe4ff449b00cc
Author: tvm-bot <[email protected]>
AuthorDate: Tue Oct 21 20:52:30 2025 +0000
Build at Tue Oct 21 20:52:30 UTC 2025
---
2025/10/21/tvm-ffi.html | 2 +-
atom.xml | 4 ++--
feed.xml | 4 ++--
rss.xml | 6 +++---
4 files changed, 8 insertions(+), 8 deletions(-)
diff --git a/2025/10/21/tvm-ffi.html b/2025/10/21/tvm-ffi.html
index a4a99bee50..0fb4b19c97 100644
--- a/2025/10/21/tvm-ffi.html
+++ b/2025/10/21/tvm-ffi.html
@@ -261,7 +261,7 @@ Please checkout the following resources:</p>
<p>The project draws collective wisdoms of the Machine Learning System
community and python open source ecosystem, including past development insights
of many developers from numpy, PyTorch, JAX, Caffe, mxnet, XGBoost, cuPy,
pybind11, nanobind and more.</p>
-<p>We would specifically like to thank the PyTorch team, JAX team, CUDA python
team, cuteDSL team, cuTile team, Apache TVM community, XGBoost team, TiLang
team, Triton distributed team, FlashInfer team, SGLang community,
TensorRT-LLM community, the vLLM community, for their their insightful
feedbacks.</p>
+<p>We would specifically like to thank the PyTorch team, JAX team, CUDA python
team, cuteDSL team, cuTile team, Apache TVM community, XGBoost team,
TileLang team, Triton distributed team, FlashInfer team, SGLang community,
TensorRT-LLM community, the vLLM community, for their their insightful
feedbacks.</p>
</div>
</div>
diff --git a/atom.xml b/atom.xml
index ce4ebb3fe8..0cc512185b 100644
--- a/atom.xml
+++ b/atom.xml
@@ -4,7 +4,7 @@
<title>TVM</title>
<link href="https://tvm.apache.org"; rel="self"/>
<link href="https://tvm.apache.org"/>
- <updated>2025-10-21T18:41:46+00:00</updated>
+ <updated>2025-10-21T20:51:57+00:00</updated>
<id>https://tvm.apache.org</id>
<author>
<name></name>
@@ -132,7 +132,7 @@ Please checkout the following resources:</p>
<p>The project draws collective wisdoms of the Machine Learning System
community and python open source ecosystem, including past development insights
of many developers from numpy, PyTorch, JAX, Caffe, mxnet, XGBoost, cuPy,
pybind11, nanobind and more.</p>
-<p>We would specifically like to thank the PyTorch team, JAX team, CUDA
python team, cuteDSL team, cuTile team, Apache TVM community, XGBoost team,
TiLang team, Triton distributed team, FlashInfer team, SGLang community,
TensorRT-LLM community, the vLLM community, for their their insightful
feedbacks.</p>
+<p>We would specifically like to thank the PyTorch team, JAX team, CUDA
python team, cuteDSL team, cuTile team, Apache TVM community, XGBoost team,
TileLang team, Triton distributed team, FlashInfer team, SGLang community,
TensorRT-LLM community, the vLLM community, for their their insightful
feedbacks.</p>
</content>
</entry>
diff --git a/feed.xml b/feed.xml
index e4de81d9e0..77489431c4 100644
--- a/feed.xml
+++ b/feed.xml
@@ -1,4 +1,4 @@
-<?xml version="1.0" encoding="utf-8"?><feed
xmlns="http://www.w3.org/2005/Atom"; ><generator uri="https://jekyllrb.com/";
version="4.4.1">Jekyll</generator><link href="/feed.xml" rel="self"
type="application/atom+xml" /><link href="/" rel="alternate" type="text/html"
/><updated>2025-10-21T18:41:46+00:00</updated><id>/feed.xml</id><title
type="html">TVM</title><author><name>{"name" =>
nil}</name></author><entry><title type="html">Building an Open ABI and FFI for
ML Systems</tit [...]
+<?xml version="1.0" encoding="utf-8"?><feed
xmlns="http://www.w3.org/2005/Atom"; ><generator uri="https://jekyllrb.com/";
version="4.4.1">Jekyll</generator><link href="/feed.xml" rel="self"
type="application/atom+xml" /><link href="/" rel="alternate" type="text/html"
/><updated>2025-10-21T20:51:57+00:00</updated><id>/feed.xml</id><title
type="html">TVM</title><author><name>{"name" =>
nil}</name></author><entry><title type="html">Building an Open ABI and FFI for
ML Systems</tit [...]
<p>The exciting growth of the ecosystem is the reason for the fast pace of
innovation in AI today. However, it also presents a significant challenge:
<strong>interoperability</strong>. Many of those components need to integrate
with each other. For example, libraries such as FlashInfer, cuDNN needs to be
integrated into PyTorch, JAX, TensorRT’s runtime system, each may come with
different interface requirements. ML compilers and DSLs also usually expose
Python JIT binding support, while [...]
@@ -113,7 +113,7 @@ Please checkout the following resources:</p>
<p>The project draws collective wisdoms of the Machine Learning System
community and python open source ecosystem, including past development insights
of many developers from numpy, PyTorch, JAX, Caffe, mxnet, XGBoost, cuPy,
pybind11, nanobind and more.</p>
-<p>We would specifically like to thank the PyTorch team, JAX team, CUDA python
team, cuteDSL team, cuTile team, Apache TVM community, XGBoost team, TiLang
team, Triton distributed team, FlashInfer team, SGLang community,
TensorRT-LLM community, the vLLM community, for their their insightful
feedbacks.</p>]]></content><author><name>Apache TVM FFI
Community</name></author><summary type="html"><![CDATA[We are currently living
in an exciting era for AI, where machine learning systems a [...]
+<p>We would specifically like to thank the PyTorch team, JAX team, CUDA python
team, cuteDSL team, cuTile team, Apache TVM community, XGBoost team,
TileLang team, Triton distributed team, FlashInfer team, SGLang community,
TensorRT-LLM community, the vLLM community, for their their insightful
feedbacks.</p>]]></content><author><name>Apache TVM FFI
Community</name></author><summary type="html"><![CDATA[We are currently living
in an exciting era for AI, where machine learning systems [...]
<h2 id="boundaries-in-the-modern-ml-system-stack">Boundaries in the Modern ML
System Stack</h2>
diff --git a/rss.xml b/rss.xml
index d58240bbfa..de2e7e52de 100644
--- a/rss.xml
+++ b/rss.xml
@@ -5,8 +5,8 @@
<description>TVM - </description>
<link>https://tvm.apache.org</link>
<atom:link href="https://tvm.apache.org"; rel="self"
type="application/rss+xml" />
- <lastBuildDate>Tue, 21 Oct 2025 18:41:46 +0000</lastBuildDate>
- <pubDate>Tue, 21 Oct 2025 18:41:46 +0000</pubDate>
+ <lastBuildDate>Tue, 21 Oct 2025 20:51:57 +0000</lastBuildDate>
+ <pubDate>Tue, 21 Oct 2025 20:51:57 +0000</pubDate>
<ttl>60</ttl>
@@ -127,7 +127,7 @@ Please checkout the following resources:</p>
<p>The project draws collective wisdoms of the Machine Learning System
community and python open source ecosystem, including past development insights
of many developers from numpy, PyTorch, JAX, Caffe, mxnet, XGBoost, cuPy,
pybind11, nanobind and more.</p>
-<p>We would specifically like to thank the PyTorch team, JAX team, CUDA
python team, cuteDSL team, cuTile team, Apache TVM community, XGBoost team,
TiLang team, Triton distributed team, FlashInfer team, SGLang community,
TensorRT-LLM community, the vLLM community, for their their insightful
feedbacks.</p>
+<p>We would specifically like to thank the PyTorch team, JAX team, CUDA
python team, cuteDSL team, cuTile team, Apache TVM community, XGBoost team,
TileLang team, Triton distributed team, FlashInfer team, SGLang community,
TensorRT-LLM community, the vLLM community, for their their insightful
feedbacks.</p>
</description>
<link>https://tvm.apache.org/2025/10/21/tvm-ffi</link>
<guid>https://tvm.apache.org/2025/10/21/tvm-ffi</guid>
